2009-01-29 Robert Millan <rmh@aybabtu.com>

[pf3gnuchains/gcc-fork.git] / gcc / tree-vect-transform.c

/* Transformation Utilities for Loop Vectorization.
   Copyright (C) 2003, 2004, 2005, 2006, 2007, 2008 Free Software Foundation, Inc.
   Contributed by Dorit Naishlos <dorit@il.ibm.com>

This file is part of GCC.

GCC is free software; you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free
Software Foundation; either version 3, or (at your option) any later
version.

GCC is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or
FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
for more details.

You should have received a copy of the GNU General Public License
along with GCC; see the file COPYING3.  If not see
<http://www.gnu.org/licenses/>.  */

#include "config.h"
#include "system.h"
#include "coretypes.h"
#include "tm.h"
#include "ggc.h"
#include "tree.h"
#include "target.h"
#include "rtl.h"
#include "basic-block.h"
#include "diagnostic.h"
#include "tree-flow.h"
#include "tree-dump.h"
#include "timevar.h"
#include "cfgloop.h"
#include "expr.h"
#include "optabs.h"
#include "params.h"
#include "recog.h"
#include "tree-data-ref.h"
#include "tree-chrec.h"
#include "tree-scalar-evolution.h"
#include "tree-vectorizer.h"
#include "langhooks.h"
#include "tree-pass.h"
#include "toplev.h"
#include "real.h"

/* Utility functions for the code transformation.  */
static bool vect_transform_stmt (gimple, gimple_stmt_iterator *, bool *,
                                 slp_tree, slp_instance);
static tree vect_create_destination_var (tree, tree);
static tree vect_create_data_ref_ptr 
  (gimple, struct loop*, tree, tree *, gimple *, bool, bool *, tree);
static tree vect_create_addr_base_for_vector_ref 
  (gimple, gimple_seq *, tree, struct loop *);
static tree vect_get_new_vect_var (tree, enum vect_var_kind, const char *);
static tree vect_get_vec_def_for_operand (tree, gimple, tree *);
static tree vect_init_vector (gimple, tree, tree, gimple_stmt_iterator *);
static void vect_finish_stmt_generation 
  (gimple stmt, gimple vec_stmt, gimple_stmt_iterator *);
static bool vect_is_simple_cond (tree, loop_vec_info); 
static void vect_create_epilog_for_reduction 
  (tree, gimple, int, enum tree_code, gimple);
static tree get_initial_def_for_reduction (gimple, tree, tree *);

/* Utility function dealing with loop peeling (not peeling itself).  */
static void vect_generate_tmps_on_preheader 
  (loop_vec_info, tree *, tree *, tree *);
static tree vect_build_loop_niters (loop_vec_info);
static void vect_update_ivs_after_vectorizer (loop_vec_info, tree, edge); 
static tree vect_gen_niters_for_prolog_loop (loop_vec_info, tree);
static void vect_update_init_of_dr (struct data_reference *, tree niters);
static void vect_update_inits_of_drs (loop_vec_info, tree);
static int vect_min_worthwhile_factor (enum tree_code);


static int
cost_for_stmt (gimple stmt)
{
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);

  switch (STMT_VINFO_TYPE (stmt_info))
  {
  case load_vec_info_type:
    return TARG_SCALAR_LOAD_COST;
  case store_vec_info_type:
    return TARG_SCALAR_STORE_COST;
  case op_vec_info_type:
  case condition_vec_info_type:
  case assignment_vec_info_type:
  case reduc_vec_info_type:
  case induc_vec_info_type:
  case type_promotion_vec_info_type:
  case type_demotion_vec_info_type:
  case type_conversion_vec_info_type:
  case call_vec_info_type:
    return TARG_SCALAR_STMT_COST;
  case undef_vec_info_type:
  default:
    gcc_unreachable ();
  }
}


/* Function vect_estimate_min_profitable_iters

   Return the number of iterations required for the vector version of the
   loop to be profitable relative to the cost of the scalar version of the
   loop.

   TODO: Take profile info into account before making vectorization
   decisions, if available.  */

int
vect_estimate_min_profitable_iters (loop_vec_info loop_vinfo)
{
  int i;
  int min_profitable_iters;
  int peel_iters_prologue;
  int peel_iters_epilogue;
  int vec_inside_cost = 0;
  int vec_outside_cost = 0;
  int scalar_single_iter_cost = 0;
  int scalar_outside_cost = 0;
  int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
  int nbbs = loop->num_nodes;
  int byte_misalign = LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo);
  int peel_guard_costs = 0;
  int innerloop_iters = 0, factor;
  VEC (slp_instance, heap) *slp_instances;
  slp_instance instance;

  /* Cost model disabled.  */
  if (!flag_vect_cost_model)
    {
      if (vect_print_dump_info (REPORT_COST))
        fprintf (vect_dump, "cost model disabled.");      
      return 0;
    }

  /* Requires loop versioning tests to handle misalignment.  */
  if (VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo)))
    {
      /*  FIXME: Make cost depend on complexity of individual check.  */
      vec_outside_cost +=
        VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo));
      if (vect_print_dump_info (REPORT_COST))
        fprintf (vect_dump, "cost model: Adding cost of checks for loop "
                 "versioning to treat misalignment.\n");
    }

  if (VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo)))
    {
      /*  FIXME: Make cost depend on complexity of individual check.  */
      vec_outside_cost +=
        VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo));
      if (vect_print_dump_info (REPORT_COST))
        fprintf (vect_dump, "cost model: Adding cost of checks for loop "
                 "versioning aliasing.\n");
    }

  if (VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo))
      || VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo)))
    {
      vec_outside_cost += TARG_COND_TAKEN_BRANCH_COST;
    }

  /* Count statements in scalar loop.  Using this as scalar cost for a single
     iteration for now.

     TODO: Add outer loop support.

     TODO: Consider assigning different costs to different scalar
     statements.  */

  /* FORNOW.  */
  if (loop->inner)
    innerloop_iters = 50; /* FIXME */

  for (i = 0; i < nbbs; i++)
    {
      gimple_stmt_iterator si;
      basic_block bb = bbs[i];

      if (bb->loop_father == loop->inner)
        factor = innerloop_iters;
      else
        factor = 1;

      for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
        {
          gimple stmt = gsi_stmt (si);
          stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
          /* Skip stmts that are not vectorized inside the loop.  */
          if (!STMT_VINFO_RELEVANT_P (stmt_info)
              && (!STMT_VINFO_LIVE_P (stmt_info)
                  || STMT_VINFO_DEF_TYPE (stmt_info) != vect_reduction_def))
            continue;
          scalar_single_iter_cost += cost_for_stmt (stmt) * factor;
          vec_inside_cost += STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info) * factor;
          /* FIXME: for stmts in the inner-loop in outer-loop vectorization,
             some of the "outside" costs are generated inside the outer-loop.  */
          vec_outside_cost += STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info);
        }
    }

  /* Add additional cost for the peeled instructions in prologue and epilogue
     loop.

     FORNOW: If we don't know the value of peel_iters for prologue or epilogue
     at compile-time - we assume it's vf/2 (the worst would be vf-1).

     TODO: Build an expression that represents peel_iters for prologue and
     epilogue to be used in a run-time test.  */

  if (byte_misalign < 0)
    {
      peel_iters_prologue = vf/2;
      if (vect_print_dump_info (REPORT_COST))
        fprintf (vect_dump, "cost model: "
                 "prologue peel iters set to vf/2.");

      /* If peeling for alignment is unknown, loop bound of main loop becomes
         unknown.  */
      peel_iters_epilogue = vf/2;
      if (vect_print_dump_info (REPORT_COST))
        fprintf (vect_dump, "cost model: "
                 "epilogue peel iters set to vf/2 because "
                 "peeling for alignment is unknown .");

      /* If peeled iterations are unknown, count a taken branch and a not taken
         branch per peeled loop. Even if scalar loop iterations are known,
         vector iterations are not known since peeled prologue iterations are
         not known. Hence guards remain the same.  */
      peel_guard_costs +=  2 * (TARG_COND_TAKEN_BRANCH_COST
                              + TARG_COND_NOT_TAKEN_BRANCH_COST);
    }
  else 
    {
      if (byte_misalign)
        {
          struct data_reference *dr = LOOP_VINFO_UNALIGNED_DR (loop_vinfo);
          int element_size = GET_MODE_SIZE (TYPE_MODE (TREE_TYPE (DR_REF (dr))));
          tree vectype = STMT_VINFO_VECTYPE (vinfo_for_stmt (DR_STMT (dr)));
          int nelements = TYPE_VECTOR_SUBPARTS (vectype);

          peel_iters_prologue = nelements - (byte_misalign / element_size);
        }
      else
        peel_iters_prologue = 0;

      if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
        {
          peel_iters_epilogue = vf/2;
          if (vect_print_dump_info (REPORT_COST))
            fprintf (vect_dump, "cost model: "
                     "epilogue peel iters set to vf/2 because "
                     "loop iterations are unknown .");

          /* If peeled iterations are known but number of scalar loop
             iterations are unknown, count a taken branch per peeled loop.  */
          peel_guard_costs +=  2 * TARG_COND_TAKEN_BRANCH_COST;

        }
      else      
        {
          int niters = LOOP_VINFO_INT_NITERS (loop_vinfo);
          peel_iters_prologue = niters < peel_iters_prologue ? 
                                        niters : peel_iters_prologue;
          peel_iters_epilogue = (niters - peel_iters_prologue) % vf;
        }
    }

  vec_outside_cost += (peel_iters_prologue * scalar_single_iter_cost)
                      + (peel_iters_epilogue * scalar_single_iter_cost)
                      + peel_guard_costs;

  /* FORNOW: The scalar outside cost is incremented in one of the
     following ways:

     1. The vectorizer checks for alignment and aliasing and generates
     a condition that allows dynamic vectorization.  A cost model
     check is ANDED with the versioning condition.  Hence scalar code
     path now has the added cost of the versioning check.

       if (cost > th & versioning_check)
         jmp to vector code

     Hence run-time scalar is incremented by not-taken branch cost.

     2. The vectorizer then checks if a prologue is required.  If the
     cost model check was not done before during versioning, it has to
     be done before the prologue check.

       if (cost <= th)
         prologue = scalar_iters
       if (prologue == 0)
         jmp to vector code
       else
         execute prologue
       if (prologue == num_iters)
         go to exit

     Hence the run-time scalar cost is incremented by a taken branch,
     plus a not-taken branch, plus a taken branch cost.

     3. The vectorizer then checks if an epilogue is required.  If the
     cost model check was not done before during prologue check, it
     has to be done with the epilogue check.

       if (prologue == 0)
         jmp to vector code
       else
         execute prologue
       if (prologue == num_iters)
         go to exit
       vector code:
         if ((cost <= th) | (scalar_iters-prologue-epilogue == 0))
           jmp to epilogue

     Hence the run-time scalar cost should be incremented by 2 taken
     branches.

     TODO: The back end may reorder the BBS's differently and reverse
     conditions/branch directions.  Change the estimates below to
     something more reasonable.  */

  /* If the number of iterations is known and we do not do versioning, we can
     decide whether to vectorize at compile time. Hence the scalar version
     do not carry cost model guard costs.  */
  if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
      || VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo))
      || VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo)))
    {
      /* Cost model check occurs at versioning.  */
      if (VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo))
          || VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo)))
        scalar_outside_cost += TARG_COND_NOT_TAKEN_BRANCH_COST;
      else
        {
          /* Cost model check occurs at prologue generation.  */
          if (LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo) < 0)
            scalar_outside_cost += 2 * TARG_COND_TAKEN_BRANCH_COST
              + TARG_COND_NOT_TAKEN_BRANCH_COST;
          /* Cost model check occurs at epilogue generation.  */
          else
            scalar_outside_cost += 2 * TARG_COND_TAKEN_BRANCH_COST;
        }
    }

  /* Add SLP costs.  */
  slp_instances = LOOP_VINFO_SLP_INSTANCES (loop_vinfo);
  for (i = 0; VEC_iterate (slp_instance, slp_instances, i, instance); i++)
    {
      vec_outside_cost += SLP_INSTANCE_OUTSIDE_OF_LOOP_COST (instance);
      vec_inside_cost += SLP_INSTANCE_INSIDE_OF_LOOP_COST (instance);
    }

  /* Calculate number of iterations required to make the vector version 
     profitable, relative to the loop bodies only. The following condition
     must hold true: 
     SIC * niters + SOC > VIC * ((niters-PL_ITERS-EP_ITERS)/VF) + VOC
     where
     SIC = scalar iteration cost, VIC = vector iteration cost,
     VOC = vector outside cost, VF = vectorization factor,
     PL_ITERS = prologue iterations, EP_ITERS= epilogue iterations
     SOC = scalar outside cost for run time cost model check.  */

  if ((scalar_single_iter_cost * vf) > vec_inside_cost)
    {
      if (vec_outside_cost <= 0)
        min_profitable_iters = 1;
      else
        {
          min_profitable_iters = ((vec_outside_cost - scalar_outside_cost) * vf
                                  - vec_inside_cost * peel_iters_prologue
                                  - vec_inside_cost * peel_iters_epilogue)
                                 / ((scalar_single_iter_cost * vf)
                                    - vec_inside_cost);

          if ((scalar_single_iter_cost * vf * min_profitable_iters)
              <= ((vec_inside_cost * min_profitable_iters)
                  + ((vec_outside_cost - scalar_outside_cost) * vf)))
            min_profitable_iters++;
        }
    }
  /* vector version will never be profitable.  */
  else
    {
      if (vect_print_dump_info (REPORT_COST))
        fprintf (vect_dump, "cost model: vector iteration cost = %d "
                 "is divisible by scalar iteration cost = %d by a factor "
                 "greater than or equal to the vectorization factor = %d .",
                 vec_inside_cost, scalar_single_iter_cost, vf);
      return -1;
    }

  if (vect_print_dump_info (REPORT_COST))
    {
      fprintf (vect_dump, "Cost model analysis: \n");
      fprintf (vect_dump, "  Vector inside of loop cost: %d\n",
               vec_inside_cost);
      fprintf (vect_dump, "  Vector outside of loop cost: %d\n",
               vec_outside_cost);
      fprintf (vect_dump, "  Scalar iteration cost: %d\n",
               scalar_single_iter_cost);
      fprintf (vect_dump, "  Scalar outside cost: %d\n", scalar_outside_cost);
      fprintf (vect_dump, "  prologue iterations: %d\n",
               peel_iters_prologue);
      fprintf (vect_dump, "  epilogue iterations: %d\n",
               peel_iters_epilogue);
      fprintf (vect_dump, "  Calculated minimum iters for profitability: %d\n",
               min_profitable_iters);
    }

  min_profitable_iters = 
        min_profitable_iters < vf ? vf : min_profitable_iters;

  /* Because the condition we create is:
     if (niters <= min_profitable_iters)
       then skip the vectorized loop.  */
  min_profitable_iters--;

  if (vect_print_dump_info (REPORT_COST))
    fprintf (vect_dump, "  Profitability threshold = %d\n",
             min_profitable_iters);
    
  return min_profitable_iters;
}


/* TODO: Close dependency between vect_model_*_cost and vectorizable_* 
   functions. Design better to avoid maintenance issues.  */
    
/* Function vect_model_reduction_cost.  

   Models cost for a reduction operation, including the vector ops 
   generated within the strip-mine loop, the initial definition before
   the loop, and the epilogue code that must be generated.  */

static bool 
vect_model_reduction_cost (stmt_vec_info stmt_info, enum tree_code reduc_code,
                           int ncopies)
{
  int outer_cost = 0;
  enum tree_code code;
  optab optab;
  tree vectype;
  gimple stmt, orig_stmt;
  tree reduction_op;
  enum machine_mode mode;
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);


  /* Cost of reduction op inside loop.  */
  STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info) += ncopies * TARG_VEC_STMT_COST;

  stmt = STMT_VINFO_STMT (stmt_info);

  switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt)))
    {
    case GIMPLE_SINGLE_RHS:
      gcc_assert (TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt)) == ternary_op);
      reduction_op = TREE_OPERAND (gimple_assign_rhs1 (stmt), 2);
      break;
    case GIMPLE_UNARY_RHS:
      reduction_op = gimple_assign_rhs1 (stmt);
      break;
    case GIMPLE_BINARY_RHS:
      reduction_op = gimple_assign_rhs2 (stmt);
      break;
    default:
      gcc_unreachable ();
    }

  vectype = get_vectype_for_scalar_type (TREE_TYPE (reduction_op));
  if (!vectype)
    {
      if (vect_print_dump_info (REPORT_COST))
        {
          fprintf (vect_dump, "unsupported data-type ");
          print_generic_expr (vect_dump, TREE_TYPE (reduction_op), TDF_SLIM);
        }
      return false;
   }
  
  mode = TYPE_MODE (vectype);
  orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);

  if (!orig_stmt) 
    orig_stmt = STMT_VINFO_STMT (stmt_info);

  code = gimple_assign_rhs_code (orig_stmt);

  /* Add in cost for initial definition.  */
  outer_cost += TARG_SCALAR_TO_VEC_COST;

  /* Determine cost of epilogue code.

     We have a reduction operator that will reduce the vector in one statement.
     Also requires scalar extract.  */

  if (!nested_in_vect_loop_p (loop, orig_stmt))
    {
      if (reduc_code < NUM_TREE_CODES) 
        outer_cost += TARG_VEC_STMT_COST + TARG_VEC_TO_SCALAR_COST;
      else 
        {
          int vec_size_in_bits = tree_low_cst (TYPE_SIZE (vectype), 1);
          tree bitsize =
            TYPE_SIZE (TREE_TYPE (gimple_assign_lhs (orig_stmt)));
          int element_bitsize = tree_low_cst (bitsize, 1);
          int nelements = vec_size_in_bits / element_bitsize;

          optab = optab_for_tree_code (code, vectype, optab_default);

          /* We have a whole vector shift available.  */
          if (VECTOR_MODE_P (mode)
              && optab_handler (optab, mode)->insn_code != CODE_FOR_nothing
              && optab_handler (vec_shr_optab, mode)->insn_code != CODE_FOR_nothing)
            /* Final reduction via vector shifts and the reduction operator. Also
               requires scalar extract.  */
            outer_cost += ((exact_log2(nelements) * 2) * TARG_VEC_STMT_COST
                                + TARG_VEC_TO_SCALAR_COST); 
          else
            /* Use extracts and reduction op for final reduction.  For N elements,
               we have N extracts and N-1 reduction ops.  */
            outer_cost += ((nelements + nelements - 1) * TARG_VEC_STMT_COST);
        }
    }

  STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info) = outer_cost;

  if (vect_print_dump_info (REPORT_COST))
    fprintf (vect_dump, "vect_model_reduction_cost: inside_cost = %d, "
             "outside_cost = %d .", STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info),
             STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info));

  return true;
}


/* Function vect_model_induction_cost.

   Models cost for induction operations.  */

static void
vect_model_induction_cost (stmt_vec_info stmt_info, int ncopies)
{
  /* loop cost for vec_loop.  */
  STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info) = ncopies * TARG_VEC_STMT_COST;
  /* prologue cost for vec_init and vec_step.  */
  STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info) = 2 * TARG_SCALAR_TO_VEC_COST;
  
  if (vect_print_dump_info (REPORT_COST))
    fprintf (vect_dump, "vect_model_induction_cost: inside_cost = %d, "
             "outside_cost = %d .", STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info),
             STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info));
}


/* Function vect_model_simple_cost.  

   Models cost for simple operations, i.e. those that only emit ncopies of a 
   single op.  Right now, this does not account for multiple insns that could
   be generated for the single vector op.  We will handle that shortly.  */

void
vect_model_simple_cost (stmt_vec_info stmt_info, int ncopies, 
                        enum vect_def_type *dt, slp_tree slp_node)
{
  int i;
  int inside_cost = 0, outside_cost = 0;

  /* The SLP costs were already calculated during SLP tree build.  */
  if (PURE_SLP_STMT (stmt_info))
    return;

  inside_cost = ncopies * TARG_VEC_STMT_COST;

  /* FORNOW: Assuming maximum 2 args per stmts.  */
  for (i = 0; i < 2; i++)
    {
      if (dt[i] == vect_constant_def || dt[i] == vect_invariant_def)
        outside_cost += TARG_SCALAR_TO_VEC_COST; 
    }
  
  if (vect_print_dump_info (REPORT_COST))
    fprintf (vect_dump, "vect_model_simple_cost: inside_cost = %d, "
             "outside_cost = %d .", inside_cost, outside_cost);

  /* Set the costs either in STMT_INFO or SLP_NODE (if exists).  */
  stmt_vinfo_set_inside_of_loop_cost (stmt_info, slp_node, inside_cost);
  stmt_vinfo_set_outside_of_loop_cost (stmt_info, slp_node, outside_cost);
}


/* Function vect_cost_strided_group_size 
 
   For strided load or store, return the group_size only if it is the first
   load or store of a group, else return 1.  This ensures that group size is
   only returned once per group.  */

static int
vect_cost_strided_group_size (stmt_vec_info stmt_info)
{
  gimple first_stmt = DR_GROUP_FIRST_DR (stmt_info);

  if (first_stmt == STMT_VINFO_STMT (stmt_info))
    return DR_GROUP_SIZE (stmt_info);

  return 1;
}


/* Function vect_model_store_cost

   Models cost for stores.  In the case of strided accesses, one access
   has the overhead of the strided access attributed to it.  */

void
vect_model_store_cost (stmt_vec_info stmt_info, int ncopies, 
                       enum vect_def_type dt, slp_tree slp_node)
{
  int group_size;
  int inside_cost = 0, outside_cost = 0;

  /* The SLP costs were already calculated during SLP tree build.  */
  if (PURE_SLP_STMT (stmt_info))
    return;

  if (dt == vect_constant_def || dt == vect_invariant_def)
    outside_cost = TARG_SCALAR_TO_VEC_COST;

  /* Strided access?  */
  if (DR_GROUP_FIRST_DR (stmt_info) && !slp_node) 
    group_size = vect_cost_strided_group_size (stmt_info);
  /* Not a strided access.  */
  else
    group_size = 1;

  /* Is this an access in a group of stores, which provide strided access?  
     If so, add in the cost of the permutes.  */
  if (group_size > 1) 
    {
      /* Uses a high and low interleave operation for each needed permute.  */
      inside_cost = ncopies * exact_log2(group_size) * group_size 
             * TARG_VEC_STMT_COST;

      if (vect_print_dump_info (REPORT_COST))
        fprintf (vect_dump, "vect_model_store_cost: strided group_size = %d .",
                 group_size);

    }

  /* Costs of the stores.  */
  inside_cost += ncopies * TARG_VEC_STORE_COST;

  if (vect_print_dump_info (REPORT_COST))
    fprintf (vect_dump, "vect_model_store_cost: inside_cost = %d, "
             "outside_cost = %d .", inside_cost, outside_cost);

  /* Set the costs either in STMT_INFO or SLP_NODE (if exists).  */
  stmt_vinfo_set_inside_of_loop_cost (stmt_info, slp_node, inside_cost);
  stmt_vinfo_set_outside_of_loop_cost (stmt_info, slp_node, outside_cost);
}


/* Function vect_model_load_cost

   Models cost for loads.  In the case of strided accesses, the last access
   has the overhead of the strided access attributed to it.  Since unaligned
   accesses are supported for loads, we also account for the costs of the 
   access scheme chosen.  */

void
vect_model_load_cost (stmt_vec_info stmt_info, int ncopies, slp_tree slp_node)
                 
{
  int group_size;
  int alignment_support_cheme;
  gimple first_stmt;
  struct data_reference *dr = STMT_VINFO_DATA_REF (stmt_info), *first_dr;
  int inside_cost = 0, outside_cost = 0;

  /* The SLP costs were already calculated during SLP tree build.  */
  if (PURE_SLP_STMT (stmt_info))
    return;

  /* Strided accesses?  */
  first_stmt = DR_GROUP_FIRST_DR (stmt_info);
  if (first_stmt && !slp_node)
    {
      group_size = vect_cost_strided_group_size (stmt_info);
      first_dr = STMT_VINFO_DATA_REF (vinfo_for_stmt (first_stmt));
    }
  /* Not a strided access.  */
  else
    {
      group_size = 1;
      first_dr = dr;
    }

  alignment_support_cheme = vect_supportable_dr_alignment (first_dr);

  /* Is this an access in a group of loads providing strided access?  
     If so, add in the cost of the permutes.  */
  if (group_size > 1) 
    {
      /* Uses an even and odd extract operations for each needed permute.  */
      inside_cost = ncopies * exact_log2(group_size) * group_size
        * TARG_VEC_STMT_COST;

      if (vect_print_dump_info (REPORT_COST))
        fprintf (vect_dump, "vect_model_load_cost: strided group_size = %d .",
                 group_size);

    }

  /* The loads themselves.  */
  switch (alignment_support_cheme)
    {
    case dr_aligned:
      {
        inside_cost += ncopies * TARG_VEC_LOAD_COST;

        if (vect_print_dump_info (REPORT_COST))
          fprintf (vect_dump, "vect_model_load_cost: aligned.");

        break;
      }
    case dr_unaligned_supported:
      {
        /* Here, we assign an additional cost for the unaligned load.  */
        inside_cost += ncopies * TARG_VEC_UNALIGNED_LOAD_COST;

        if (vect_print_dump_info (REPORT_COST))
          fprintf (vect_dump, "vect_model_load_cost: unaligned supported by "
                   "hardware.");

        break;
      }
    case dr_explicit_realign:
      {
        inside_cost += ncopies * (2*TARG_VEC_LOAD_COST + TARG_VEC_STMT_COST);

        /* FIXME: If the misalignment remains fixed across the iterations of
           the containing loop, the following cost should be added to the
           outside costs.  */
        if (targetm.vectorize.builtin_mask_for_load)
          inside_cost += TARG_VEC_STMT_COST;

        break;
      }
    case dr_explicit_realign_optimized:
      {
        if (vect_print_dump_info (REPORT_COST))
          fprintf (vect_dump, "vect_model_load_cost: unaligned software "
                   "pipelined.");

        /* Unaligned software pipeline has a load of an address, an initial
           load, and possibly a mask operation to "prime" the loop. However,
           if this is an access in a group of loads, which provide strided
           access, then the above cost should only be considered for one
           access in the group. Inside the loop, there is a load op
           and a realignment op.  */

        if ((!DR_GROUP_FIRST_DR (stmt_info)) || group_size > 1 || slp_node)
          {
            outside_cost = 2*TARG_VEC_STMT_COST;
            if (targetm.vectorize.builtin_mask_for_load)
              outside_cost += TARG_VEC_STMT_COST;
          }

        inside_cost += ncopies * (TARG_VEC_LOAD_COST + TARG_VEC_STMT_COST);

        break;
      }

    default:
      gcc_unreachable ();
    }
  
  if (vect_print_dump_info (REPORT_COST))
    fprintf (vect_dump, "vect_model_load_cost: inside_cost = %d, "
             "outside_cost = %d .", inside_cost, outside_cost);

  /* Set the costs either in STMT_INFO or SLP_NODE (if exists).  */
  stmt_vinfo_set_inside_of_loop_cost (stmt_info, slp_node, inside_cost);
  stmt_vinfo_set_outside_of_loop_cost (stmt_info, slp_node, outside_cost);
}


/* Function vect_get_new_vect_var.

   Returns a name for a new variable. The current naming scheme appends the 
   prefix "vect_" or "vect_p" (depending on the value of VAR_KIND) to 
   the name of vectorizer generated variables, and appends that to NAME if 
   provided.  */

static tree
vect_get_new_vect_var (tree type, enum vect_var_kind var_kind, const char *name)
{
  const char *prefix;
  tree new_vect_var;

  switch (var_kind)
  {
  case vect_simple_var:
    prefix = "vect_";
    break;
  case vect_scalar_var:
    prefix = "stmp_";
    break;
  case vect_pointer_var:
    prefix = "vect_p";
    break;
  default:
    gcc_unreachable ();
  }

  if (name)
    {
      char* tmp = concat (prefix, name, NULL);
      new_vect_var = create_tmp_var (type, tmp);
      free (tmp);
    }
  else
    new_vect_var = create_tmp_var (type, prefix);

  /* Mark vector typed variable as a gimple register variable.  */
  if (TREE_CODE (type) == VECTOR_TYPE)
    DECL_GIMPLE_REG_P (new_vect_var) = true;

  return new_vect_var;
}


/* Function vect_create_addr_base_for_vector_ref.

   Create an expression that computes the address of the first memory location
   that will be accessed for a data reference.

   Input:
   STMT: The statement containing the data reference.
   NEW_STMT_LIST: Must be initialized to NULL_TREE or a statement list.
   OFFSET: Optional. If supplied, it is be added to the initial address.
   LOOP:    Specify relative to which loop-nest should the address be computed.
            For example, when the dataref is in an inner-loop nested in an
            outer-loop that is now being vectorized, LOOP can be either the
            outer-loop, or the inner-loop. The first memory location accessed
            by the following dataref ('in' points to short):

                for (i=0; i<N; i++)
                   for (j=0; j<M; j++)
                     s += in[i+j]

            is as follows:
            if LOOP=i_loop:     &in             (relative to i_loop)
            if LOOP=j_loop:     &in+i*2B        (relative to j_loop)

   Output:
   1. Return an SSA_NAME whose value is the address of the memory location of 
      the first vector of the data reference.
   2. If new_stmt_list is not NULL_TREE after return then the caller must insert
      these statement(s) which define the returned SSA_NAME.

   FORNOW: We are only handling array accesses with step 1.  */

static tree
vect_create_addr_base_for_vector_ref (gimple stmt,
                                      gimple_seq *new_stmt_list,
                                      tree offset,
                                      struct loop *loop)
{
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  struct data_reference *dr = STMT_VINFO_DATA_REF (stmt_info);
  struct loop *containing_loop = (gimple_bb (stmt))->loop_father;
  tree data_ref_base = unshare_expr (DR_BASE_ADDRESS (dr));
  tree base_name;
  tree data_ref_base_var;
  tree vec_stmt;
  tree addr_base, addr_expr;
  tree dest;
  gimple_seq seq = NULL;
  tree base_offset = unshare_expr (DR_OFFSET (dr));
  tree init = unshare_expr (DR_INIT (dr));
  tree vect_ptr_type, addr_expr2;
  tree step = TYPE_SIZE_UNIT (TREE_TYPE (DR_REF (dr)));

  gcc_assert (loop);
  if (loop != containing_loop)
    {
      loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
      struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);

      gcc_assert (nested_in_vect_loop_p (loop, stmt));

      data_ref_base = unshare_expr (STMT_VINFO_DR_BASE_ADDRESS (stmt_info));
      base_offset = unshare_expr (STMT_VINFO_DR_OFFSET (stmt_info));
      init = unshare_expr (STMT_VINFO_DR_INIT (stmt_info));
    }

  /* Create data_ref_base */
  base_name = build_fold_indirect_ref (data_ref_base);
  data_ref_base_var = create_tmp_var (TREE_TYPE (data_ref_base), "batmp");
  add_referenced_var (data_ref_base_var);
  data_ref_base = force_gimple_operand (data_ref_base, &seq, true,
                                        data_ref_base_var);
  gimple_seq_add_seq (new_stmt_list, seq);

  /* Create base_offset */
  base_offset = size_binop (PLUS_EXPR,
                            fold_convert (sizetype, base_offset),
                            fold_convert (sizetype, init));
  dest = create_tmp_var (sizetype, "base_off");
  add_referenced_var (dest);
  base_offset = force_gimple_operand (base_offset, &seq, true, dest);
  gimple_seq_add_seq (new_stmt_list, seq);

  if (offset)
    {
      tree tmp = create_tmp_var (sizetype, "offset");

      add_referenced_var (tmp);
      offset = fold_build2 (MULT_EXPR, sizetype,
                            fold_convert (sizetype, offset), step);
      base_offset = fold_build2 (PLUS_EXPR, sizetype,
                                 base_offset, offset);
      base_offset = force_gimple_operand (base_offset, &seq, false, tmp);
      gimple_seq_add_seq (new_stmt_list, seq);
    }

  /* base + base_offset */
  addr_base = fold_build2 (POINTER_PLUS_EXPR, TREE_TYPE (data_ref_base), 
                           data_ref_base, base_offset);

  vect_ptr_type = build_pointer_type (STMT_VINFO_VECTYPE (stmt_info));

  /* addr_expr = addr_base */
  addr_expr = vect_get_new_vect_var (vect_ptr_type, vect_pointer_var,
                                     get_name (base_name));
  add_referenced_var (addr_expr);
  vec_stmt = fold_convert (vect_ptr_type, addr_base);
  addr_expr2 = vect_get_new_vect_var (vect_ptr_type, vect_pointer_var,
                                     get_name (base_name));
  add_referenced_var (addr_expr2);
  vec_stmt = force_gimple_operand (vec_stmt, &seq, false, addr_expr2);
  gimple_seq_add_seq (new_stmt_list, seq);

  if (vect_print_dump_info (REPORT_DETAILS))
    {
      fprintf (vect_dump, "created ");
      print_generic_expr (vect_dump, vec_stmt, TDF_SLIM);
    }
  return vec_stmt;
}


/* Function vect_create_data_ref_ptr.

   Create a new pointer to vector type (vp), that points to the first location
   accessed in the loop by STMT, along with the def-use update chain to 
   appropriately advance the pointer through the loop iterations. Also set
   aliasing information for the pointer.  This vector pointer is used by the
   callers to this function to create a memory reference expression for vector
   load/store access.

   Input:
   1. STMT: a stmt that references memory. Expected to be of the form
         GIMPLE_ASSIGN <name, data-ref> or
         GIMPLE_ASSIGN <data-ref, name>.
   2. AT_LOOP: the loop where the vector memref is to be created.
   3. OFFSET (optional): an offset to be added to the initial address accessed
        by the data-ref in STMT.
   4. ONLY_INIT: indicate if vp is to be updated in the loop, or remain
        pointing to the initial address.
   5. TYPE: if not NULL indicates the required type of the data-ref.

   Output:
   1. Declare a new ptr to vector_type, and have it point to the base of the
      data reference (initial addressed accessed by the data reference).
      For example, for vector of type V8HI, the following code is generated:

      v8hi *vp;
      vp = (v8hi *)initial_address;

      if OFFSET is not supplied:
         initial_address = &a[init];
      if OFFSET is supplied:
         initial_address = &a[init + OFFSET];

      Return the initial_address in INITIAL_ADDRESS.

   2. If ONLY_INIT is true, just return the initial pointer.  Otherwise, also
      update the pointer in each iteration of the loop.  

      Return the increment stmt that updates the pointer in PTR_INCR.

   3. Set INV_P to true if the access pattern of the data reference in the 
      vectorized loop is invariant. Set it to false otherwise.

   4. Return the pointer.  */

static tree
vect_create_data_ref_ptr (gimple stmt, struct loop *at_loop,
                          tree offset, tree *initial_address, gimple *ptr_incr,
                          bool only_init, bool *inv_p, tree type)
{
  tree base_name;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  bool nested_in_vect_loop = nested_in_vect_loop_p (loop, stmt);
  struct loop *containing_loop = (gimple_bb (stmt))->loop_father;
  tree vectype = STMT_VINFO_VECTYPE (stmt_info);
  tree vect_ptr_type;
  tree vect_ptr;
  tree tag;
  tree new_temp;
  gimple vec_stmt;
  gimple_seq new_stmt_list = NULL;
  edge pe;
  basic_block new_bb;
  tree vect_ptr_init;
  struct data_reference *dr = STMT_VINFO_DATA_REF (stmt_info);
  tree vptr;
  gimple_stmt_iterator incr_gsi;
  bool insert_after;
  tree indx_before_incr, indx_after_incr;
  gimple incr;
  tree step;

  /* Check the step (evolution) of the load in LOOP, and record
     whether it's invariant.  */
  if (nested_in_vect_loop)
    step = STMT_VINFO_DR_STEP (stmt_info);
  else
    step = DR_STEP (STMT_VINFO_DATA_REF (stmt_info));
    
  if (tree_int_cst_compare (step, size_zero_node) == 0)
    *inv_p = true;
  else
    *inv_p = false;

  /* Create an expression for the first address accessed by this load
     in LOOP.  */ 
  base_name = build_fold_indirect_ref (unshare_expr (DR_BASE_ADDRESS (dr)));

  if (vect_print_dump_info (REPORT_DETAILS))
    {
      tree data_ref_base = base_name;
      fprintf (vect_dump, "create vector-pointer variable to type: ");
      print_generic_expr (vect_dump, vectype, TDF_SLIM);
      if (TREE_CODE (data_ref_base) == VAR_DECL)
        fprintf (vect_dump, "  vectorizing a one dimensional array ref: ");
      else if (TREE_CODE (data_ref_base) == ARRAY_REF)
        fprintf (vect_dump, "  vectorizing a multidimensional array ref: ");
      else if (TREE_CODE (data_ref_base) == COMPONENT_REF)
        fprintf (vect_dump, "  vectorizing a record based array ref: ");
      else if (TREE_CODE (data_ref_base) == SSA_NAME)
        fprintf (vect_dump, "  vectorizing a pointer ref: ");
      print_generic_expr (vect_dump, base_name, TDF_SLIM);
    }

  /** (1) Create the new vector-pointer variable:  **/
  if (type)
    vect_ptr_type = build_pointer_type (type);
  else
    vect_ptr_type = build_pointer_type (vectype);

  if (TREE_CODE (DR_BASE_ADDRESS (dr)) == SSA_NAME
      && TYPE_RESTRICT (TREE_TYPE (DR_BASE_ADDRESS (dr))))
    vect_ptr_type = build_qualified_type (vect_ptr_type, TYPE_QUAL_RESTRICT);
  vect_ptr = vect_get_new_vect_var (vect_ptr_type, vect_pointer_var,
                                    get_name (base_name));
  if (TREE_CODE (DR_BASE_ADDRESS (dr)) == SSA_NAME
      && TYPE_RESTRICT (TREE_TYPE (DR_BASE_ADDRESS (dr))))
    {
      get_alias_set (base_name);
      DECL_POINTER_ALIAS_SET (vect_ptr)
        = DECL_POINTER_ALIAS_SET (SSA_NAME_VAR (DR_BASE_ADDRESS (dr)));
    }

  add_referenced_var (vect_ptr);

  /** (2) Add aliasing information to the new vector-pointer:
          (The points-to info (DR_PTR_INFO) may be defined later.)  **/
  
  tag = DR_SYMBOL_TAG (dr);
  gcc_assert (tag);

  /* If tag is a variable (and NOT_A_TAG) than a new symbol memory
     tag must be created with tag added to its may alias list.  */
  if (!MTAG_P (tag))
    new_type_alias (vect_ptr, tag, DR_REF (dr));
  else
    set_symbol_mem_tag (vect_ptr, tag);

  /** Note: If the dataref is in an inner-loop nested in LOOP, and we are
      vectorizing LOOP (i.e. outer-loop vectorization), we need to create two
      def-use update cycles for the pointer: One relative to the outer-loop
      (LOOP), which is what steps (3) and (4) below do. The other is relative
      to the inner-loop (which is the inner-most loop containing the dataref),
      and this is done be step (5) below. 

      When vectorizing inner-most loops, the vectorized loop (LOOP) is also the
      inner-most loop, and so steps (3),(4) work the same, and step (5) is
      redundant.  Steps (3),(4) create the following:

        vp0 = &base_addr;
        LOOP:   vp1 = phi(vp0,vp2)
                ...  
                ...
                vp2 = vp1 + step
                goto LOOP
                        
      If there is an inner-loop nested in loop, then step (5) will also be
      applied, and an additional update in the inner-loop will be created:

        vp0 = &base_addr;
        LOOP:   vp1 = phi(vp0,vp2)
                ...
        inner:     vp3 = phi(vp1,vp4)
                   vp4 = vp3 + inner_step
                   if () goto inner
                ...
                vp2 = vp1 + step
                if () goto LOOP   */

  /** (3) Calculate the initial address the vector-pointer, and set
          the vector-pointer to point to it before the loop:  **/

  /* Create: (&(base[init_val+offset]) in the loop preheader.  */

  new_temp = vect_create_addr_base_for_vector_ref (stmt, &new_stmt_list,
                                                   offset, loop);
  pe = loop_preheader_edge (loop);
  if (new_stmt_list)
    {
      new_bb = gsi_insert_seq_on_edge_immediate (pe, new_stmt_list);
      gcc_assert (!new_bb);
    }

  *initial_address = new_temp;

  /* Create: p = (vectype *) initial_base  */
  vec_stmt = gimple_build_assign (vect_ptr,
                                  fold_convert (vect_ptr_type, new_temp));
  vect_ptr_init = make_ssa_name (vect_ptr, vec_stmt);
  gimple_assign_set_lhs (vec_stmt, vect_ptr_init);
  new_bb = gsi_insert_on_edge_immediate (pe, vec_stmt);
  gcc_assert (!new_bb);


  /** (4) Handle the updating of the vector-pointer inside the loop.
          This is needed when ONLY_INIT is false, and also when AT_LOOP
          is the inner-loop nested in LOOP (during outer-loop vectorization).
   **/

  if (only_init && at_loop == loop) /* No update in loop is required.  */
    {
      /* Copy the points-to information if it exists. */
      if (DR_PTR_INFO (dr))
        duplicate_ssa_name_ptr_info (vect_ptr_init, DR_PTR_INFO (dr));
      vptr = vect_ptr_init;
    }
  else
    {
      /* The step of the vector pointer is the Vector Size.  */
      tree step = TYPE_SIZE_UNIT (vectype);
      /* One exception to the above is when the scalar step of the load in 
         LOOP is zero. In this case the step here is also zero.  */
      if (*inv_p)
        step = size_zero_node;

      standard_iv_increment_position (loop, &incr_gsi, &insert_after);

      create_iv (vect_ptr_init,
                 fold_convert (vect_ptr_type, step),
                 vect_ptr, loop, &incr_gsi, insert_after,
                 &indx_before_incr, &indx_after_incr);
      incr = gsi_stmt (incr_gsi);
      set_vinfo_for_stmt (incr, new_stmt_vec_info (incr, loop_vinfo));

      /* Copy the points-to information if it exists. */
      if (DR_PTR_INFO (dr))
        {
          duplicate_ssa_name_ptr_info (indx_before_incr, DR_PTR_INFO (dr));
          duplicate_ssa_name_ptr_info (indx_after_incr, DR_PTR_INFO (dr));
        }
      merge_alias_info (vect_ptr_init, indx_before_incr);
      merge_alias_info (vect_ptr_init, indx_after_incr);
      if (ptr_incr)
        *ptr_incr = incr;

      vptr = indx_before_incr;
    }

  if (!nested_in_vect_loop || only_init)
    return vptr;


  /** (5) Handle the updating of the vector-pointer inside the inner-loop
          nested in LOOP, if exists: **/

  gcc_assert (nested_in_vect_loop);
  if (!only_init)
    {
      standard_iv_increment_position (containing_loop, &incr_gsi,
                                      &insert_after);
      create_iv (vptr, fold_convert (vect_ptr_type, DR_STEP (dr)), vect_ptr, 
                 containing_loop, &incr_gsi, insert_after, &indx_before_incr,
                 &indx_after_incr);
      incr = gsi_stmt (incr_gsi);
      set_vinfo_for_stmt (incr, new_stmt_vec_info (incr, loop_vinfo));

      /* Copy the points-to information if it exists. */
      if (DR_PTR_INFO (dr))
        {
          duplicate_ssa_name_ptr_info (indx_before_incr, DR_PTR_INFO (dr));
          duplicate_ssa_name_ptr_info (indx_after_incr, DR_PTR_INFO (dr));
        }
      merge_alias_info (vect_ptr_init, indx_before_incr);
      merge_alias_info (vect_ptr_init, indx_after_incr);
      if (ptr_incr)
        *ptr_incr = incr;

      return indx_before_incr; 
    }
  else
    gcc_unreachable ();
}


/* Function bump_vector_ptr

   Increment a pointer (to a vector type) by vector-size. If requested,
   i.e. if PTR-INCR is given, then also connect the new increment stmt 
   to the existing def-use update-chain of the pointer, by modifying
   the PTR_INCR as illustrated below:

   The pointer def-use update-chain before this function:
                        DATAREF_PTR = phi (p_0, p_2)
                        ....
        PTR_INCR:       p_2 = DATAREF_PTR + step 

   The pointer def-use update-chain after this function:
                        DATAREF_PTR = phi (p_0, p_2)
                        ....
                        NEW_DATAREF_PTR = DATAREF_PTR + BUMP
                        ....
        PTR_INCR:       p_2 = NEW_DATAREF_PTR + step

   Input:
   DATAREF_PTR - ssa_name of a pointer (to vector type) that is being updated 
                 in the loop.
   PTR_INCR - optional. The stmt that updates the pointer in each iteration of 
              the loop.  The increment amount across iterations is expected
              to be vector_size.      
   BSI - location where the new update stmt is to be placed.
   STMT - the original scalar memory-access stmt that is being vectorized.
   BUMP - optional. The offset by which to bump the pointer. If not given,
          the offset is assumed to be vector_size.

   Output: Return NEW_DATAREF_PTR as illustrated above.
   
*/

static tree
bump_vector_ptr (tree dataref_ptr, gimple ptr_incr, gimple_stmt_iterator *gsi,
                 gimple stmt, tree bump)
{
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  struct data_reference *dr = STMT_VINFO_DATA_REF (stmt_info);
  tree vectype = STMT_VINFO_VECTYPE (stmt_info);
  tree ptr_var = SSA_NAME_VAR (dataref_ptr);
  tree update = TYPE_SIZE_UNIT (vectype);
  gimple incr_stmt;
  ssa_op_iter iter;
  use_operand_p use_p;
  tree new_dataref_ptr;

  if (bump)
    update = bump;
    
  incr_stmt = gimple_build_assign_with_ops (POINTER_PLUS_EXPR, ptr_var,
                                            dataref_ptr, update);
  new_dataref_ptr = make_ssa_name (ptr_var, incr_stmt);
  gimple_assign_set_lhs (incr_stmt, new_dataref_ptr);
  vect_finish_stmt_generation (stmt, incr_stmt, gsi);

  /* Copy the points-to information if it exists. */
  if (DR_PTR_INFO (dr))
    duplicate_ssa_name_ptr_info (new_dataref_ptr, DR_PTR_INFO (dr));
  merge_alias_info (new_dataref_ptr, dataref_ptr);

  if (!ptr_incr)
    return new_dataref_ptr;

  /* Update the vector-pointer's cross-iteration increment.  */
  FOR_EACH_SSA_USE_OPERAND (use_p, ptr_incr, iter, SSA_OP_USE)
    {
      tree use = USE_FROM_PTR (use_p);

      if (use == dataref_ptr)
        SET_USE (use_p, new_dataref_ptr);
      else
        gcc_assert (tree_int_cst_compare (use, update) == 0);
    }

  return new_dataref_ptr;
}


/* Function vect_create_destination_var.

   Create a new temporary of type VECTYPE.  */

static tree
vect_create_destination_var (tree scalar_dest, tree vectype)
{
  tree vec_dest;
  const char *new_name;
  tree type;
  enum vect_var_kind kind;

  kind = vectype ? vect_simple_var : vect_scalar_var;
  type = vectype ? vectype : TREE_TYPE (scalar_dest);

  gcc_assert (TREE_CODE (scalar_dest) == SSA_NAME);

  new_name = get_name (scalar_dest);
  if (!new_name)
    new_name = "var_";
  vec_dest = vect_get_new_vect_var (type, kind, new_name);
  add_referenced_var (vec_dest);

  return vec_dest;
}


/* Function vect_init_vector.

   Insert a new stmt (INIT_STMT) that initializes a new vector variable with
   the vector elements of VECTOR_VAR. Place the initialization at BSI if it
   is not NULL. Otherwise, place the initialization at the loop preheader.
   Return the DEF of INIT_STMT. 
   It will be used in the vectorization of STMT.  */

static tree
vect_init_vector (gimple stmt, tree vector_var, tree vector_type,
                  gimple_stmt_iterator *gsi)
{
  stmt_vec_info stmt_vinfo = vinfo_for_stmt (stmt);
  tree new_var;
  gimple init_stmt;
  tree vec_oprnd;
  edge pe;
  tree new_temp;
  basic_block new_bb;
 
  new_var = vect_get_new_vect_var (vector_type, vect_simple_var, "cst_");
  add_referenced_var (new_var); 
  init_stmt = gimple_build_assign  (new_var, vector_var);
  new_temp = make_ssa_name (new_var, init_stmt);
  gimple_assign_set_lhs (init_stmt, new_temp);

  if (gsi)
    vect_finish_stmt_generation (stmt, init_stmt, gsi);
  else
    {
      loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo);
      struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);

      if (nested_in_vect_loop_p (loop, stmt))
        loop = loop->inner;
      pe = loop_preheader_edge (loop);
      new_bb = gsi_insert_on_edge_immediate (pe, init_stmt);
      gcc_assert (!new_bb);
    }

  if (vect_print_dump_info (REPORT_DETAILS))
    {
      fprintf (vect_dump, "created new init_stmt: ");
      print_gimple_stmt (vect_dump, init_stmt, 0, TDF_SLIM);
    }

  vec_oprnd = gimple_assign_lhs (init_stmt);
  return vec_oprnd;
}


/* For constant and loop invariant defs of SLP_NODE this function returns 
   (vector) defs (VEC_OPRNDS) that will be used in the vectorized stmts.  
   OP_NUM determines if we gather defs for operand 0 or operand 1 of the scalar
   stmts. NUMBER_OF_VECTORS is the number of vector defs to create.  */

static void
vect_get_constant_vectors (slp_tree slp_node, VEC(tree,heap) **vec_oprnds,
                           unsigned int op_num, unsigned int number_of_vectors)
{
  VEC (gimple, heap) *stmts = SLP_TREE_SCALAR_STMTS (slp_node);
  gimple stmt = VEC_index (gimple, stmts, 0);
  stmt_vec_info stmt_vinfo = vinfo_for_stmt (stmt);
  tree vectype = STMT_VINFO_VECTYPE (stmt_vinfo);
  int nunits;
  tree vec_cst;
  tree t = NULL_TREE;
  int j, number_of_places_left_in_vector;
  tree vector_type;
  tree op, vop;
  int group_size = VEC_length (gimple, stmts);
  unsigned int vec_num, i;
  int number_of_copies = 1;
  VEC (tree, heap) *voprnds = VEC_alloc (tree, heap, number_of_vectors);
  bool constant_p, is_store;

  if (STMT_VINFO_DATA_REF (stmt_vinfo))
    {
      is_store = true;
      op = gimple_assign_rhs1 (stmt);
    }
  else
    {
      is_store = false;
      op = gimple_op (stmt, op_num + 1);
    }

  if (CONSTANT_CLASS_P (op))
    {
      vector_type = vectype;
      constant_p = true;
    }
  else
    {
      vector_type = get_vectype_for_scalar_type (TREE_TYPE (op)); 
      gcc_assert (vector_type);
      constant_p = false;
    }

  nunits = TYPE_VECTOR_SUBPARTS (vector_type);

  /* NUMBER_OF_COPIES is the number of times we need to use the same values in
     created vectors. It is greater than 1 if unrolling is performed. 

     For example, we have two scalar operands, s1 and s2 (e.g., group of
     strided accesses of size two), while NUNITS is four (i.e., four scalars
     of this type can be packed in a vector). The output vector will contain
     two copies of each scalar operand: {s1, s2, s1, s2}. (NUMBER_OF_COPIES
     will be 2).

     If GROUP_SIZE > NUNITS, the scalars will be split into several vectors 
     containing the operands.

     For example, NUNITS is four as before, and the group size is 8
     (s1, s2, ..., s8). We will create two vectors {s1, s2, s3, s4} and
     {s5, s6, s7, s8}.  */
    
  number_of_copies = least_common_multiple (nunits, group_size) / group_size;

  number_of_places_left_in_vector = nunits;
  for (j = 0; j < number_of_copies; j++)
    {
      for (i = group_size - 1; VEC_iterate (gimple, stmts, i, stmt); i--)
        {
          if (is_store)
            op = gimple_assign_rhs1 (stmt);
          else
            op = gimple_op (stmt, op_num + 1);
    
          /* Create 'vect_ = {op0,op1,...,opn}'.  */
          t = tree_cons (NULL_TREE, op, t);

          number_of_places_left_in_vector--;

          if (number_of_places_left_in_vector == 0)
            {
              number_of_places_left_in_vector = nunits;

              if (constant_p)
                vec_cst = build_vector (vector_type, t);
              else
                vec_cst = build_constructor_from_list (vector_type, t);
              VEC_quick_push (tree, voprnds,
                              vect_init_vector (stmt, vec_cst, vector_type, NULL));
              t = NULL_TREE;
            }
        }
    }

  /* Since the vectors are created in the reverse order, we should invert 
     them.  */
  vec_num = VEC_length (tree, voprnds);
  for (j = vec_num - 1; j >= 0; j--)
    {
      vop = VEC_index (tree, voprnds, j);
      VEC_quick_push (tree, *vec_oprnds, vop);
    }

  VEC_free (tree, heap, voprnds);

  /* In case that VF is greater than the unrolling factor needed for the SLP
     group of stmts, NUMBER_OF_VECTORS to be created is greater than 
     NUMBER_OF_SCALARS/NUNITS or NUNITS/NUMBER_OF_SCALARS, and hence we have 
     to replicate the vectors.  */
  while (number_of_vectors > VEC_length (tree, *vec_oprnds))
    {
      for (i = 0; VEC_iterate (tree, *vec_oprnds, i, vop) && i < vec_num; i++)
        VEC_quick_push (tree, *vec_oprnds, vop);
    }
}


/* Get vectorized definitions from SLP_NODE that contains corresponding
   vectorized def-stmts.  */

static void
vect_get_slp_vect_defs (slp_tree slp_node, VEC (tree,heap) **vec_oprnds)
{
  tree vec_oprnd;
  gimple vec_def_stmt;
  unsigned int i;

  gcc_assert (SLP_TREE_VEC_STMTS (slp_node));

  for (i = 0;
       VEC_iterate (gimple, SLP_TREE_VEC_STMTS (slp_node), i, vec_def_stmt);
       i++)
    {
      gcc_assert (vec_def_stmt);
      vec_oprnd = gimple_get_lhs (vec_def_stmt);
      VEC_quick_push (tree, *vec_oprnds, vec_oprnd);
    }
}


/* Get vectorized definitions for SLP_NODE. 
   If the scalar definitions are loop invariants or constants, collect them and 
   call vect_get_constant_vectors() to create vector stmts.
   Otherwise, the def-stmts must be already vectorized and the vectorized stmts
   must be stored in the LEFT/RIGHT node of SLP_NODE, and we call
   vect_get_slp_vect_defs() to retrieve them.  
   If VEC_OPRNDS1 is NULL, don't get vector defs for the second operand (from
   the right node. This is used when the second operand must remain scalar.  */ 
 
static void
vect_get_slp_defs (slp_tree slp_node, VEC (tree,heap) **vec_oprnds0,
                   VEC (tree,heap) **vec_oprnds1)
{
  gimple first_stmt;
  enum tree_code code;
  int number_of_vects;
  HOST_WIDE_INT lhs_size_unit, rhs_size_unit; 

  first_stmt = VEC_index (gimple, SLP_TREE_SCALAR_STMTS (slp_node), 0);
  /* The number of vector defs is determined by the number of vector statements
     in the node from which we get those statements.  */
  if (SLP_TREE_LEFT (slp_node)) 
    number_of_vects = SLP_TREE_NUMBER_OF_VEC_STMTS (SLP_TREE_LEFT (slp_node));
  else
    {
      number_of_vects = SLP_TREE_NUMBER_OF_VEC_STMTS (slp_node);
      /* Number of vector stmts was calculated according to LHS in
         vect_schedule_slp_instance(), fix it by replacing LHS with RHS, if
         necessary. See vect_get_smallest_scalar_type() for details.  */
      vect_get_smallest_scalar_type (first_stmt, &lhs_size_unit,
                                     &rhs_size_unit);
      if (rhs_size_unit != lhs_size_unit)
        {
          number_of_vects *= rhs_size_unit;
          number_of_vects /= lhs_size_unit;
        }
    }

  /* Allocate memory for vectorized defs.  */
  *vec_oprnds0 = VEC_alloc (tree, heap, number_of_vects);

  /* SLP_NODE corresponds either to a group of stores or to a group of
     unary/binary operations. We don't call this function for loads.  */
  if (SLP_TREE_LEFT (slp_node))
    /* The defs are already vectorized.  */
    vect_get_slp_vect_defs (SLP_TREE_LEFT (slp_node), vec_oprnds0);
  else
    /* Build vectors from scalar defs.  */
    vect_get_constant_vectors (slp_node, vec_oprnds0, 0, number_of_vects);

  if (STMT_VINFO_DATA_REF (vinfo_for_stmt (first_stmt)))
    /* Since we don't call this function with loads, this is a group of
       stores.  */
    return;

  code = gimple_assign_rhs_code (first_stmt);
  if (get_gimple_rhs_class (code) != GIMPLE_BINARY_RHS || !vec_oprnds1)
    return;

  /* The number of vector defs is determined by the number of vector statements
     in the node from which we get those statements.  */
  if (SLP_TREE_RIGHT (slp_node))
    number_of_vects = SLP_TREE_NUMBER_OF_VEC_STMTS (SLP_TREE_RIGHT (slp_node));
  else
    number_of_vects = SLP_TREE_NUMBER_OF_VEC_STMTS (slp_node);

  *vec_oprnds1 = VEC_alloc (tree, heap, number_of_vects);

  if (SLP_TREE_RIGHT (slp_node))
    /* The defs are already vectorized.  */
    vect_get_slp_vect_defs (SLP_TREE_RIGHT (slp_node), vec_oprnds1);
  else
    /* Build vectors from scalar defs.  */
    vect_get_constant_vectors (slp_node, vec_oprnds1, 1, number_of_vects);
}


/* Function get_initial_def_for_induction

   Input:
   STMT - a stmt that performs an induction operation in the loop.
   IV_PHI - the initial value of the induction variable

   Output:
   Return a vector variable, initialized with the first VF values of
   the induction variable. E.g., for an iv with IV_PHI='X' and
   evolution S, for a vector of 4 units, we want to return: 
   [X, X + S, X + 2*S, X + 3*S].  */

static tree
get_initial_def_for_induction (gimple iv_phi)
{
  stmt_vec_info stmt_vinfo = vinfo_for_stmt (iv_phi);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  tree scalar_type = TREE_TYPE (gimple_phi_result (iv_phi));
  tree vectype; 
  int nunits;
  edge pe = loop_preheader_edge (loop);
  struct loop *iv_loop;
  basic_block new_bb;
  tree vec, vec_init, vec_step, t;
  tree access_fn;
  tree new_var;
  tree new_name;
  gimple init_stmt, induction_phi, new_stmt;
  tree induc_def, vec_def, vec_dest;
  tree init_expr, step_expr;
  int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
  int i;
  bool ok;
  int ncopies;
  tree expr;
  stmt_vec_info phi_info = vinfo_for_stmt (iv_phi);
  bool nested_in_vect_loop = false;
  gimple_seq stmts = NULL;
  imm_use_iterator imm_iter;
  use_operand_p use_p;
  gimple exit_phi;
  edge latch_e;
  tree loop_arg;
  gimple_stmt_iterator si;
  basic_block bb = gimple_bb (iv_phi);

  vectype = get_vectype_for_scalar_type (scalar_type);
  gcc_assert (vectype);
  nunits = TYPE_VECTOR_SUBPARTS (vectype);
  ncopies = vf / nunits;

  gcc_assert (phi_info);
  gcc_assert (ncopies >= 1);

  /* Find the first insertion point in the BB.  */
  si = gsi_after_labels (bb);

  if (INTEGRAL_TYPE_P (scalar_type) || POINTER_TYPE_P (scalar_type))
    step_expr = build_int_cst (scalar_type, 0);
  else
    step_expr = build_real (scalar_type, dconst0);

  /* Is phi in an inner-loop, while vectorizing an enclosing outer-loop?  */
  if (nested_in_vect_loop_p (loop, iv_phi))
    {
      nested_in_vect_loop = true;
      iv_loop = loop->inner;
    }
  else
    iv_loop = loop;
  gcc_assert (iv_loop == (gimple_bb (iv_phi))->loop_father);

  latch_e = loop_latch_edge (iv_loop);
  loop_arg = PHI_ARG_DEF_FROM_EDGE (iv_phi, latch_e);

  access_fn = analyze_scalar_evolution (iv_loop, PHI_RESULT (iv_phi));
  gcc_assert (access_fn);
  ok = vect_is_simple_iv_evolution (iv_loop->num, access_fn,
                                  &init_expr, &step_expr);
  gcc_assert (ok);
  pe = loop_preheader_edge (iv_loop);

  /* Create the vector that holds the initial_value of the induction.  */
  if (nested_in_vect_loop)
    {
      /* iv_loop is nested in the loop to be vectorized.  init_expr had already
         been created during vectorization of previous stmts; We obtain it from
         the STMT_VINFO_VEC_STMT of the defining stmt. */
      tree iv_def = PHI_ARG_DEF_FROM_EDGE (iv_phi, loop_preheader_edge (iv_loop));
      vec_init = vect_get_vec_def_for_operand (iv_def, iv_phi, NULL);
    }
  else
    {
      /* iv_loop is the loop to be vectorized. Create:
         vec_init = [X, X+S, X+2*S, X+3*S] (S = step_expr, X = init_expr)  */
      new_var = vect_get_new_vect_var (scalar_type, vect_scalar_var, "var_");
      add_referenced_var (new_var);

      new_name = force_gimple_operand (init_expr, &stmts, false, new_var);
      if (stmts)
        {
          new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts);
          gcc_assert (!new_bb);
        }

      t = NULL_TREE;
      t = tree_cons (NULL_TREE, init_expr, t);
      for (i = 1; i < nunits; i++)
        {
          /* Create: new_name_i = new_name + step_expr  */
          enum tree_code code = POINTER_TYPE_P (scalar_type)
                                ? POINTER_PLUS_EXPR : PLUS_EXPR;
          init_stmt = gimple_build_assign_with_ops (code, new_var,
                                                    new_name, step_expr);
          new_name = make_ssa_name (new_var, init_stmt);
          gimple_assign_set_lhs (init_stmt, new_name);

          new_bb = gsi_insert_on_edge_immediate (pe, init_stmt);
          gcc_assert (!new_bb);

          if (vect_print_dump_info (REPORT_DETAILS))
            {
              fprintf (vect_dump, "created new init_stmt: ");
              print_gimple_stmt (vect_dump, init_stmt, 0, TDF_SLIM);
            }
          t = tree_cons (NULL_TREE, new_name, t);
        }
      /* Create a vector from [new_name_0, new_name_1, ..., new_name_nunits-1]  */
      vec = build_constructor_from_list (vectype, nreverse (t));
      vec_init = vect_init_vector (iv_phi, vec, vectype, NULL);
    }


  /* Create the vector that holds the step of the induction.  */
  if (nested_in_vect_loop)
    /* iv_loop is nested in the loop to be vectorized. Generate:
       vec_step = [S, S, S, S]  */
    new_name = step_expr;
  else
    {
      /* iv_loop is the loop to be vectorized. Generate:
          vec_step = [VF*S, VF*S, VF*S, VF*S]  */
      expr = build_int_cst (scalar_type, vf);
      new_name = fold_build2 (MULT_EXPR, scalar_type, expr, step_expr);
    }

  t = NULL_TREE;
  for (i = 0; i < nunits; i++)
    t = tree_cons (NULL_TREE, unshare_expr (new_name), t);
  gcc_assert (CONSTANT_CLASS_P (new_name));
  vec = build_vector (vectype, t);
  vec_step = vect_init_vector (iv_phi, vec, vectype, NULL);


  /* Create the following def-use cycle:
     loop prolog:
         vec_init = ...
         vec_step = ...
     loop:
         vec_iv = PHI <vec_init, vec_loop>
         ...
         STMT
         ...
         vec_loop = vec_iv + vec_step;  */

  /* Create the induction-phi that defines the induction-operand.  */
  vec_dest = vect_get_new_vect_var (vectype, vect_simple_var, "vec_iv_");
  add_referenced_var (vec_dest);
  induction_phi = create_phi_node (vec_dest, iv_loop->header);
  set_vinfo_for_stmt (induction_phi,
                      new_stmt_vec_info (induction_phi, loop_vinfo));
  induc_def = PHI_RESULT (induction_phi);

  /* Create the iv update inside the loop  */
  new_stmt = gimple_build_assign_with_ops (PLUS_EXPR, vec_dest,
                                           induc_def, vec_step);
  vec_def = make_ssa_name (vec_dest, new_stmt);
  gimple_assign_set_lhs (new_stmt, vec_def);
  gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
  set_vinfo_for_stmt (new_stmt, new_stmt_vec_info (new_stmt, loop_vinfo));

  /* Set the arguments of the phi node:  */
  add_phi_arg (induction_phi, vec_init, pe);
  add_phi_arg (induction_phi, vec_def, loop_latch_edge (iv_loop));


  /* In case that vectorization factor (VF) is bigger than the number
     of elements that we can fit in a vectype (nunits), we have to generate
     more than one vector stmt - i.e - we need to "unroll" the
     vector stmt by a factor VF/nunits.  For more details see documentation
     in vectorizable_operation.  */
  
  if (ncopies > 1)
    {
      stmt_vec_info prev_stmt_vinfo;
      /* FORNOW. This restriction should be relaxed.  */
      gcc_assert (!nested_in_vect_loop);

      /* Create the vector that holds the step of the induction.  */
      expr = build_int_cst (scalar_type, nunits);
      new_name = fold_build2 (MULT_EXPR, scalar_type, expr, step_expr);
      t = NULL_TREE;
      for (i = 0; i < nunits; i++)
        t = tree_cons (NULL_TREE, unshare_expr (new_name), t);
      gcc_assert (CONSTANT_CLASS_P (new_name));
      vec = build_vector (vectype, t);
      vec_step = vect_init_vector (iv_phi, vec, vectype, NULL);

      vec_def = induc_def;
      prev_stmt_vinfo = vinfo_for_stmt (induction_phi);
      for (i = 1; i < ncopies; i++)
        {
          /* vec_i = vec_prev + vec_step  */
          new_stmt = gimple_build_assign_with_ops (PLUS_EXPR, vec_dest,
                                                   vec_def, vec_step);
          vec_def = make_ssa_name (vec_dest, new_stmt);
          gimple_assign_set_lhs (new_stmt, vec_def);

          gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
          set_vinfo_for_stmt (new_stmt,
                              new_stmt_vec_info (new_stmt, loop_vinfo));
          STMT_VINFO_RELATED_STMT (prev_stmt_vinfo) = new_stmt;
          prev_stmt_vinfo = vinfo_for_stmt (new_stmt); 
        }
    }

  if (nested_in_vect_loop)
    {
      /* Find the loop-closed exit-phi of the induction, and record
         the final vector of induction results:  */
      exit_phi = NULL;
      FOR_EACH_IMM_USE_FAST (use_p, imm_iter, loop_arg)
        {
          if (!flow_bb_inside_loop_p (iv_loop, gimple_bb (USE_STMT (use_p))))
            {
              exit_phi = USE_STMT (use_p);
              break;
            }
        }
      if (exit_phi) 
        {
          stmt_vec_info stmt_vinfo = vinfo_for_stmt (exit_phi);
          /* FORNOW. Currently not supporting the case that an inner-loop induction
             is not used in the outer-loop (i.e. only outside the outer-loop).  */
          gcc_assert (STMT_VINFO_RELEVANT_P (stmt_vinfo)
                      && !STMT_VINFO_LIVE_P (stmt_vinfo));

          STMT_VINFO_VEC_STMT (stmt_vinfo) = new_stmt;
          if (vect_print_dump_info (REPORT_DETAILS))
            {
              fprintf (vect_dump, "vector of inductions after inner-loop:");
              print_gimple_stmt (vect_dump, new_stmt, 0, TDF_SLIM);
            }
        }
    }


  if (vect_print_dump_info (REPORT_DETAILS))
    {
      fprintf (vect_dump, "transform induction: created def-use cycle: ");
      print_gimple_stmt (vect_dump, induction_phi, 0, TDF_SLIM);
      fprintf (vect_dump, "\n");
      print_gimple_stmt (vect_dump, SSA_NAME_DEF_STMT (vec_def), 0, TDF_SLIM);
    }

  STMT_VINFO_VEC_STMT (phi_info) = induction_phi;
  return induc_def;
}


/* Function vect_get_vec_def_for_operand.

   OP is an operand in STMT. This function returns a (vector) def that will be
   used in the vectorized stmt for STMT.

   In the case that OP is an SSA_NAME which is defined in the loop, then
   STMT_VINFO_VEC_STMT of the defining stmt holds the relevant def.

   In case OP is an invariant or constant, a new stmt that creates a vector def
   needs to be introduced.  */

static tree
vect_get_vec_def_for_operand (tree op, gimple stmt, tree *scalar_def)
{
  tree vec_oprnd;
  gimple vec_stmt;
  gimple def_stmt;
  stmt_vec_info def_stmt_info = NULL;
  stmt_vec_info stmt_vinfo = vinfo_for_stmt (stmt);
  tree vectype = STMT_VINFO_VECTYPE (stmt_vinfo);
  unsigned int nunits = TYPE_VECTOR_SUBPARTS (vectype);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo);
  tree vec_inv;
  tree vec_cst;
  tree t = NULL_TREE;
  tree def;
  int i;
  enum vect_def_type dt;
  bool is_simple_use;
  tree vector_type;

  if (vect_print_dump_info (REPORT_DETAILS))
    {
      fprintf (vect_dump, "vect_get_vec_def_for_operand: ");
      print_generic_expr (vect_dump, op, TDF_SLIM);
    }

  is_simple_use = vect_is_simple_use (op, loop_vinfo, &def_stmt, &def, &dt);
  gcc_assert (is_simple_use);
  if (vect_print_dump_info (REPORT_DETAILS))
    {
      if (def)
        {
          fprintf (vect_dump, "def =  ");
          print_generic_expr (vect_dump, def, TDF_SLIM);
        }
      if (def_stmt)
        {
          fprintf (vect_dump, "  def_stmt =  ");
          print_gimple_stmt (vect_dump, def_stmt, 0, TDF_SLIM);
        }
    }

  switch (dt)
    {
    /* Case 1: operand is a constant.  */
    case vect_constant_def:
      {
        if (scalar_def) 
          *scalar_def = op;

        /* Create 'vect_cst_ = {cst,cst,...,cst}'  */
        if (vect_print_dump_info (REPORT_DETAILS))
          fprintf (vect_dump, "Create vector_cst. nunits = %d", nunits);

        for (i = nunits - 1; i >= 0; --i)
          {
            t = tree_cons (NULL_TREE, op, t);
          }
        vec_cst = build_vector (vectype, t);
        return vect_init_vector (stmt, vec_cst, vectype, NULL);
      }

    /* Case 2: operand is defined outside the loop - loop invariant.  */
    case vect_invariant_def:
      {
        vector_type = get_vectype_for_scalar_type (TREE_TYPE (def));
        gcc_assert (vector_type);
        nunits = TYPE_VECTOR_SUBPARTS (vector_type);

        if (scalar_def) 
          *scalar_def = def;

        /* Create 'vec_inv = {inv,inv,..,inv}'  */
        if (vect_print_dump_info (REPORT_DETAILS))
          fprintf (vect_dump, "Create vector_inv.");

        for (i = nunits - 1; i >= 0; --i)
          {
            t = tree_cons (NULL_TREE, def, t);
          }

        /* FIXME: use build_constructor directly.  */
        vec_inv = build_constructor_from_list (vector_type, t);
        return vect_init_vector (stmt, vec_inv, vector_type, NULL);
      }

    /* Case 3: operand is defined inside the loop.  */
    case vect_loop_def:
      {
        if (scalar_def) 
          *scalar_def = NULL/* FIXME tuples: def_stmt*/;

        /* Get the def from the vectorized stmt.  */
        def_stmt_info = vinfo_for_stmt (def_stmt);
        vec_stmt = STMT_VINFO_VEC_STMT (def_stmt_info);
        gcc_assert (vec_stmt);
        if (gimple_code (vec_stmt) == GIMPLE_PHI)
          vec_oprnd = PHI_RESULT (vec_stmt);
        else if (is_gimple_call (vec_stmt))
          vec_oprnd = gimple_call_lhs (vec_stmt);
        else
          vec_oprnd = gimple_assign_lhs (vec_stmt);
        return vec_oprnd;
      }

    /* Case 4: operand is defined by a loop header phi - reduction  */
    case vect_reduction_def:
      {
        struct loop *loop;

        gcc_assert (gimple_code (def_stmt) == GIMPLE_PHI);
        loop = (gimple_bb (def_stmt))->loop_father; 

        /* Get the def before the loop  */
        op = PHI_ARG_DEF_FROM_EDGE (def_stmt, loop_preheader_edge (loop));
        return get_initial_def_for_reduction (stmt, op, scalar_def);
     }

    /* Case 5: operand is defined by loop-header phi - induction.  */
    case vect_induction_def:
      {
        gcc_assert (gimple_code (def_stmt) == GIMPLE_PHI);

        /* Get the def from the vectorized stmt.  */
        def_stmt_info = vinfo_for_stmt (def_stmt);
        vec_stmt = STMT_VINFO_VEC_STMT (def_stmt_info);
        gcc_assert (vec_stmt && gimple_code (vec_stmt) == GIMPLE_PHI);
        vec_oprnd = PHI_RESULT (vec_stmt);
        return vec_oprnd;
      }

    default:
      gcc_unreachable ();
    }
}


/* Function vect_get_vec_def_for_stmt_copy

   Return a vector-def for an operand. This function is used when the 
   vectorized stmt to be created (by the caller to this function) is a "copy" 
   created in case the vectorized result cannot fit in one vector, and several 
   copies of the vector-stmt are required. In this case the vector-def is 
   retrieved from the vector stmt recorded in the STMT_VINFO_RELATED_STMT field
   of the stmt that defines VEC_OPRND. 
   DT is the type of the vector def VEC_OPRND.

   Context:
        In case the vectorization factor (VF) is bigger than the number
   of elements that can fit in a vectype (nunits), we have to generate
   more than one vector stmt to vectorize the scalar stmt. This situation
   arises when there are multiple data-types operated upon in the loop; the 
   smallest data-type determines the VF, and as a result, when vectorizing
   stmts operating on wider types we need to create 'VF/nunits' "copies" of the
   vector stmt (each computing a vector of 'nunits' results, and together
   computing 'VF' results in each iteration).  This function is called when 
   vectorizing such a stmt (e.g. vectorizing S2 in the illustration below, in
   which VF=16 and nunits=4, so the number of copies required is 4):

   scalar stmt:         vectorized into:        STMT_VINFO_RELATED_STMT
 
   S1: x = load         VS1.0:  vx.0 = memref0      VS1.1
                        VS1.1:  vx.1 = memref1      VS1.2
                        VS1.2:  vx.2 = memref2      VS1.3
                        VS1.3:  vx.3 = memref3 

   S2: z = x + ...      VSnew.0:  vz0 = vx.0 + ...  VSnew.1
                        VSnew.1:  vz1 = vx.1 + ...  VSnew.2
                        VSnew.2:  vz2 = vx.2 + ...  VSnew.3
                        VSnew.3:  vz3 = vx.3 + ...

   The vectorization of S1 is explained in vectorizable_load.
   The vectorization of S2:
        To create the first vector-stmt out of the 4 copies - VSnew.0 - 
   the function 'vect_get_vec_def_for_operand' is called to 
   get the relevant vector-def for each operand of S2. For operand x it
   returns  the vector-def 'vx.0'.

        To create the remaining copies of the vector-stmt (VSnew.j), this 
   function is called to get the relevant vector-def for each operand.  It is 
   obtained from the respective VS1.j stmt, which is recorded in the 
   STMT_VINFO_RELATED_STMT field of the stmt that defines VEC_OPRND.

        For example, to obtain the vector-def 'vx.1' in order to create the 
   vector stmt 'VSnew.1', this function is called with VEC_OPRND='vx.0'. 
   Given 'vx0' we obtain the stmt that defines it ('VS1.0'); from the 
   STMT_VINFO_RELATED_STMT field of 'VS1.0' we obtain the next copy - 'VS1.1',
   and return its def ('vx.1').
   Overall, to create the above sequence this function will be called 3 times:
        vx.1 = vect_get_vec_def_for_stmt_copy (dt, vx.0);
        vx.2 = vect_get_vec_def_for_stmt_copy (dt, vx.1);
        vx.3 = vect_get_vec_def_for_stmt_copy (dt, vx.2);  */

static tree
vect_get_vec_def_for_stmt_copy (enum vect_def_type dt, tree vec_oprnd)
{
  gimple vec_stmt_for_operand;
  stmt_vec_info def_stmt_info;

  /* Do nothing; can reuse same def.  */
  if (dt == vect_invariant_def || dt == vect_constant_def )
    return vec_oprnd;

  vec_stmt_for_operand = SSA_NAME_DEF_STMT (vec_oprnd);
  def_stmt_info = vinfo_for_stmt (vec_stmt_for_operand);
  gcc_assert (def_stmt_info);
  vec_stmt_for_operand = STMT_VINFO_RELATED_STMT (def_stmt_info);
  gcc_assert (vec_stmt_for_operand);
  vec_oprnd = gimple_get_lhs (vec_stmt_for_operand);
  if (gimple_code (vec_stmt_for_operand) == GIMPLE_PHI)
    vec_oprnd = PHI_RESULT (vec_stmt_for_operand);
  else
    vec_oprnd = gimple_get_lhs (vec_stmt_for_operand);
  return vec_oprnd;
}


/* Get vectorized definitions for the operands to create a copy of an original
   stmt. See vect_get_vec_def_for_stmt_copy() for details.  */

static void
vect_get_vec_defs_for_stmt_copy (enum vect_def_type *dt, 
                                 VEC(tree,heap) **vec_oprnds0, 
                                 VEC(tree,heap) **vec_oprnds1)
{
  tree vec_oprnd = VEC_pop (tree, *vec_oprnds0);

  vec_oprnd = vect_get_vec_def_for_stmt_copy (dt[0], vec_oprnd);
  VEC_quick_push (tree, *vec_oprnds0, vec_oprnd);

  if (vec_oprnds1 && *vec_oprnds1)
    {
      vec_oprnd = VEC_pop (tree, *vec_oprnds1);
      vec_oprnd = vect_get_vec_def_for_stmt_copy (dt[1], vec_oprnd);
      VEC_quick_push (tree, *vec_oprnds1, vec_oprnd);
    }
}


/* Get vectorized definitions for OP0 and OP1, or SLP_NODE if it is not NULL.  */

static void
vect_get_vec_defs (tree op0, tree op1, gimple stmt,
                   VEC(tree,heap) **vec_oprnds0, VEC(tree,heap) **vec_oprnds1,
                   slp_tree slp_node)
{
  if (slp_node)
    vect_get_slp_defs (slp_node, vec_oprnds0, vec_oprnds1);
  else
    {
      tree vec_oprnd;

      *vec_oprnds0 = VEC_alloc (tree, heap, 1); 
      vec_oprnd = vect_get_vec_def_for_operand (op0, stmt, NULL);      
      VEC_quick_push (tree, *vec_oprnds0, vec_oprnd);

      if (op1)
        {
          *vec_oprnds1 = VEC_alloc (tree, heap, 1);     
          vec_oprnd = vect_get_vec_def_for_operand (op1, stmt, NULL);      
          VEC_quick_push (tree, *vec_oprnds1, vec_oprnd);
        }
    }
}


/* Function vect_finish_stmt_generation.

   Insert a new stmt.  */

static void
vect_finish_stmt_generation (gimple stmt, gimple vec_stmt,
                             gimple_stmt_iterator *gsi)
{
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);

  gcc_assert (gimple_code (stmt) != GIMPLE_LABEL);

  gsi_insert_before (gsi, vec_stmt, GSI_SAME_STMT);

  set_vinfo_for_stmt (vec_stmt, new_stmt_vec_info (vec_stmt, loop_vinfo));

  if (vect_print_dump_info (REPORT_DETAILS))
    {
      fprintf (vect_dump, "add new stmt: ");
      print_gimple_stmt (vect_dump, vec_stmt, 0, TDF_SLIM);
    }

  gimple_set_location (vec_stmt, gimple_location (gsi_stmt (*gsi)));
}


/* Function get_initial_def_for_reduction

   Input:
   STMT - a stmt that performs a reduction operation in the loop.
   INIT_VAL - the initial value of the reduction variable

   Output:
   ADJUSTMENT_DEF - a tree that holds a value to be added to the final result
        of the reduction (used for adjusting the epilog - see below).
   Return a vector variable, initialized according to the operation that STMT
        performs. This vector will be used as the initial value of the
        vector of partial results.

   Option1 (adjust in epilog): Initialize the vector as follows:
     add:         [0,0,...,0,0]
     mult:        [1,1,...,1,1]
     min/max:     [init_val,init_val,..,init_val,init_val]
     bit and/or:  [init_val,init_val,..,init_val,init_val]
   and when necessary (e.g. add/mult case) let the caller know
   that it needs to adjust the result by init_val.

   Option2: Initialize the vector as follows:
     add:         [0,0,...,0,init_val]
     mult:        [1,1,...,1,init_val]
     min/max:     [init_val,init_val,...,init_val]
     bit and/or:  [init_val,init_val,...,init_val]
   and no adjustments are needed.

   For example, for the following code:

   s = init_val;
   for (i=0;i<n;i++)
     s = s + a[i];

   STMT is 's = s + a[i]', and the reduction variable is 's'.
   For a vector of 4 units, we want to return either [0,0,0,init_val],
   or [0,0,0,0] and let the caller know that it needs to adjust
   the result at the end by 'init_val'.

   FORNOW, we are using the 'adjust in epilog' scheme, because this way the
   initialization vector is simpler (same element in all entries).
   A cost model should help decide between these two schemes.  */

static tree
get_initial_def_for_reduction (gimple stmt, tree init_val, tree *adjustment_def)
{
  stmt_vec_info stmt_vinfo = vinfo_for_stmt (stmt);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  tree vectype = STMT_VINFO_VECTYPE (stmt_vinfo);
  int nunits =  TYPE_VECTOR_SUBPARTS (vectype);
  tree scalar_type = TREE_TYPE (vectype);
  enum tree_code code = gimple_assign_rhs_code (stmt);
  tree type = TREE_TYPE (init_val);
  tree vecdef;
  tree def_for_init;
  tree init_def;
  tree t = NULL_TREE;
  int i;
  bool nested_in_vect_loop = false; 

  gcc_assert (POINTER_TYPE_P (type) || INTEGRAL_TYPE_P (type) || SCALAR_FLOAT_TYPE_P (type));
  if (nested_in_vect_loop_p (loop, stmt))
    nested_in_vect_loop = true;
  else
    gcc_assert (loop == (gimple_bb (stmt))->loop_father);

  vecdef = vect_get_vec_def_for_operand (init_val, stmt, NULL);

  switch (code)
  {
  case WIDEN_SUM_EXPR:
  case DOT_PROD_EXPR:
  case PLUS_EXPR:
    if (nested_in_vect_loop)
      *adjustment_def = vecdef;
    else
      *adjustment_def = init_val;
    /* Create a vector of zeros for init_def.  */
    if (SCALAR_FLOAT_TYPE_P (scalar_type))
      def_for_init = build_real (scalar_type, dconst0);
    else
      def_for_init = build_int_cst (scalar_type, 0);
      
    for (i = nunits - 1; i >= 0; --i)
      t = tree_cons (NULL_TREE, def_for_init, t);
    init_def = build_vector (vectype, t);
    break;

  case MIN_EXPR:
  case MAX_EXPR:
    *adjustment_def = NULL_TREE;
    init_def = vecdef;
    break;

  default:
    gcc_unreachable ();
  }

  return init_def;
}


/* Function vect_create_epilog_for_reduction
    
   Create code at the loop-epilog to finalize the result of a reduction
   computation. 
  
   VECT_DEF is a vector of partial results. 
   REDUC_CODE is the tree-code for the epilog reduction.
   NCOPIES is > 1 in case the vectorization factor (VF) is bigger than the
     number of elements that we can fit in a vectype (nunits). In this case
     we have to generate more than one vector stmt - i.e - we need to "unroll"
     the vector stmt by a factor VF/nunits.  For more details see documentation
     in vectorizable_operation.
   STMT is the scalar reduction stmt that is being vectorized.
   REDUCTION_PHI is the phi-node that carries the reduction computation.

   This function:
   1. Creates the reduction def-use cycle: sets the arguments for 
      REDUCTION_PHI:
      The loop-entry argument is the vectorized initial-value of the reduction.
      The loop-latch argument is VECT_DEF - the vector of partial sums.
   2. "Reduces" the vector of partial results VECT_DEF into a single result,
      by applying the operation specified by REDUC_CODE if available, or by 
      other means (whole-vector shifts or a scalar loop).
      The function also creates a new phi node at the loop exit to preserve 
      loop-closed form, as illustrated below.
  
     The flow at the entry to this function:
    
        loop:
          vec_def = phi <null, null>            # REDUCTION_PHI
          VECT_DEF = vector_stmt                # vectorized form of STMT
          s_loop = scalar_stmt                  # (scalar) STMT
        loop_exit:
          s_out0 = phi <s_loop>                 # (scalar) EXIT_PHI
          use <s_out0>
          use <s_out0>

     The above is transformed by this function into:

        loop:
          vec_def = phi <vec_init, VECT_DEF>    # REDUCTION_PHI
          VECT_DEF = vector_stmt                # vectorized form of STMT
          s_loop = scalar_stmt                  # (scalar) STMT 
        loop_exit:
          s_out0 = phi <s_loop>                 # (scalar) EXIT_PHI
          v_out1 = phi <VECT_DEF>               # NEW_EXIT_PHI
          v_out2 = reduce <v_out1>
          s_out3 = extract_field <v_out2, 0>
          s_out4 = adjust_result <s_out3>
          use <s_out4>
          use <s_out4>
*/

static void
vect_create_epilog_for_reduction (tree vect_def, gimple stmt,
                                  int ncopies,
                                  enum tree_code reduc_code,
                                  gimple reduction_phi)
{
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  stmt_vec_info prev_phi_info;
  tree vectype;
  enum machine_mode mode;
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  basic_block exit_bb;
  tree scalar_dest;
  tree scalar_type;
  gimple new_phi = NULL, phi;
  gimple_stmt_iterator exit_gsi;
  tree vec_dest;
  tree new_temp = NULL_TREE;
  tree new_name;
  gimple epilog_stmt = NULL;
  tree new_scalar_dest, new_dest;
  gimple exit_phi;
  tree bitsize, bitpos, bytesize; 
  enum tree_code code = gimple_assign_rhs_code (stmt);
  tree adjustment_def;
  tree vec_initial_def, def;
  tree orig_name;
  imm_use_iterator imm_iter;
  use_operand_p use_p;
  bool extract_scalar_result = false;
  tree reduction_op, expr;
  gimple orig_stmt;
  gimple use_stmt;
  bool nested_in_vect_loop = false;
  VEC(gimple,heap) *phis = NULL;
  enum vect_def_type dt = vect_unknown_def_type;
  int j, i;
  
  if (nested_in_vect_loop_p (loop, stmt))
    {
      loop = loop->inner;
      nested_in_vect_loop = true;
    }
  
  switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt)))
    {
    case GIMPLE_SINGLE_RHS:
      gcc_assert (TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt)) == ternary_op);
      reduction_op = TREE_OPERAND (gimple_assign_rhs1 (stmt), 2);
      break;
    case GIMPLE_UNARY_RHS:
      reduction_op = gimple_assign_rhs1 (stmt);
      break;
    case GIMPLE_BINARY_RHS:
      reduction_op = gimple_assign_rhs2 (stmt);
      break;
    default:
      gcc_unreachable ();
    }

  vectype = get_vectype_for_scalar_type (TREE_TYPE (reduction_op));
  gcc_assert (vectype);
  mode = TYPE_MODE (vectype);

  /*** 1. Create the reduction def-use cycle  ***/
  
  /* For the case of reduction, vect_get_vec_def_for_operand returns
     the scalar def before the loop, that defines the initial value
     of the reduction variable.  */
  vec_initial_def = vect_get_vec_def_for_operand (reduction_op, stmt,
                                                  &adjustment_def);

  phi = reduction_phi;
  def = vect_def;
  for (j = 0; j < ncopies; j++)
    {
      /* 1.1 set the loop-entry arg of the reduction-phi:  */
      add_phi_arg (phi, vec_initial_def, loop_preheader_edge (loop));

      /* 1.2 set the loop-latch arg for the reduction-phi:  */
      if (j > 0)
        def = vect_get_vec_def_for_stmt_copy (dt, def);
      add_phi_arg (phi, def, loop_latch_edge (loop));

      if (vect_print_dump_info (REPORT_DETAILS))
        {
          fprintf (vect_dump, "transform reduction: created def-use cycle: ");
          print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
          fprintf (vect_dump, "\n");
          print_gimple_stmt (vect_dump, SSA_NAME_DEF_STMT (def), 0, TDF_SLIM);
        }

      phi = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi));
    }

  /*** 2. Create epilog code
          The reduction epilog code operates across the elements of the vector
          of partial results computed by the vectorized loop.
          The reduction epilog code consists of:
          step 1: compute the scalar result in a vector (v_out2)
          step 2: extract the scalar result (s_out3) from the vector (v_out2)
          step 3: adjust the scalar result (s_out3) if needed.

          Step 1 can be accomplished using one the following three schemes:
          (scheme 1) using reduc_code, if available.
          (scheme 2) using whole-vector shifts, if available.
          (scheme 3) using a scalar loop. In this case steps 1+2 above are 
                     combined.
                
          The overall epilog code looks like this:

          s_out0 = phi <s_loop>         # original EXIT_PHI
          v_out1 = phi <VECT_DEF>       # NEW_EXIT_PHI
          v_out2 = reduce <v_out1>              # step 1
          s_out3 = extract_field <v_out2, 0>    # step 2
          s_out4 = adjust_result <s_out3>       # step 3

          (step 3 is optional, and steps 1 and 2 may be combined).
          Lastly, the uses of s_out0 are replaced by s_out4.

          ***/

  /* 2.1 Create new loop-exit-phi to preserve loop-closed form:
        v_out1 = phi <v_loop>  */

  exit_bb = single_exit (loop)->dest;
  def = vect_def;
  prev_phi_info = NULL;
  for (j = 0; j < ncopies; j++)
    {
      phi = create_phi_node (SSA_NAME_VAR (vect_def), exit_bb);
      set_vinfo_for_stmt (phi, new_stmt_vec_info (phi, loop_vinfo));
      if (j == 0)
        new_phi = phi;
      else
        {
          def = vect_get_vec_def_for_stmt_copy (dt, def);
          STMT_VINFO_RELATED_STMT (prev_phi_info) = phi;
        }
      SET_PHI_ARG_DEF (phi, single_exit (loop)->dest_idx, def);
      prev_phi_info = vinfo_for_stmt (phi);
    }
  exit_gsi = gsi_after_labels (exit_bb);

  /* 2.2 Get the relevant tree-code to use in the epilog for schemes 2,3 
         (i.e. when reduc_code is not available) and in the final adjustment
         code (if needed).  Also get the original scalar reduction variable as
         defined in the loop.  In case STMT is a "pattern-stmt" (i.e. - it 
         represents a reduction pattern), the tree-code and scalar-def are 
         taken from the original stmt that the pattern-stmt (STMT) replaces.  
         Otherwise (it is a regular reduction) - the tree-code and scalar-def
         are taken from STMT.  */ 

  orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);
  if (!orig_stmt)
    {
      /* Regular reduction  */
      orig_stmt = stmt;
    }
  else
    {
      /* Reduction pattern  */
      stmt_vec_info stmt_vinfo = vinfo_for_stmt (orig_stmt);
      gcc_assert (STMT_VINFO_IN_PATTERN_P (stmt_vinfo));
      gcc_assert (STMT_VINFO_RELATED_STMT (stmt_vinfo) == stmt);
    }
  code = gimple_assign_rhs_code (orig_stmt);
  scalar_dest = gimple_assign_lhs (orig_stmt);
  scalar_type = TREE_TYPE (scalar_dest);
  new_scalar_dest = vect_create_destination_var (scalar_dest, NULL);
  bitsize = TYPE_SIZE (scalar_type);
  bytesize = TYPE_SIZE_UNIT (scalar_type);


  /* In case this is a reduction in an inner-loop while vectorizing an outer
     loop - we don't need to extract a single scalar result at the end of the
     inner-loop.  The final vector of partial results will be used in the
     vectorized outer-loop, or reduced to a scalar result at the end of the
     outer-loop.  */
  if (nested_in_vect_loop)
    goto vect_finalize_reduction;

  /* FORNOW */
  gcc_assert (ncopies == 1);

  /* 2.3 Create the reduction code, using one of the three schemes described
         above.  */

  if (reduc_code < NUM_TREE_CODES)
    {
      tree tmp;

      /*** Case 1:  Create:
           v_out2 = reduc_expr <v_out1>  */

      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "Reduce using direct vector reduction.");

      vec_dest = vect_create_destination_var (scalar_dest, vectype);
      tmp = build1 (reduc_code, vectype,  PHI_RESULT (new_phi));
      epilog_stmt = gimple_build_assign (vec_dest, tmp);
      new_temp = make_ssa_name (vec_dest, epilog_stmt);
      gimple_assign_set_lhs (epilog_stmt, new_temp);
      gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);

      extract_scalar_result = true;
    }
  else
    {
      enum tree_code shift_code = 0;
      bool have_whole_vector_shift = true;
      int bit_offset;
      int element_bitsize = tree_low_cst (bitsize, 1);
      int vec_size_in_bits = tree_low_cst (TYPE_SIZE (vectype), 1);
      tree vec_temp;

      if (optab_handler (vec_shr_optab, mode)->insn_code != CODE_FOR_nothing)
        shift_code = VEC_RSHIFT_EXPR;
      else
        have_whole_vector_shift = false;

      /* Regardless of whether we have a whole vector shift, if we're
         emulating the operation via tree-vect-generic, we don't want
         to use it.  Only the first round of the reduction is likely
         to still be profitable via emulation.  */
      /* ??? It might be better to emit a reduction tree code here, so that
         tree-vect-generic can expand the first round via bit tricks.  */
      if (!VECTOR_MODE_P (mode))
        have_whole_vector_shift = false;
      else
        {
          optab optab = optab_for_tree_code (code, vectype, optab_default);
          if (optab_handler (optab, mode)->insn_code == CODE_FOR_nothing)
            have_whole_vector_shift = false;
        }

      if (have_whole_vector_shift)
        {
          /*** Case 2: Create:
             for (offset = VS/2; offset >= element_size; offset/=2)
                {
                  Create:  va' = vec_shift <va, offset>
                  Create:  va = vop <va, va'>
                }  */

          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "Reduce using vector shifts");

          vec_dest = vect_create_destination_var (scalar_dest, vectype);
          new_temp = PHI_RESULT (new_phi);

          for (bit_offset = vec_size_in_bits/2;
               bit_offset >= element_bitsize;
               bit_offset /= 2)
            {
              tree bitpos = size_int (bit_offset);
              epilog_stmt = gimple_build_assign_with_ops (shift_code, vec_dest,
                                                          new_temp, bitpos);
              new_name = make_ssa_name (vec_dest, epilog_stmt);
              gimple_assign_set_lhs (epilog_stmt, new_name);
              gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);

              epilog_stmt = gimple_build_assign_with_ops (code, vec_dest,
                                                          new_name, new_temp);
              new_temp = make_ssa_name (vec_dest, epilog_stmt);
              gimple_assign_set_lhs (epilog_stmt, new_temp);
              gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
            }

          extract_scalar_result = true;
        }
      else
        {
          tree rhs;

          /*** Case 3: Create:  
             s = extract_field <v_out2, 0>
             for (offset = element_size; 
                  offset < vector_size; 
                  offset += element_size;)
               {
                 Create:  s' = extract_field <v_out2, offset>
                 Create:  s = op <s, s'>
               }  */

          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "Reduce using scalar code. ");

          vec_temp = PHI_RESULT (new_phi);
          vec_size_in_bits = tree_low_cst (TYPE_SIZE (vectype), 1);
          rhs = build3 (BIT_FIELD_REF, scalar_type, vec_temp, bitsize,
                         bitsize_zero_node);
          epilog_stmt = gimple_build_assign (new_scalar_dest, rhs);
          new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
          gimple_assign_set_lhs (epilog_stmt, new_temp);
          gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
              
          for (bit_offset = element_bitsize;
               bit_offset < vec_size_in_bits;
               bit_offset += element_bitsize)
            { 
              tree bitpos = bitsize_int (bit_offset);
              tree rhs = build3 (BIT_FIELD_REF, scalar_type, vec_temp, bitsize,
                                 bitpos);
                
              epilog_stmt = gimple_build_assign (new_scalar_dest, rhs);
              new_name = make_ssa_name (new_scalar_dest, epilog_stmt);
              gimple_assign_set_lhs (epilog_stmt, new_name);
              gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);

              epilog_stmt = gimple_build_assign_with_ops (code,
                                                          new_scalar_dest,
                                                          new_name, new_temp);
              new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
              gimple_assign_set_lhs (epilog_stmt, new_temp);
              gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
            }

          extract_scalar_result = false;
        }
    }

  /* 2.4  Extract the final scalar result.  Create:
         s_out3 = extract_field <v_out2, bitpos>  */
  
  if (extract_scalar_result)
    {
      tree rhs;

      gcc_assert (!nested_in_vect_loop);
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "extract scalar result");

      if (BYTES_BIG_ENDIAN)
        bitpos = size_binop (MULT_EXPR,
                       bitsize_int (TYPE_VECTOR_SUBPARTS (vectype) - 1),
                       TYPE_SIZE (scalar_type));
      else
        bitpos = bitsize_zero_node;

      rhs = build3 (BIT_FIELD_REF, scalar_type, new_temp, bitsize, bitpos);
      epilog_stmt = gimple_build_assign (new_scalar_dest, rhs);
      new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
      gimple_assign_set_lhs (epilog_stmt, new_temp);
      gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
    }

vect_finalize_reduction:

  /* 2.5 Adjust the final result by the initial value of the reduction
         variable. (When such adjustment is not needed, then
         'adjustment_def' is zero).  For example, if code is PLUS we create:
         new_temp = loop_exit_def + adjustment_def  */

  if (adjustment_def)
    {
      if (nested_in_vect_loop)
        {
          gcc_assert (TREE_CODE (TREE_TYPE (adjustment_def)) == VECTOR_TYPE);
          expr = build2 (code, vectype, PHI_RESULT (new_phi), adjustment_def);
          new_dest = vect_create_destination_var (scalar_dest, vectype);
        }
      else
        {
          gcc_assert (TREE_CODE (TREE_TYPE (adjustment_def)) != VECTOR_TYPE);
          expr = build2 (code, scalar_type, new_temp, adjustment_def);
          new_dest = vect_create_destination_var (scalar_dest, scalar_type);
        }
      epilog_stmt = gimple_build_assign (new_dest, expr);
      new_temp = make_ssa_name (new_dest, epilog_stmt);
      gimple_assign_set_lhs (epilog_stmt, new_temp);
      SSA_NAME_DEF_STMT (new_temp) = epilog_stmt;
      gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
    }


  /* 2.6  Handle the loop-exit phi  */

  /* Replace uses of s_out0 with uses of s_out3:
     Find the loop-closed-use at the loop exit of the original scalar result.
     (The reduction result is expected to have two immediate uses - one at the 
     latch block, and one at the loop exit).  */
  phis = VEC_alloc (gimple, heap, 10);
  FOR_EACH_IMM_USE_FAST (use_p, imm_iter, scalar_dest)
    {
      if (!flow_bb_inside_loop_p (loop, gimple_bb (USE_STMT (use_p))))
        {
          exit_phi = USE_STMT (use_p);
          VEC_quick_push (gimple, phis, exit_phi);
        }
    }
  /* We expect to have found an exit_phi because of loop-closed-ssa form.  */
  gcc_assert (!VEC_empty (gimple, phis));

  for (i = 0; VEC_iterate (gimple, phis, i, exit_phi); i++)
    {
      if (nested_in_vect_loop)
        {
          stmt_vec_info stmt_vinfo = vinfo_for_stmt (exit_phi);

          /* FORNOW. Currently not supporting the case that an inner-loop
             reduction is not used in the outer-loop (but only outside the
             outer-loop).  */
          gcc_assert (STMT_VINFO_RELEVANT_P (stmt_vinfo) 
                      && !STMT_VINFO_LIVE_P (stmt_vinfo));

          epilog_stmt = adjustment_def ? epilog_stmt : new_phi;
          STMT_VINFO_VEC_STMT (stmt_vinfo) = epilog_stmt;
          set_vinfo_for_stmt (epilog_stmt, 
                              new_stmt_vec_info (epilog_stmt, loop_vinfo));
          if (adjustment_def)
            STMT_VINFO_RELATED_STMT (vinfo_for_stmt (epilog_stmt)) =
                STMT_VINFO_RELATED_STMT (vinfo_for_stmt (new_phi));
          continue;
        }

      /* Replace the uses:  */
      orig_name = PHI_RESULT (exit_phi);
      FOR_EACH_IMM_USE_STMT (use_stmt, imm_iter, orig_name)
        FOR_EACH_IMM_USE_ON_STMT (use_p, imm_iter)
          SET_USE (use_p, new_temp);
    }
  VEC_free (gimple, heap, phis);
} 


/* Function vectorizable_reduction.

   Check if STMT performs a reduction operation that can be vectorized.
   If VEC_STMT is also passed, vectorize the STMT: create a vectorized
   stmt to replace it, put it in VEC_STMT, and insert it at BSI.
   Return FALSE if not a vectorizable STMT, TRUE otherwise.

   This function also handles reduction idioms (patterns) that have been 
   recognized in advance during vect_pattern_recog. In this case, STMT may be
   of this form:
     X = pattern_expr (arg0, arg1, ..., X)
   and it's STMT_VINFO_RELATED_STMT points to the last stmt in the original
   sequence that had been detected and replaced by the pattern-stmt (STMT).
  
   In some cases of reduction patterns, the type of the reduction variable X is
   different than the type of the other arguments of STMT.
   In such cases, the vectype that is used when transforming STMT into a vector
   stmt is different than the vectype that is used to determine the
   vectorization factor, because it consists of a different number of elements 
   than the actual number of elements that are being operated upon in parallel.

   For example, consider an accumulation of shorts into an int accumulator.
   On some targets it's possible to vectorize this pattern operating on 8
   shorts at a time (hence, the vectype for purposes of determining the
   vectorization factor should be V8HI); on the other hand, the vectype that
   is used to create the vector form is actually V4SI (the type of the result).

   Upon entry to this function, STMT_VINFO_VECTYPE records the vectype that
   indicates what is the actual level of parallelism (V8HI in the example), so
   that the right vectorization factor would be derived. This vectype
   corresponds to the type of arguments to the reduction stmt, and should *NOT*
   be used to create the vectorized stmt. The right vectype for the vectorized
   stmt is obtained from the type of the result X:
        get_vectype_for_scalar_type (TREE_TYPE (X))

   This means that, contrary to "regular" reductions (or "regular" stmts in
   general), the following equation:
      STMT_VINFO_VECTYPE == get_vectype_for_scalar_type (TREE_TYPE (X))
   does *NOT* necessarily hold for reduction patterns.  */

bool
vectorizable_reduction (gimple stmt, gimple_stmt_iterator *gsi,
                        gimple *vec_stmt)
{
  tree vec_dest;
  tree scalar_dest;
  tree loop_vec_def0 = NULL_TREE, loop_vec_def1 = NULL_TREE;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  tree vectype = STMT_VINFO_VECTYPE (stmt_info);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  enum tree_code code, orig_code, epilog_reduc_code = 0;
  enum machine_mode vec_mode;
  int op_type;
  optab optab, reduc_optab;
  tree new_temp = NULL_TREE;
  tree def;
  gimple def_stmt;
  enum vect_def_type dt;
  gimple new_phi = NULL;
  tree scalar_type;
  bool is_simple_use;
  gimple orig_stmt;
  stmt_vec_info orig_stmt_info;
  tree expr = NULL_TREE;
  int i;
  int nunits = TYPE_VECTOR_SUBPARTS (vectype);
  int ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits;
  int epilog_copies;
  stmt_vec_info prev_stmt_info, prev_phi_info;
  gimple first_phi = NULL;
  bool single_defuse_cycle = false;
  tree reduc_def;
  gimple new_stmt = NULL;
  int j;
  tree ops[3];

  if (nested_in_vect_loop_p (loop, stmt))
    loop = loop->inner;

  gcc_assert (ncopies >= 1);

  /* FORNOW: SLP not supported.  */
  if (STMT_SLP_TYPE (stmt_info))
    return false;

  /* 1. Is vectorizable reduction?  */

  /* Not supportable if the reduction variable is used in the loop.  */
  if (STMT_VINFO_RELEVANT (stmt_info) > vect_used_in_outer)
    return false;

  /* Reductions that are not used even in an enclosing outer-loop,
     are expected to be "live" (used out of the loop).  */
  if (STMT_VINFO_RELEVANT (stmt_info) == vect_unused_in_loop
      && !STMT_VINFO_LIVE_P (stmt_info))
    return false;

  /* Make sure it was already recognized as a reduction computation.  */
  if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_reduction_def)
    return false;

  /* 2. Has this been recognized as a reduction pattern? 

     Check if STMT represents a pattern that has been recognized
     in earlier analysis stages.  For stmts that represent a pattern,
     the STMT_VINFO_RELATED_STMT field records the last stmt in
     the original sequence that constitutes the pattern.  */

  orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);
  if (orig_stmt)
    {
      orig_stmt_info = vinfo_for_stmt (orig_stmt);
      gcc_assert (STMT_VINFO_RELATED_STMT (orig_stmt_info) == stmt);
      gcc_assert (STMT_VINFO_IN_PATTERN_P (orig_stmt_info));
      gcc_assert (!STMT_VINFO_IN_PATTERN_P (stmt_info));
    }
 
  /* 3. Check the operands of the operation. The first operands are defined
        inside the loop body. The last operand is the reduction variable,
        which is defined by the loop-header-phi.  */

  gcc_assert (is_gimple_assign (stmt));

  /* Flatten RHS */
  switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt)))
    {
    case GIMPLE_SINGLE_RHS:
      op_type = TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt));
      if (op_type == ternary_op)
        {
          tree rhs = gimple_assign_rhs1 (stmt);
          ops[0] = TREE_OPERAND (rhs, 0);
          ops[1] = TREE_OPERAND (rhs, 1);
          ops[2] = TREE_OPERAND (rhs, 2);
          code = TREE_CODE (rhs);
        }
      else
        return false;
      break;

    case GIMPLE_BINARY_RHS:
      code = gimple_assign_rhs_code (stmt);
      op_type = TREE_CODE_LENGTH (code);
      gcc_assert (op_type == binary_op);
      ops[0] = gimple_assign_rhs1 (stmt);
      ops[1] = gimple_assign_rhs2 (stmt);
      break;

    case GIMPLE_UNARY_RHS:
      return false;

    default:
      gcc_unreachable ();
    }

  scalar_dest = gimple_assign_lhs (stmt);
  scalar_type = TREE_TYPE (scalar_dest);
  if (!POINTER_TYPE_P (scalar_type) && !INTEGRAL_TYPE_P (scalar_type) 
      && !SCALAR_FLOAT_TYPE_P (scalar_type))
    return false;

  /* All uses but the last are expected to be defined in the loop.
     The last use is the reduction variable.  */
  for (i = 0; i < op_type-1; i++)
    {
      is_simple_use = vect_is_simple_use (ops[i], loop_vinfo, &def_stmt,
                                          &def, &dt);
      gcc_assert (is_simple_use);
      if (dt != vect_loop_def
          && dt != vect_invariant_def
          && dt != vect_constant_def
          && dt != vect_induction_def)
        return false;
    }

  is_simple_use = vect_is_simple_use (ops[i], loop_vinfo, &def_stmt, &def, &dt);
  gcc_assert (is_simple_use);
  gcc_assert (dt == vect_reduction_def);
  gcc_assert (gimple_code (def_stmt) == GIMPLE_PHI);
  if (orig_stmt) 
    gcc_assert (orig_stmt == vect_is_simple_reduction (loop_vinfo, def_stmt));
  else
    gcc_assert (stmt == vect_is_simple_reduction (loop_vinfo, def_stmt));
  
  if (STMT_VINFO_LIVE_P (vinfo_for_stmt (def_stmt)))
    return false;

  /* 4. Supportable by target?  */

  /* 4.1. check support for the operation in the loop  */
  optab = optab_for_tree_code (code, vectype, optab_default);
  if (!optab)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "no optab.");
      return false;
    }
  vec_mode = TYPE_MODE (vectype);
  if (optab_handler (optab, vec_mode)->insn_code == CODE_FOR_nothing)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "op not supported by target.");
      if (GET_MODE_SIZE (vec_mode) != UNITS_PER_WORD
          || LOOP_VINFO_VECT_FACTOR (loop_vinfo)
             < vect_min_worthwhile_factor (code))
        return false;
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "proceeding using word mode.");
    }

  /* Worthwhile without SIMD support?  */
  if (!VECTOR_MODE_P (TYPE_MODE (vectype))
      && LOOP_VINFO_VECT_FACTOR (loop_vinfo)
         < vect_min_worthwhile_factor (code))
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "not worthwhile without SIMD support.");
      return false;
    }

  /* 4.2. Check support for the epilog operation.

          If STMT represents a reduction pattern, then the type of the
          reduction variable may be different than the type of the rest
          of the arguments.  For example, consider the case of accumulation
          of shorts into an int accumulator; The original code:
                        S1: int_a = (int) short_a;
          orig_stmt->   S2: int_acc = plus <int_a ,int_acc>;

          was replaced with:
                        STMT: int_acc = widen_sum <short_a, int_acc>

          This means that:
          1. The tree-code that is used to create the vector operation in the 
             epilog code (that reduces the partial results) is not the 
             tree-code of STMT, but is rather the tree-code of the original 
             stmt from the pattern that STMT is replacing. I.e, in the example 
             above we want to use 'widen_sum' in the loop, but 'plus' in the 
             epilog.
          2. The type (mode) we use to check available target support
             for the vector operation to be created in the *epilog*, is 
             determined by the type of the reduction variable (in the example 
             above we'd check this: plus_optab[vect_int_mode]).
             However the type (mode) we use to check available target support
             for the vector operation to be created *inside the loop*, is
             determined by the type of the other arguments to STMT (in the
             example we'd check this: widen_sum_optab[vect_short_mode]).
  
          This is contrary to "regular" reductions, in which the types of all 
          the arguments are the same as the type of the reduction variable. 
          For "regular" reductions we can therefore use the same vector type 
          (and also the same tree-code) when generating the epilog code and
          when generating the code inside the loop.  */

  if (orig_stmt)
    {
      /* This is a reduction pattern: get the vectype from the type of the
         reduction variable, and get the tree-code from orig_stmt.  */
      orig_code = gimple_assign_rhs_code (orig_stmt);
      vectype = get_vectype_for_scalar_type (TREE_TYPE (def));
      if (!vectype)
        {
          if (vect_print_dump_info (REPORT_DETAILS))
            {
              fprintf (vect_dump, "unsupported data-type ");
              print_generic_expr (vect_dump, TREE_TYPE (def), TDF_SLIM);
            }
          return false;
        }

      vec_mode = TYPE_MODE (vectype);
    }
  else
    {
      /* Regular reduction: use the same vectype and tree-code as used for
         the vector code inside the loop can be used for the epilog code. */
      orig_code = code;
    }

  if (!reduction_code_for_scalar_code (orig_code, &epilog_reduc_code))
    return false;
  reduc_optab = optab_for_tree_code (epilog_reduc_code, vectype, optab_default);
  if (!reduc_optab)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "no optab for reduction.");
      epilog_reduc_code = NUM_TREE_CODES;
    }
  if (optab_handler (reduc_optab, vec_mode)->insn_code == CODE_FOR_nothing)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "reduc op not supported by target.");
      epilog_reduc_code = NUM_TREE_CODES;
    }
 
  if (!vec_stmt) /* transformation not required.  */
    {
      STMT_VINFO_TYPE (stmt_info) = reduc_vec_info_type;
      if (!vect_model_reduction_cost (stmt_info, epilog_reduc_code, ncopies))
        return false;
      return true;
    }

  /** Transform.  **/

  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "transform reduction.");

  /* Create the destination vector  */
  vec_dest = vect_create_destination_var (scalar_dest, vectype);

  /* In case the vectorization factor (VF) is bigger than the number
     of elements that we can fit in a vectype (nunits), we have to generate
     more than one vector stmt - i.e - we need to "unroll" the
     vector stmt by a factor VF/nunits.  For more details see documentation
     in vectorizable_operation.  */

  /* If the reduction is used in an outer loop we need to generate
     VF intermediate results, like so (e.g. for ncopies=2):
        r0 = phi (init, r0)
        r1 = phi (init, r1)
        r0 = x0 + r0;
        r1 = x1 + r1;
    (i.e. we generate VF results in 2 registers).
    In this case we have a separate def-use cycle for each copy, and therefore
    for each copy we get the vector def for the reduction variable from the
    respective phi node created for this copy.

    Otherwise (the reduction is unused in the loop nest), we can combine
    together intermediate results, like so (e.g. for ncopies=2):
        r = phi (init, r)
        r = x0 + r;
        r = x1 + r;
   (i.e. we generate VF/2 results in a single register).
   In this case for each copy we get the vector def for the reduction variable
   from the vectorized reduction operation generated in the previous iteration.
  */

  if (STMT_VINFO_RELEVANT (stmt_info) == vect_unused_in_loop)
    {
      single_defuse_cycle = true;
      epilog_copies = 1;
    }
  else
    epilog_copies = ncopies;

  prev_stmt_info = NULL;
  prev_phi_info = NULL;
  for (j = 0; j < ncopies; j++)
    {
      if (j == 0 || !single_defuse_cycle)
        {
          /* Create the reduction-phi that defines the reduction-operand.  */
          new_phi = create_phi_node (vec_dest, loop->header);
          set_vinfo_for_stmt (new_phi, new_stmt_vec_info (new_phi, loop_vinfo));
        }

      /* Handle uses.  */
      if (j == 0)
        {
          loop_vec_def0 = vect_get_vec_def_for_operand (ops[0], stmt, NULL);
          if (op_type == ternary_op)
            {
              loop_vec_def1 = vect_get_vec_def_for_operand (ops[1], stmt, NULL);
            }

          /* Get the vector def for the reduction variable from the phi node */
          reduc_def = PHI_RESULT (new_phi);
          first_phi = new_phi;
        }
      else
        {
          enum vect_def_type dt = vect_unknown_def_type; /* Dummy */
          loop_vec_def0 = vect_get_vec_def_for_stmt_copy (dt, loop_vec_def0);
          if (op_type == ternary_op)
            loop_vec_def1 = vect_get_vec_def_for_stmt_copy (dt, loop_vec_def1);

          if (single_defuse_cycle)
            reduc_def = gimple_assign_lhs (new_stmt);
          else
            reduc_def = PHI_RESULT (new_phi);

          STMT_VINFO_RELATED_STMT (prev_phi_info) = new_phi;
        }

      /* Arguments are ready. create the new vector stmt.  */
      if (op_type == binary_op)
        expr = build2 (code, vectype, loop_vec_def0, reduc_def);
      else
        expr = build3 (code, vectype, loop_vec_def0, loop_vec_def1, 
                       reduc_def);
      new_stmt = gimple_build_assign (vec_dest, expr);
      new_temp = make_ssa_name (vec_dest, new_stmt);
      gimple_assign_set_lhs (new_stmt, new_temp);
      vect_finish_stmt_generation (stmt, new_stmt, gsi);

      if (j == 0)
        STMT_VINFO_VEC_STMT (stmt_info) = *vec_stmt = new_stmt;
      else
        STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;
      prev_stmt_info = vinfo_for_stmt (new_stmt);
      prev_phi_info = vinfo_for_stmt (new_phi);
    }

  /* Finalize the reduction-phi (set its arguments) and create the
     epilog reduction code.  */
  if (!single_defuse_cycle)
    new_temp = gimple_assign_lhs (*vec_stmt);
  vect_create_epilog_for_reduction (new_temp, stmt, epilog_copies,
                                    epilog_reduc_code, first_phi);
  return true;
}

/* Checks if CALL can be vectorized in type VECTYPE.  Returns
   a function declaration if the target has a vectorized version
   of the function, or NULL_TREE if the function cannot be vectorized.  */

tree
vectorizable_function (gimple call, tree vectype_out, tree vectype_in)
{
  tree fndecl = gimple_call_fndecl (call);
  enum built_in_function code;

  /* We only handle functions that do not read or clobber memory -- i.e.
     const or novops ones.  */
  if (!(gimple_call_flags (call) & (ECF_CONST | ECF_NOVOPS)))
    return NULL_TREE;

  if (!fndecl
      || TREE_CODE (fndecl) != FUNCTION_DECL
      || !DECL_BUILT_IN (fndecl))
    return NULL_TREE;

  code = DECL_FUNCTION_CODE (fndecl);
  return targetm.vectorize.builtin_vectorized_function (code, vectype_out,
                                                        vectype_in);
}

/* Function vectorizable_call.

   Check if STMT performs a function call that can be vectorized. 
   If VEC_STMT is also passed, vectorize the STMT: create a vectorized 
   stmt to replace it, put it in VEC_STMT, and insert it at BSI.
   Return FALSE if not a vectorizable STMT, TRUE otherwise.  */

bool
vectorizable_call (gimple stmt, gimple_stmt_iterator *gsi, gimple *vec_stmt)
{
  tree vec_dest;
  tree scalar_dest;
  tree op, type;
  tree vec_oprnd0 = NULL_TREE, vec_oprnd1 = NULL_TREE;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt), prev_stmt_info;
  tree vectype_out, vectype_in;
  int nunits_in;
  int nunits_out;
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  tree fndecl, new_temp, def, rhs_type, lhs_type;
  gimple def_stmt;
  enum vect_def_type dt[2] = {vect_unknown_def_type, vect_unknown_def_type};
  gimple new_stmt;
  int ncopies, j;
  VEC(tree, heap) *vargs = NULL;
  enum { NARROW, NONE, WIDEN } modifier;
  size_t i, nargs;

  if (!STMT_VINFO_RELEVANT_P (stmt_info))
    return false;

  if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_loop_def)
    return false;

  /* FORNOW: SLP not supported.  */
  if (STMT_SLP_TYPE (stmt_info))
    return false;

  /* Is STMT a vectorizable call?   */
  if (!is_gimple_call (stmt))
    return false;

  if (TREE_CODE (gimple_call_lhs (stmt)) != SSA_NAME)
    return false;

  /* Process function arguments.  */
  rhs_type = NULL_TREE;
  nargs = gimple_call_num_args (stmt);

  /* Bail out if the function has more than two arguments, we
     do not have interesting builtin functions to vectorize with
     more than two arguments.  No arguments is also not good.  */
  if (nargs == 0 || nargs > 2)
    return false;

  for (i = 0; i < nargs; i++)
    {
      op = gimple_call_arg (stmt, i);

      /* We can only handle calls with arguments of the same type.  */
      if (rhs_type
          && rhs_type != TREE_TYPE (op))
        {
          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "argument types differ.");
          return false;
        }
      rhs_type = TREE_TYPE (op);

      if (!vect_is_simple_use (op, loop_vinfo, &def_stmt, &def, &dt[i]))
        {
          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "use not simple.");
          return false;
        }
    }

  vectype_in = get_vectype_for_scalar_type (rhs_type);
  if (!vectype_in)
    return false;
  nunits_in = TYPE_VECTOR_SUBPARTS (vectype_in);

  lhs_type = TREE_TYPE (gimple_call_lhs (stmt));
  vectype_out = get_vectype_for_scalar_type (lhs_type);
  if (!vectype_out)
    return false;
  nunits_out = TYPE_VECTOR_SUBPARTS (vectype_out);

  /* FORNOW */
  if (nunits_in == nunits_out / 2)
    modifier = NARROW;
  else if (nunits_out == nunits_in)
    modifier = NONE;
  else if (nunits_out == nunits_in / 2)
    modifier = WIDEN;
  else
    return false;

  /* For now, we only vectorize functions if a target specific builtin
     is available.  TODO -- in some cases, it might be profitable to
     insert the calls for pieces of the vector, in order to be able
     to vectorize other operations in the loop.  */
  fndecl = vectorizable_function (stmt, vectype_out, vectype_in);
  if (fndecl == NULL_TREE)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "function is not vectorizable.");

      return false;
    }

  gcc_assert (ZERO_SSA_OPERANDS (stmt, SSA_OP_ALL_VIRTUALS));

  if (modifier == NARROW)
    ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits_out;
  else
    ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits_in;

  /* Sanity check: make sure that at least one copy of the vectorized stmt
     needs to be generated.  */
  gcc_assert (ncopies >= 1);

  if (!vec_stmt) /* transformation not required.  */
    {
      STMT_VINFO_TYPE (stmt_info) = call_vec_info_type;
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "=== vectorizable_call ===");
      vect_model_simple_cost (stmt_info, ncopies, dt, NULL);
      return true;
    }

  /** Transform.  **/

  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "transform operation.");

  /* Handle def.  */
  scalar_dest = gimple_call_lhs (stmt);
  vec_dest = vect_create_destination_var (scalar_dest, vectype_out);

  prev_stmt_info = NULL;
  switch (modifier)
    {
    case NONE:
      for (j = 0; j < ncopies; ++j)
        {
          /* Build argument list for the vectorized call.  */
          if (j == 0)
            vargs = VEC_alloc (tree, heap, nargs);
          else
            VEC_truncate (tree, vargs, 0);

          for (i = 0; i < nargs; i++)
            {
              op = gimple_call_arg (stmt, i);
              if (j == 0)
                vec_oprnd0
                  = vect_get_vec_def_for_operand (op, stmt, NULL);
              else
                vec_oprnd0
                  = vect_get_vec_def_for_stmt_copy (dt[nargs], vec_oprnd0);

              VEC_quick_push (tree, vargs, vec_oprnd0);
            }

          new_stmt = gimple_build_call_vec (fndecl, vargs);
          new_temp = make_ssa_name (vec_dest, new_stmt);
          gimple_call_set_lhs (new_stmt, new_temp);

          vect_finish_stmt_generation (stmt, new_stmt, gsi);

          if (j == 0)
            STMT_VINFO_VEC_STMT (stmt_info) = *vec_stmt = new_stmt;
          else
            STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;

          prev_stmt_info = vinfo_for_stmt (new_stmt);
        }

      break;

    case NARROW:
      for (j = 0; j < ncopies; ++j)
        {
          /* Build argument list for the vectorized call.  */
          if (j == 0)
            vargs = VEC_alloc (tree, heap, nargs * 2);
          else
            VEC_truncate (tree, vargs, 0);

          for (i = 0; i < nargs; i++)
            {
              op = gimple_call_arg (stmt, i);
              if (j == 0)
                {
                  vec_oprnd0
                    = vect_get_vec_def_for_operand (op, stmt, NULL);
                  vec_oprnd1
                    = vect_get_vec_def_for_stmt_copy (dt[nargs], vec_oprnd0);
                }
              else
                {
                  vec_oprnd0
                    = vect_get_vec_def_for_stmt_copy (dt[nargs], vec_oprnd1);
                  vec_oprnd1
                    = vect_get_vec_def_for_stmt_copy (dt[nargs], vec_oprnd0);
                }

              VEC_quick_push (tree, vargs, vec_oprnd0);
              VEC_quick_push (tree, vargs, vec_oprnd1);
            }

          new_stmt = gimple_build_call_vec (fndecl, vargs);
          new_temp = make_ssa_name (vec_dest, new_stmt);
          gimple_call_set_lhs (new_stmt, new_temp);

          vect_finish_stmt_generation (stmt, new_stmt, gsi);

          if (j == 0)
            STMT_VINFO_VEC_STMT (stmt_info) = new_stmt;
          else
            STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;

          prev_stmt_info = vinfo_for_stmt (new_stmt);
        }

      *vec_stmt = STMT_VINFO_VEC_STMT (stmt_info);

      break;

    case WIDEN:
      /* No current target implements this case.  */
      return false;
    }

  VEC_free (tree, heap, vargs);

  /* The call in STMT might prevent it from being removed in dce.
     We however cannot remove it here, due to the way the ssa name
     it defines is mapped to the new definition.  So just replace
     rhs of the statement with something harmless.  */

  type = TREE_TYPE (scalar_dest);
  new_stmt = gimple_build_assign (gimple_call_lhs (stmt),
                                  fold_convert (type, integer_zero_node));
  set_vinfo_for_stmt (new_stmt, stmt_info);
  set_vinfo_for_stmt (stmt, NULL);
  STMT_VINFO_STMT (stmt_info) = new_stmt;
  gsi_replace (gsi, new_stmt, false);
  SSA_NAME_DEF_STMT (gimple_assign_lhs (new_stmt)) = new_stmt;

  return true;
}


/* Function vect_gen_widened_results_half

   Create a vector stmt whose code, type, number of arguments, and result
   variable are CODE, OP_TYPE, and VEC_DEST, and its arguments are 
   VEC_OPRND0 and VEC_OPRND1. The new vector stmt is to be inserted at BSI.
   In the case that CODE is a CALL_EXPR, this means that a call to DECL
   needs to be created (DECL is a function-decl of a target-builtin).
   STMT is the original scalar stmt that we are vectorizing.  */

static gimple
vect_gen_widened_results_half (enum tree_code code,
                               tree decl,
                               tree vec_oprnd0, tree vec_oprnd1, int op_type,
                               tree vec_dest, gimple_stmt_iterator *gsi,
                               gimple stmt)
{ 
  gimple new_stmt;
  tree new_temp; 
  tree sym; 
  ssa_op_iter iter;
 
  /* Generate half of the widened result:  */ 
  if (code == CALL_EXPR) 
    {  
      /* Target specific support  */ 
      if (op_type == binary_op)
        new_stmt = gimple_build_call (decl, 2, vec_oprnd0, vec_oprnd1);
      else
        new_stmt = gimple_build_call (decl, 1, vec_oprnd0);
      new_temp = make_ssa_name (vec_dest, new_stmt);
      gimple_call_set_lhs (new_stmt, new_temp);
    } 
  else 
    {
      /* Generic support */ 
      gcc_assert (op_type == TREE_CODE_LENGTH (code)); 
      if (op_type != binary_op)
        vec_oprnd1 = NULL;
      new_stmt = gimple_build_assign_with_ops (code, vec_dest, vec_oprnd0,
                                               vec_oprnd1);
      new_temp = make_ssa_name (vec_dest, new_stmt);
      gimple_assign_set_lhs (new_stmt, new_temp);
    } 
  vect_finish_stmt_generation (stmt, new_stmt, gsi);

  if (code == CALL_EXPR)
    {
      FOR_EACH_SSA_TREE_OPERAND (sym, new_stmt, iter, SSA_OP_ALL_VIRTUALS)
        {
          if (TREE_CODE (sym) == SSA_NAME)
            sym = SSA_NAME_VAR (sym);
          mark_sym_for_renaming (sym);
        }
    }

  return new_stmt;
}


/* Check if STMT performs a conversion operation, that can be vectorized. 
   If VEC_STMT is also passed, vectorize the STMT: create a vectorized 
   stmt to replace it, put it in VEC_STMT, and insert it at BSI.
   Return FALSE if not a vectorizable STMT, TRUE otherwise.  */

bool
vectorizable_conversion (gimple stmt, gimple_stmt_iterator *gsi,
                         gimple *vec_stmt, slp_tree slp_node)
{
  tree vec_dest;
  tree scalar_dest;
  tree op0;
  tree vec_oprnd0 = NULL_TREE, vec_oprnd1 = NULL_TREE;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  enum tree_code code, code1 = ERROR_MARK, code2 = ERROR_MARK;
  tree decl1 = NULL_TREE, decl2 = NULL_TREE;
  tree new_temp;
  tree def;
  gimple def_stmt;
  enum vect_def_type dt[2] = {vect_unknown_def_type, vect_unknown_def_type};
  gimple new_stmt = NULL;
  stmt_vec_info prev_stmt_info;
  int nunits_in;
  int nunits_out;
  tree vectype_out, vectype_in;
  int ncopies, j;
  tree expr;
  tree rhs_type, lhs_type;
  tree builtin_decl;
  enum { NARROW, NONE, WIDEN } modifier;
  int i;
  VEC(tree,heap) *vec_oprnds0 = NULL;
  tree vop0;
  tree integral_type;
  VEC(tree,heap) *dummy = NULL;
  int dummy_int;

  /* Is STMT a vectorizable conversion?   */

  if (!STMT_VINFO_RELEVANT_P (stmt_info))
    return false;

  if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_loop_def)
    return false;

  if (!is_gimple_assign (stmt))
    return false;

  if (TREE_CODE (gimple_assign_lhs (stmt)) != SSA_NAME)
    return false;

  code = gimple_assign_rhs_code (stmt);
  if (code != FIX_TRUNC_EXPR && code != FLOAT_EXPR)
    return false;

  /* Check types of lhs and rhs.  */
  op0 = gimple_assign_rhs1 (stmt);
  rhs_type = TREE_TYPE (op0);
  vectype_in = get_vectype_for_scalar_type (rhs_type);
  if (!vectype_in)
    return false;
  nunits_in = TYPE_VECTOR_SUBPARTS (vectype_in);

  scalar_dest = gimple_assign_lhs (stmt);
  lhs_type = TREE_TYPE (scalar_dest);
  vectype_out = get_vectype_for_scalar_type (lhs_type);
  if (!vectype_out)
    return false;
  nunits_out = TYPE_VECTOR_SUBPARTS (vectype_out);

  /* FORNOW */
  if (nunits_in == nunits_out / 2)
    modifier = NARROW;
  else if (nunits_out == nunits_in)
    modifier = NONE;
  else if (nunits_out == nunits_in / 2)
    modifier = WIDEN;
  else
    return false;

  if (modifier == NONE)
    gcc_assert (STMT_VINFO_VECTYPE (stmt_info) == vectype_out);

  /* Bail out if the types are both integral or non-integral.  */
  if ((INTEGRAL_TYPE_P (rhs_type) && INTEGRAL_TYPE_P (lhs_type))
      || (!INTEGRAL_TYPE_P (rhs_type) && !INTEGRAL_TYPE_P (lhs_type)))
    return false;

  integral_type = INTEGRAL_TYPE_P (rhs_type) ? vectype_in : vectype_out;

  if (modifier == NARROW)
    ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits_out;
  else
    ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits_in;

  /* FORNOW: SLP with multiple types is not supported. The SLP analysis verifies
     this, so we can safely override NCOPIES with 1 here.  */
  if (slp_node)
    ncopies = 1;
  
  /* Sanity check: make sure that at least one copy of the vectorized stmt
     needs to be generated.  */
  gcc_assert (ncopies >= 1);

  /* Check the operands of the operation.  */
  if (!vect_is_simple_use (op0, loop_vinfo, &def_stmt, &def, &dt[0]))
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "use not simple.");
      return false;
    }

  /* Supportable by target?  */
  if ((modifier == NONE
       && !targetm.vectorize.builtin_conversion (code, integral_type))
      || (modifier == WIDEN
          && !supportable_widening_operation (code, stmt, vectype_in,
                                              &decl1, &decl2,
                                              &code1, &code2,
                                              &dummy_int, &dummy))
      || (modifier == NARROW
          && !supportable_narrowing_operation (code, stmt, vectype_in,
                                               &code1, &dummy_int, &dummy)))
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "conversion not supported by target.");
      return false;
    }

  if (modifier != NONE)
    {
      STMT_VINFO_VECTYPE (stmt_info) = vectype_in;
      /* FORNOW: SLP not supported.  */
      if (STMT_SLP_TYPE (stmt_info))
        return false;      
    }

  if (!vec_stmt)                /* transformation not required.  */
    {
      STMT_VINFO_TYPE (stmt_info) = type_conversion_vec_info_type;
      return true;
    }

  /** Transform.  **/
  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "transform conversion.");

  /* Handle def.  */
  vec_dest = vect_create_destination_var (scalar_dest, vectype_out);

  if (modifier == NONE && !slp_node)
    vec_oprnds0 = VEC_alloc (tree, heap, 1);

  prev_stmt_info = NULL;
  switch (modifier)
    {
    case NONE:
      for (j = 0; j < ncopies; j++)
        {
          tree sym;
          ssa_op_iter iter;

          if (j == 0)
            vect_get_vec_defs (op0, NULL, stmt, &vec_oprnds0, NULL, slp_node); 
          else
            vect_get_vec_defs_for_stmt_copy (dt, &vec_oprnds0, NULL);

          builtin_decl =
            targetm.vectorize.builtin_conversion (code, integral_type);
          for (i = 0; VEC_iterate (tree, vec_oprnds0, i, vop0); i++)
            { 
              /* Arguments are ready. create the new vector stmt.  */
              new_stmt = gimple_build_call (builtin_decl, 1, vop0);
              new_temp = make_ssa_name (vec_dest, new_stmt);
              gimple_call_set_lhs (new_stmt, new_temp);
              vect_finish_stmt_generation (stmt, new_stmt, gsi);
              FOR_EACH_SSA_TREE_OPERAND (sym, new_stmt, iter, 
                                         SSA_OP_ALL_VIRTUALS)
                {
                  if (TREE_CODE (sym) == SSA_NAME)
                    sym = SSA_NAME_VAR (sym);
                  mark_sym_for_renaming (sym);
                }
              if (slp_node)
                VEC_quick_push (gimple, SLP_TREE_VEC_STMTS (slp_node), new_stmt);
            }

          if (j == 0)
            STMT_VINFO_VEC_STMT (stmt_info) = *vec_stmt = new_stmt;
          else
            STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;
          prev_stmt_info = vinfo_for_stmt (new_stmt);
        }
      break;

    case WIDEN:
      /* In case the vectorization factor (VF) is bigger than the number
         of elements that we can fit in a vectype (nunits), we have to
         generate more than one vector stmt - i.e - we need to "unroll"
         the vector stmt by a factor VF/nunits.  */
      for (j = 0; j < ncopies; j++)
        {
          if (j == 0)
            vec_oprnd0 = vect_get_vec_def_for_operand (op0, stmt, NULL);
          else
            vec_oprnd0 = vect_get_vec_def_for_stmt_copy (dt[0], vec_oprnd0);

          STMT_VINFO_VECTYPE (stmt_info) = vectype_in;

          /* Generate first half of the widened result:  */
          new_stmt
            = vect_gen_widened_results_half (code1, decl1, 
                                             vec_oprnd0, vec_oprnd1,
                                             unary_op, vec_dest, gsi, stmt);
          if (j == 0)
            STMT_VINFO_VEC_STMT (stmt_info) = new_stmt;
          else
            STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;
          prev_stmt_info = vinfo_for_stmt (new_stmt);

          /* Generate second half of the widened result:  */
          new_stmt
            = vect_gen_widened_results_half (code2, decl2,
                                             vec_oprnd0, vec_oprnd1,
                                             unary_op, vec_dest, gsi, stmt);
          STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;
          prev_stmt_info = vinfo_for_stmt (new_stmt);
        }
      break;

    case NARROW:
      /* In case the vectorization factor (VF) is bigger than the number
         of elements that we can fit in a vectype (nunits), we have to
         generate more than one vector stmt - i.e - we need to "unroll"
         the vector stmt by a factor VF/nunits.  */
      for (j = 0; j < ncopies; j++)
        {
          /* Handle uses.  */
          if (j == 0)
            {
              vec_oprnd0 = vect_get_vec_def_for_operand (op0, stmt, NULL);
              vec_oprnd1 = vect_get_vec_def_for_stmt_copy (dt[0], vec_oprnd0);
            }
          else
            {
              vec_oprnd0 = vect_get_vec_def_for_stmt_copy (dt[0], vec_oprnd1);
              vec_oprnd1 = vect_get_vec_def_for_stmt_copy (dt[0], vec_oprnd0);
            }

          /* Arguments are ready. Create the new vector stmt.  */
          expr = build2 (code1, vectype_out, vec_oprnd0, vec_oprnd1);
          new_stmt = gimple_build_assign_with_ops (code1, vec_dest, vec_oprnd0,
                                                   vec_oprnd1);
          new_temp = make_ssa_name (vec_dest, new_stmt);
          gimple_assign_set_lhs (new_stmt, new_temp);
          vect_finish_stmt_generation (stmt, new_stmt, gsi);

          if (j == 0)
            STMT_VINFO_VEC_STMT (stmt_info) = new_stmt;
          else
            STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;

          prev_stmt_info = vinfo_for_stmt (new_stmt);
        }

      *vec_stmt = STMT_VINFO_VEC_STMT (stmt_info);
    }

  if (vec_oprnds0)
    VEC_free (tree, heap, vec_oprnds0); 

  return true;
}


/* Function vectorizable_assignment.

   Check if STMT performs an assignment (copy) that can be vectorized. 
   If VEC_STMT is also passed, vectorize the STMT: create a vectorized 
   stmt to replace it, put it in VEC_STMT, and insert it at BSI.
   Return FALSE if not a vectorizable STMT, TRUE otherwise.  */

bool
vectorizable_assignment (gimple stmt, gimple_stmt_iterator *gsi,
                         gimple *vec_stmt, slp_tree slp_node)
{
  tree vec_dest;
  tree scalar_dest;
  tree op;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  tree vectype = STMT_VINFO_VECTYPE (stmt_info);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  tree new_temp;
  tree def;
  gimple def_stmt;
  enum vect_def_type dt[2] = {vect_unknown_def_type, vect_unknown_def_type};
  int nunits = TYPE_VECTOR_SUBPARTS (vectype);
  int ncopies;
  int i;
  VEC(tree,heap) *vec_oprnds = NULL;
  tree vop;

  /* Multiple types in SLP are handled by creating the appropriate number of
     vectorized stmts for each SLP node. Hence, NCOPIES is always 1 in
     case of SLP.  */
  if (slp_node)
    ncopies = 1;
  else
    ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits;

  gcc_assert (ncopies >= 1);
  if (ncopies > 1)
    return false; /* FORNOW */

  if (!STMT_VINFO_RELEVANT_P (stmt_info))
    return false;

  if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_loop_def)
    return false;

  /* Is vectorizable assignment?  */
  if (!is_gimple_assign (stmt))
    return false;

  scalar_dest = gimple_assign_lhs (stmt);
  if (TREE_CODE (scalar_dest) != SSA_NAME)
    return false;

  if (gimple_assign_single_p (stmt)
      || gimple_assign_rhs_code (stmt) == PAREN_EXPR)
    op = gimple_assign_rhs1 (stmt);
  else
    return false;

  if (!vect_is_simple_use (op, loop_vinfo, &def_stmt, &def, &dt[0]))
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "use not simple.");
      return false;
    }

  if (!vec_stmt) /* transformation not required.  */
    {
      STMT_VINFO_TYPE (stmt_info) = assignment_vec_info_type;
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "=== vectorizable_assignment ===");
      vect_model_simple_cost (stmt_info, ncopies, dt, NULL);
      return true;
    }

  /** Transform.  **/
  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "transform assignment.");

  /* Handle def.  */
  vec_dest = vect_create_destination_var (scalar_dest, vectype);

  /* Handle use.  */
  vect_get_vec_defs (op, NULL, stmt, &vec_oprnds, NULL, slp_node);

  /* Arguments are ready. create the new vector stmt.  */
  for (i = 0; VEC_iterate (tree, vec_oprnds, i, vop); i++)
    {
      *vec_stmt = gimple_build_assign (vec_dest, vop);
      new_temp = make_ssa_name (vec_dest, *vec_stmt);
      gimple_assign_set_lhs (*vec_stmt, new_temp);
      vect_finish_stmt_generation (stmt, *vec_stmt, gsi);
      STMT_VINFO_VEC_STMT (stmt_info) = *vec_stmt;

      if (slp_node)
        VEC_quick_push (gimple, SLP_TREE_VEC_STMTS (slp_node), *vec_stmt);
   }
  
  VEC_free (tree, heap, vec_oprnds);       
  return true;
}


/* Function vect_min_worthwhile_factor.

   For a loop where we could vectorize the operation indicated by CODE,
   return the minimum vectorization factor that makes it worthwhile
   to use generic vectors.  */
static int
vect_min_worthwhile_factor (enum tree_code code)
{
  switch (code)
    {
    case PLUS_EXPR:
    case MINUS_EXPR:
    case NEGATE_EXPR:
      return 4;

    case BIT_AND_EXPR:
    case BIT_IOR_EXPR:
    case BIT_XOR_EXPR:
    case BIT_NOT_EXPR:
      return 2;

    default:
      return INT_MAX;
    }
}


/* Function vectorizable_induction

   Check if PHI performs an induction computation that can be vectorized.
   If VEC_STMT is also passed, vectorize the induction PHI: create a vectorized
   phi to replace it, put it in VEC_STMT, and add it to the same basic block.
   Return FALSE if not a vectorizable STMT, TRUE otherwise.  */

bool
vectorizable_induction (gimple phi, gimple_stmt_iterator *gsi ATTRIBUTE_UNUSED,
                        gimple *vec_stmt)
{
  stmt_vec_info stmt_info = vinfo_for_stmt (phi);
  tree vectype = STMT_VINFO_VECTYPE (stmt_info);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  int nunits = TYPE_VECTOR_SUBPARTS (vectype);
  int ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits;
  tree vec_def;

  gcc_assert (ncopies >= 1);
  /* FORNOW. This restriction should be relaxed.  */
  if (nested_in_vect_loop_p (loop, phi) && ncopies > 1)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "multiple types in nested loop.");
      return false;
    }

  if (!STMT_VINFO_RELEVANT_P (stmt_info))
    return false;

  /* FORNOW: SLP not supported.  */
  if (STMT_SLP_TYPE (stmt_info))
    return false;

  gcc_assert (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def);

  if (gimple_code (phi) != GIMPLE_PHI)
    return false;

  if (!vec_stmt) /* transformation not required.  */
    {
      STMT_VINFO_TYPE (stmt_info) = induc_vec_info_type;
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "=== vectorizable_induction ===");
      vect_model_induction_cost (stmt_info, ncopies);
      return true;
    }

  /** Transform.  **/

  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "transform induction phi.");

  vec_def = get_initial_def_for_induction (phi);
  *vec_stmt = SSA_NAME_DEF_STMT (vec_def);
  return true;
}


/* Function vectorizable_operation.

   Check if STMT performs a binary or unary operation that can be vectorized. 
   If VEC_STMT is also passed, vectorize the STMT: create a vectorized 
   stmt to replace it, put it in VEC_STMT, and insert it at BSI.
   Return FALSE if not a vectorizable STMT, TRUE otherwise.  */

bool
vectorizable_operation (gimple stmt, gimple_stmt_iterator *gsi,
                        gimple *vec_stmt, slp_tree slp_node)
{
  tree vec_dest;
  tree scalar_dest;
  tree op0, op1 = NULL;
  tree vec_oprnd1 = NULL_TREE;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  tree vectype = STMT_VINFO_VECTYPE (stmt_info);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  enum tree_code code;
  enum machine_mode vec_mode;
  tree new_temp;
  int op_type;
  optab optab;
  int icode;
  enum machine_mode optab_op2_mode;
  tree def;
  gimple def_stmt;
  enum vect_def_type dt[2] = {vect_unknown_def_type, vect_unknown_def_type};
  gimple new_stmt = NULL;
  stmt_vec_info prev_stmt_info;
  int nunits_in = TYPE_VECTOR_SUBPARTS (vectype);
  int nunits_out;
  tree vectype_out;
  int ncopies;
  int j, i;
  VEC(tree,heap) *vec_oprnds0 = NULL, *vec_oprnds1 = NULL;
  tree vop0, vop1;
  unsigned int k;
  bool shift_p = false;
  bool scalar_shift_arg = false;

  /* Multiple types in SLP are handled by creating the appropriate number of
     vectorized stmts for each SLP node. Hence, NCOPIES is always 1 in
     case of SLP.  */
  if (slp_node)
    ncopies = 1;
  else
    ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits_in;

  gcc_assert (ncopies >= 1);

  if (!STMT_VINFO_RELEVANT_P (stmt_info))
    return false;

  if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_loop_def)
    return false;

  /* Is STMT a vectorizable binary/unary operation?   */
  if (!is_gimple_assign (stmt))
    return false;

  if (TREE_CODE (gimple_assign_lhs (stmt)) != SSA_NAME)
    return false;

  scalar_dest = gimple_assign_lhs (stmt);
  vectype_out = get_vectype_for_scalar_type (TREE_TYPE (scalar_dest));
  if (!vectype_out)
    return false;
  nunits_out = TYPE_VECTOR_SUBPARTS (vectype_out);
  if (nunits_out != nunits_in)
    return false;

  code = gimple_assign_rhs_code (stmt);

  /* For pointer addition, we should use the normal plus for
     the vector addition.  */
  if (code == POINTER_PLUS_EXPR)
    code = PLUS_EXPR;

  /* Support only unary or binary operations.  */
  op_type = TREE_CODE_LENGTH (code);
  if (op_type != unary_op && op_type != binary_op)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "num. args = %d (not unary/binary op).", op_type);
      return false;
    }

  op0 = gimple_assign_rhs1 (stmt);
  if (!vect_is_simple_use (op0, loop_vinfo, &def_stmt, &def, &dt[0]))
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "use not simple.");
      return false;
    }

  if (op_type == binary_op)
    {
      op1 = gimple_assign_rhs2 (stmt);
      if (!vect_is_simple_use (op1, loop_vinfo, &def_stmt, &def, &dt[1]))
        {
          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "use not simple.");
          return false;
        }
    }

  /* If this is a shift/rotate, determine whether the shift amount is a vector,
     or scalar.  If the shift/rotate amount is a vector, use the vector/vector
     shift optabs.  */
  if (code == LSHIFT_EXPR || code == RSHIFT_EXPR || code == LROTATE_EXPR
      || code == RROTATE_EXPR)
    {
      shift_p = true;

      /* vector shifted by vector */
      if (dt[1] == vect_loop_def)
        {
          optab = optab_for_tree_code (code, vectype, optab_vector);
          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "vector/vector shift/rotate found.");
        }

      /* See if the machine has a vector shifted by scalar insn and if not
         then see if it has a vector shifted by vector insn */
      else if (dt[1] == vect_constant_def || dt[1] == vect_invariant_def)
        {
          optab = optab_for_tree_code (code, vectype, optab_scalar);
          if (optab
              && (optab_handler (optab, TYPE_MODE (vectype))->insn_code
                  != CODE_FOR_nothing))
            {
              scalar_shift_arg = true;
              if (vect_print_dump_info (REPORT_DETAILS))
                fprintf (vect_dump, "vector/scalar shift/rotate found.");
            }
          else
            {
              optab = optab_for_tree_code (code, vectype, optab_vector);
              if (vect_print_dump_info (REPORT_DETAILS)
                  && optab
                  && (optab_handler (optab, TYPE_MODE (vectype))->insn_code
                      != CODE_FOR_nothing))
                fprintf (vect_dump, "vector/vector shift/rotate found.");
            }
        }

      else
        {
          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "operand mode requires invariant argument.");
          return false;
        }
    }
  else
    optab = optab_for_tree_code (code, vectype, optab_default);

  /* Supportable by target?  */
  if (!optab)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "no optab.");
      return false;
    }
  vec_mode = TYPE_MODE (vectype);
  icode = (int) optab_handler (optab, vec_mode)->insn_code;
  if (icode == CODE_FOR_nothing)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "op not supported by target.");
      /* Check only during analysis.  */
      if (GET_MODE_SIZE (vec_mode) != UNITS_PER_WORD
          || (LOOP_VINFO_VECT_FACTOR (loop_vinfo)
              < vect_min_worthwhile_factor (code)
              && !vec_stmt))
        return false;
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "proceeding using word mode.");
    }

  /* Worthwhile without SIMD support? Check only during analysis.  */
  if (!VECTOR_MODE_P (TYPE_MODE (vectype))
      && LOOP_VINFO_VECT_FACTOR (loop_vinfo)
         < vect_min_worthwhile_factor (code)
      && !vec_stmt)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "not worthwhile without SIMD support.");
      return false;
    }

  if (!vec_stmt) /* transformation not required.  */
    {
      STMT_VINFO_TYPE (stmt_info) = op_vec_info_type;
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "=== vectorizable_operation ===");
      vect_model_simple_cost (stmt_info, ncopies, dt, NULL);
      return true;
    }

  /** Transform.  **/

  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "transform binary/unary operation.");

  /* Handle def.  */
  vec_dest = vect_create_destination_var (scalar_dest, vectype);

  /* Allocate VECs for vector operands. In case of SLP, vector operands are 
     created in the previous stages of the recursion, so no allocation is
     needed, except for the case of shift with scalar shift argument. In that
     case we store the scalar operand in VEC_OPRNDS1 for every vector stmt to
     be created to vectorize the SLP group, i.e., SLP_NODE->VEC_STMTS_SIZE.
     In case of loop-based vectorization we allocate VECs of size 1. We 
     allocate VEC_OPRNDS1 only in case of binary operation.  */ 
  if (!slp_node)
    {
      vec_oprnds0 = VEC_alloc (tree, heap, 1);
      if (op_type == binary_op)
        vec_oprnds1 = VEC_alloc (tree, heap, 1);
    }
  else if (scalar_shift_arg)
    vec_oprnds1 = VEC_alloc (tree, heap, slp_node->vec_stmts_size);  

  /* In case the vectorization factor (VF) is bigger than the number
     of elements that we can fit in a vectype (nunits), we have to generate
     more than one vector stmt - i.e - we need to "unroll" the
     vector stmt by a factor VF/nunits. In doing so, we record a pointer
     from one copy of the vector stmt to the next, in the field
     STMT_VINFO_RELATED_STMT. This is necessary in order to allow following
     stages to find the correct vector defs to be used when vectorizing
     stmts that use the defs of the current stmt. The example below illustrates
     the vectorization process when VF=16 and nunits=4 (i.e - we need to create
     4 vectorized stmts):

     before vectorization:
                                RELATED_STMT    VEC_STMT
        S1:     x = memref      -               -
        S2:     z = x + 1       -               -

     step 1: vectorize stmt S1 (done in vectorizable_load. See more details
             there):
                                RELATED_STMT    VEC_STMT
        VS1_0:  vx0 = memref0   VS1_1           -
        VS1_1:  vx1 = memref1   VS1_2           -
        VS1_2:  vx2 = memref2   VS1_3           -
        VS1_3:  vx3 = memref3   -               -
        S1:     x = load        -               VS1_0
        S2:     z = x + 1       -               -

     step2: vectorize stmt S2 (done here):
        To vectorize stmt S2 we first need to find the relevant vector
        def for the first operand 'x'. This is, as usual, obtained from
        the vector stmt recorded in the STMT_VINFO_VEC_STMT of the stmt
        that defines 'x' (S1). This way we find the stmt VS1_0, and the
        relevant vector def 'vx0'. Having found 'vx0' we can generate
        the vector stmt VS2_0, and as usual, record it in the
        STMT_VINFO_VEC_STMT of stmt S2.
        When creating the second copy (VS2_1), we obtain the relevant vector
        def from the vector stmt recorded in the STMT_VINFO_RELATED_STMT of
        stmt VS1_0. This way we find the stmt VS1_1 and the relevant
        vector def 'vx1'. Using 'vx1' we create stmt VS2_1 and record a
        pointer to it in the STMT_VINFO_RELATED_STMT of the vector stmt VS2_0.
        Similarly when creating stmts VS2_2 and VS2_3. This is the resulting
        chain of stmts and pointers:
                                RELATED_STMT    VEC_STMT
        VS1_0:  vx0 = memref0   VS1_1           -
        VS1_1:  vx1 = memref1   VS1_2           -
        VS1_2:  vx2 = memref2   VS1_3           -
        VS1_3:  vx3 = memref3   -               -
        S1:     x = load        -               VS1_0
        VS2_0:  vz0 = vx0 + v1  VS2_1           -
        VS2_1:  vz1 = vx1 + v1  VS2_2           -
        VS2_2:  vz2 = vx2 + v1  VS2_3           -
        VS2_3:  vz3 = vx3 + v1  -               -
        S2:     z = x + 1       -               VS2_0  */

  prev_stmt_info = NULL;
  for (j = 0; j < ncopies; j++)
    {
      /* Handle uses.  */
      if (j == 0)
        {
          if (op_type == binary_op && scalar_shift_arg)
            {
              /* Vector shl and shr insn patterns can be defined with scalar 
                 operand 2 (shift operand). In this case, use constant or loop 
                 invariant op1 directly, without extending it to vector mode 
                 first.  */
              optab_op2_mode = insn_data[icode].operand[2].mode;
              if (!VECTOR_MODE_P (optab_op2_mode))
                {
                  if (vect_print_dump_info (REPORT_DETAILS))
                    fprintf (vect_dump, "operand 1 using scalar mode.");
                  vec_oprnd1 = op1;
                  VEC_quick_push (tree, vec_oprnds1, vec_oprnd1);
                  if (slp_node)
                    {
                      /* Store vec_oprnd1 for every vector stmt to be created
                         for SLP_NODE. We check during the analysis that all the
                         shift arguments are the same.  
                         TODO: Allow different constants for different vector 
                         stmts generated for an SLP instance.  */          
                      for (k = 0; k < slp_node->vec_stmts_size - 1; k++)
                        VEC_quick_push (tree, vec_oprnds1, vec_oprnd1);
                    }
                }
            }
         
          /* vec_oprnd1 is available if operand 1 should be of a scalar-type 
             (a special case for certain kind of vector shifts); otherwise, 
             operand 1 should be of a vector type (the usual case).  */
          if (op_type == binary_op && !vec_oprnd1)
            vect_get_vec_defs (op0, op1, stmt, &vec_oprnds0, &vec_oprnds1, 
                               slp_node);
          else
            vect_get_vec_defs (op0, NULL_TREE, stmt, &vec_oprnds0, NULL, 
                               slp_node);
        }
      else
        vect_get_vec_defs_for_stmt_copy (dt, &vec_oprnds0, &vec_oprnds1);

      /* Arguments are ready. Create the new vector stmt.  */
      for (i = 0; VEC_iterate (tree, vec_oprnds0, i, vop0); i++)
        {
          vop1 = ((op_type == binary_op)
                  ? VEC_index (tree, vec_oprnds1, i) : NULL);
          new_stmt = gimple_build_assign_with_ops (code, vec_dest, vop0, vop1);
          new_temp = make_ssa_name (vec_dest, new_stmt);
          gimple_assign_set_lhs (new_stmt, new_temp);
          vect_finish_stmt_generation (stmt, new_stmt, gsi);
          if (slp_node)
            VEC_quick_push (gimple, SLP_TREE_VEC_STMTS (slp_node), new_stmt);
        }

      if (slp_node)
        continue;

      if (j == 0)
        STMT_VINFO_VEC_STMT (stmt_info) = *vec_stmt = new_stmt;
      else
        STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;
      prev_stmt_info = vinfo_for_stmt (new_stmt);
    }

  VEC_free (tree, heap, vec_oprnds0);
  if (vec_oprnds1)
    VEC_free (tree, heap, vec_oprnds1);

  return true;
}


/* Get vectorized definitions for loop-based vectorization. For the first
   operand we call vect_get_vec_def_for_operand() (with OPRND containing 
   scalar operand), and for the rest we get a copy with 
   vect_get_vec_def_for_stmt_copy() using the previous vector definition
   (stored in OPRND). See vect_get_vec_def_for_stmt_copy() for details.
   The vectors are collected into VEC_OPRNDS.  */

static void
vect_get_loop_based_defs (tree *oprnd, gimple stmt, enum vect_def_type dt, 
                          VEC (tree, heap) **vec_oprnds, int multi_step_cvt)
{
  tree vec_oprnd;

  /* Get first vector operand.  */
  /* All the vector operands except the very first one (that is scalar oprnd)
     are stmt copies.  */
  if (TREE_CODE (TREE_TYPE (*oprnd)) != VECTOR_TYPE)  
    vec_oprnd = vect_get_vec_def_for_operand (*oprnd, stmt, NULL);
  else
    vec_oprnd = vect_get_vec_def_for_stmt_copy (dt, *oprnd);

  VEC_quick_push (tree, *vec_oprnds, vec_oprnd);

  /* Get second vector operand.  */
  vec_oprnd = vect_get_vec_def_for_stmt_copy (dt, vec_oprnd);
  VEC_quick_push (tree, *vec_oprnds, vec_oprnd);
    
  *oprnd = vec_oprnd;

  /* For conversion in multiple steps, continue to get operands 
     recursively.  */
  if (multi_step_cvt)
    vect_get_loop_based_defs (oprnd, stmt, dt, vec_oprnds,  multi_step_cvt - 1); 
}


/* Create vectorized demotion statements for vector operands from VEC_OPRNDS.
   For multi-step conversions store the resulting vectors and call the function 
   recursively.  */

static void
vect_create_vectorized_demotion_stmts (VEC (tree, heap) **vec_oprnds,
                                       int multi_step_cvt, gimple stmt,
                                       VEC (tree, heap) *vec_dsts,
                                       gimple_stmt_iterator *gsi,
                                       slp_tree slp_node, enum tree_code code,
                                       stmt_vec_info *prev_stmt_info)
{
  unsigned int i;
  tree vop0, vop1, new_tmp, vec_dest;
  gimple new_stmt;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);

  vec_dest = VEC_pop (tree, vec_dsts); 

  for (i = 0; i < VEC_length (tree, *vec_oprnds); i += 2)
    {
      /* Create demotion operation.  */
      vop0 = VEC_index (tree, *vec_oprnds, i);
      vop1 = VEC_index (tree, *vec_oprnds, i + 1);
      new_stmt = gimple_build_assign_with_ops (code, vec_dest, vop0, vop1);
      new_tmp = make_ssa_name (vec_dest, new_stmt);
      gimple_assign_set_lhs (new_stmt, new_tmp);
      vect_finish_stmt_generation (stmt, new_stmt, gsi);

      if (multi_step_cvt)
        /* Store the resulting vector for next recursive call.  */
        VEC_replace (tree, *vec_oprnds, i/2, new_tmp);      
      else
        {
          /* This is the last step of the conversion sequence. Store the 
             vectors in SLP_NODE or in vector info of the scalar statement
             (or in STMT_VINFO_RELATED_STMT chain).  */
          if (slp_node)
            VEC_quick_push (gimple, SLP_TREE_VEC_STMTS (slp_node), new_stmt);
          else
            {
              if (!*prev_stmt_info)
                STMT_VINFO_VEC_STMT (stmt_info) = new_stmt;
              else
                STMT_VINFO_RELATED_STMT (*prev_stmt_info) = new_stmt;

              *prev_stmt_info = vinfo_for_stmt (new_stmt);
            }
        }
    }

  /* For multi-step demotion operations we first generate demotion operations
     from the source type to the intermediate types, and then combine the 
     results (stored in VEC_OPRNDS) in demotion operation to the destination
     type.  */
  if (multi_step_cvt)
    {
      /* At each level of recursion we have have of the operands we had at the
         previous level.  */
      VEC_truncate (tree, *vec_oprnds, (i+1)/2);
      vect_create_vectorized_demotion_stmts (vec_oprnds, multi_step_cvt - 1, 
                                             stmt, vec_dsts, gsi, slp_node,
                                             code, prev_stmt_info);
    }
}


/* Function vectorizable_type_demotion

   Check if STMT performs a binary or unary operation that involves
   type demotion, and if it can be vectorized.
   If VEC_STMT is also passed, vectorize the STMT: create a vectorized
   stmt to replace it, put it in VEC_STMT, and insert it at BSI.
   Return FALSE if not a vectorizable STMT, TRUE otherwise.  */

bool
vectorizable_type_demotion (gimple stmt, gimple_stmt_iterator *gsi,
                            gimple *vec_stmt, slp_tree slp_node)
{
  tree vec_dest;
  tree scalar_dest;
  tree op0;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  enum tree_code code, code1 = ERROR_MARK;
  tree def;
  gimple def_stmt;
  enum vect_def_type dt[2] = {vect_unknown_def_type, vect_unknown_def_type};
  stmt_vec_info prev_stmt_info;
  int nunits_in;
  int nunits_out;
  tree vectype_out;
  int ncopies;
  int j, i;
  tree vectype_in;
  int multi_step_cvt = 0;
  VEC (tree, heap) *vec_oprnds0 = NULL;
  VEC (tree, heap) *vec_dsts = NULL, *interm_types = NULL, *tmp_vec_dsts = NULL;
  tree last_oprnd, intermediate_type;

  if (!STMT_VINFO_RELEVANT_P (stmt_info))
    return false;

  if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_loop_def)
    return false;

  /* Is STMT a vectorizable type-demotion operation?  */
  if (!is_gimple_assign (stmt))
    return false;

  if (TREE_CODE (gimple_assign_lhs (stmt)) != SSA_NAME)
    return false;

  code = gimple_assign_rhs_code (stmt);
  if (!CONVERT_EXPR_CODE_P (code))
    return false;

  op0 = gimple_assign_rhs1 (stmt);
  vectype_in = get_vectype_for_scalar_type (TREE_TYPE (op0));
  if (!vectype_in)
    return false;
  nunits_in = TYPE_VECTOR_SUBPARTS (vectype_in);

  scalar_dest = gimple_assign_lhs (stmt);
  vectype_out = get_vectype_for_scalar_type (TREE_TYPE (scalar_dest));
  if (!vectype_out)
    return false;
  nunits_out = TYPE_VECTOR_SUBPARTS (vectype_out);
  if (nunits_in >= nunits_out)
    return false;

  /* Multiple types in SLP are handled by creating the appropriate number of
     vectorized stmts for each SLP node. Hence, NCOPIES is always 1 in
     case of SLP.  */
  if (slp_node)
    ncopies = 1;
  else
    ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits_out;

  gcc_assert (ncopies >= 1);

  if (! ((INTEGRAL_TYPE_P (TREE_TYPE (scalar_dest))
          && INTEGRAL_TYPE_P (TREE_TYPE (op0)))
         || (SCALAR_FLOAT_TYPE_P (TREE_TYPE (scalar_dest))
             && SCALAR_FLOAT_TYPE_P (TREE_TYPE (op0))
             && CONVERT_EXPR_CODE_P (code))))
    return false;

  /* Check the operands of the operation.  */
  if (!vect_is_simple_use (op0, loop_vinfo, &def_stmt, &def, &dt[0]))
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "use not simple.");
      return false;
    }

  /* Supportable by target?  */
  if (!supportable_narrowing_operation (code, stmt, vectype_in, &code1,
                                        &multi_step_cvt, &interm_types))
    return false;

  STMT_VINFO_VECTYPE (stmt_info) = vectype_in;

  if (!vec_stmt) /* transformation not required.  */
    {
      STMT_VINFO_TYPE (stmt_info) = type_demotion_vec_info_type;
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "=== vectorizable_demotion ===");
      vect_model_simple_cost (stmt_info, ncopies, dt, NULL);
      return true;
    }

  /** Transform.  **/
  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "transform type demotion operation. ncopies = %d.",
             ncopies);

  /* In case of multi-step demotion, we first generate demotion operations to 
     the intermediate types, and then from that types to the final one. 
     We create vector destinations for the intermediate type (TYPES) received
     from supportable_narrowing_operation, and store them in the correct order 
     for future use in vect_create_vectorized_demotion_stmts().  */
  if (multi_step_cvt)
    vec_dsts = VEC_alloc (tree, heap, multi_step_cvt + 1);
  else
    vec_dsts = VEC_alloc (tree, heap, 1);
 
  vec_dest = vect_create_destination_var (scalar_dest, vectype_out);
  VEC_quick_push (tree, vec_dsts, vec_dest);

  if (multi_step_cvt)
    {
      for (i = VEC_length (tree, interm_types) - 1; 
           VEC_iterate (tree, interm_types, i, intermediate_type); i--)
        {
          vec_dest = vect_create_destination_var (scalar_dest, 
                                                  intermediate_type);
          VEC_quick_push (tree, vec_dsts, vec_dest);
        }
    }

  /* In case the vectorization factor (VF) is bigger than the number
     of elements that we can fit in a vectype (nunits), we have to generate
     more than one vector stmt - i.e - we need to "unroll" the
     vector stmt by a factor VF/nunits.   */
  last_oprnd = op0;
  prev_stmt_info = NULL;
  for (j = 0; j < ncopies; j++)
    {
      /* Handle uses.  */
      if (slp_node)
        vect_get_slp_defs (slp_node, &vec_oprnds0, NULL); 
      else
        {
          VEC_free (tree, heap, vec_oprnds0);
          vec_oprnds0 = VEC_alloc (tree, heap,
                        (multi_step_cvt ? vect_pow2 (multi_step_cvt) * 2 : 2));
          vect_get_loop_based_defs (&last_oprnd, stmt, dt[0], &vec_oprnds0,  
                                    vect_pow2 (multi_step_cvt) - 1);
        }

      /* Arguments are ready. Create the new vector stmts.  */
      tmp_vec_dsts = VEC_copy (tree, heap, vec_dsts);
      vect_create_vectorized_demotion_stmts (&vec_oprnds0,  
                                             multi_step_cvt, stmt, tmp_vec_dsts,
                                             gsi, slp_node, code1, 
                                             &prev_stmt_info);
    }

  VEC_free (tree, heap, vec_oprnds0);
  VEC_free (tree, heap, vec_dsts);
  VEC_free (tree, heap, tmp_vec_dsts);
  VEC_free (tree, heap, interm_types);

  *vec_stmt = STMT_VINFO_VEC_STMT (stmt_info);
  return true;
}


/* Create vectorized promotion statements for vector operands from VEC_OPRNDS0
   and VEC_OPRNDS1 (for binary operations). For multi-step conversions store 
   the resulting vectors and call the function recursively.  */

static void
vect_create_vectorized_promotion_stmts (VEC (tree, heap) **vec_oprnds0,
                                        VEC (tree, heap) **vec_oprnds1,
                                        int multi_step_cvt, gimple stmt,
                                        VEC (tree, heap) *vec_dsts,
                                        gimple_stmt_iterator *gsi,
                                        slp_tree slp_node, enum tree_code code1,
                                        enum tree_code code2, tree decl1, 
                                        tree decl2, int op_type,
                                        stmt_vec_info *prev_stmt_info)
{
  int i;
  tree vop0, vop1, new_tmp1, new_tmp2, vec_dest;
  gimple new_stmt1, new_stmt2;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  VEC (tree, heap) *vec_tmp;

  vec_dest = VEC_pop (tree, vec_dsts);
  vec_tmp = VEC_alloc (tree, heap, VEC_length (tree, *vec_oprnds0) * 2);

  for (i = 0; VEC_iterate (tree, *vec_oprnds0, i, vop0); i++)
    {
      if (op_type == binary_op)
        vop1 = VEC_index (tree, *vec_oprnds1, i);
      else
        vop1 = NULL_TREE;

      /* Generate the two halves of promotion operation.  */
      new_stmt1 = vect_gen_widened_results_half (code1, decl1, vop0, vop1,  
                                                 op_type, vec_dest, gsi, stmt);
      new_stmt2 = vect_gen_widened_results_half (code2, decl2, vop0, vop1,
                                                 op_type, vec_dest, gsi, stmt);
      if (is_gimple_call (new_stmt1))
        {
          new_tmp1 = gimple_call_lhs (new_stmt1);
          new_tmp2 = gimple_call_lhs (new_stmt2);
        }
      else
        {
          new_tmp1 = gimple_assign_lhs (new_stmt1);
          new_tmp2 = gimple_assign_lhs (new_stmt2);
        }

      if (multi_step_cvt)
        {
          /* Store the results for the recursive call.  */
          VEC_quick_push (tree, vec_tmp, new_tmp1);
          VEC_quick_push (tree, vec_tmp, new_tmp2);
        }
      else
        {
          /* Last step of promotion sequience - store the results.  */
          if (slp_node)
            {
              VEC_quick_push (gimple, SLP_TREE_VEC_STMTS (slp_node), new_stmt1);
              VEC_quick_push (gimple, SLP_TREE_VEC_STMTS (slp_node), new_stmt2);
            }
          else
            {
              if (!*prev_stmt_info)
                STMT_VINFO_VEC_STMT (stmt_info) = new_stmt1;
              else
                STMT_VINFO_RELATED_STMT (*prev_stmt_info) = new_stmt1;

              *prev_stmt_info = vinfo_for_stmt (new_stmt1);
              STMT_VINFO_RELATED_STMT (*prev_stmt_info) = new_stmt2;
              *prev_stmt_info = vinfo_for_stmt (new_stmt2);
            }
        }
    }

  if (multi_step_cvt)
    {
      /* For multi-step promotion operation we first generate we call the 
         function recurcively for every stage. We start from the input type,
         create promotion operations to the intermediate types, and then
         create promotions to the output type.  */
      *vec_oprnds0 = VEC_copy (tree, heap, vec_tmp);
      VEC_free (tree, heap, vec_tmp);
      vect_create_vectorized_promotion_stmts (vec_oprnds0, vec_oprnds1,
                                              multi_step_cvt - 1, stmt,
                                              vec_dsts, gsi, slp_node, code1,
                                              code2, decl2, decl2, op_type,
                                              prev_stmt_info);
    }
}


/* Function vectorizable_type_promotion

   Check if STMT performs a binary or unary operation that involves
   type promotion, and if it can be vectorized.
   If VEC_STMT is also passed, vectorize the STMT: create a vectorized
   stmt to replace it, put it in VEC_STMT, and insert it at BSI.
   Return FALSE if not a vectorizable STMT, TRUE otherwise.  */

bool
vectorizable_type_promotion (gimple stmt, gimple_stmt_iterator *gsi,
                             gimple *vec_stmt, slp_tree slp_node)
{
  tree vec_dest;
  tree scalar_dest;
  tree op0, op1 = NULL;
  tree vec_oprnd0=NULL, vec_oprnd1=NULL;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  enum tree_code code, code1 = ERROR_MARK, code2 = ERROR_MARK;
  tree decl1 = NULL_TREE, decl2 = NULL_TREE;
  int op_type; 
  tree def;
  gimple def_stmt;
  enum vect_def_type dt[2] = {vect_unknown_def_type, vect_unknown_def_type};
  stmt_vec_info prev_stmt_info;
  int nunits_in;
  int nunits_out;
  tree vectype_out;
  int ncopies;
  int j, i;
  tree vectype_in;
  tree intermediate_type = NULL_TREE;
  int multi_step_cvt = 0;
  VEC (tree, heap) *vec_oprnds0 = NULL, *vec_oprnds1 = NULL;
  VEC (tree, heap) *vec_dsts = NULL, *interm_types = NULL, *tmp_vec_dsts = NULL;
  
  if (!STMT_VINFO_RELEVANT_P (stmt_info))
    return false;

  if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_loop_def)
    return false;

  /* Is STMT a vectorizable type-promotion operation?  */
  if (!is_gimple_assign (stmt))
    return false;

  if (TREE_CODE (gimple_assign_lhs (stmt)) != SSA_NAME)
    return false;

  code = gimple_assign_rhs_code (stmt);
  if (!CONVERT_EXPR_CODE_P (code)
      && code != WIDEN_MULT_EXPR)
    return false;

  op0 = gimple_assign_rhs1 (stmt);
  vectype_in = get_vectype_for_scalar_type (TREE_TYPE (op0));
  if (!vectype_in)
    return false;
  nunits_in = TYPE_VECTOR_SUBPARTS (vectype_in);

  scalar_dest = gimple_assign_lhs (stmt);
  vectype_out = get_vectype_for_scalar_type (TREE_TYPE (scalar_dest));
  if (!vectype_out)
    return false;
  nunits_out = TYPE_VECTOR_SUBPARTS (vectype_out);
  if (nunits_in <= nunits_out)
    return false;

  /* Multiple types in SLP are handled by creating the appropriate number of
     vectorized stmts for each SLP node. Hence, NCOPIES is always 1 in
     case of SLP.  */
  if (slp_node)
    ncopies = 1;
  else
    ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits_in;

  gcc_assert (ncopies >= 1);

  if (! ((INTEGRAL_TYPE_P (TREE_TYPE (scalar_dest))
          && INTEGRAL_TYPE_P (TREE_TYPE (op0)))
         || (SCALAR_FLOAT_TYPE_P (TREE_TYPE (scalar_dest))
             && SCALAR_FLOAT_TYPE_P (TREE_TYPE (op0))
             && CONVERT_EXPR_CODE_P (code))))
    return false;

  /* Check the operands of the operation.  */
  if (!vect_is_simple_use (op0, loop_vinfo, &def_stmt, &def, &dt[0]))
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "use not simple.");
      return false;
    }

  op_type = TREE_CODE_LENGTH (code);
  if (op_type == binary_op)
    {
      op1 = gimple_assign_rhs2 (stmt);
      if (!vect_is_simple_use (op1, loop_vinfo, &def_stmt, &def, &dt[1]))
        {
          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "use not simple.");
          return false;
        }
    }

  /* Supportable by target?  */
  if (!supportable_widening_operation (code, stmt, vectype_in,
                                       &decl1, &decl2, &code1, &code2,
                                       &multi_step_cvt, &interm_types))
    return false;

  /* Binary widening operation can only be supported directly by the
     architecture.  */
  gcc_assert (!(multi_step_cvt && op_type == binary_op));

  STMT_VINFO_VECTYPE (stmt_info) = vectype_in;

  if (!vec_stmt) /* transformation not required.  */
    {
      STMT_VINFO_TYPE (stmt_info) = type_promotion_vec_info_type;
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "=== vectorizable_promotion ===");
      vect_model_simple_cost (stmt_info, 2*ncopies, dt, NULL);
      return true;
    }

  /** Transform.  **/

  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "transform type promotion operation. ncopies = %d.",
                        ncopies);

  /* Handle def.  */
  /* In case of multi-step promotion, we first generate promotion operations 
     to the intermediate types, and then from that types to the final one.
     We store vector destination in VEC_DSTS in the correct order for 
     recursive creation of promotion operations in 
     vect_create_vectorized_promotion_stmts(). Vector destinations are created
     according to TYPES recieved from supportable_widening_operation().   */
  if (multi_step_cvt)
    vec_dsts = VEC_alloc (tree, heap, multi_step_cvt + 1);
  else
    vec_dsts = VEC_alloc (tree, heap, 1);

  vec_dest = vect_create_destination_var (scalar_dest, vectype_out);
  VEC_quick_push (tree, vec_dsts, vec_dest);

  if (multi_step_cvt)
    {
      for (i = VEC_length (tree, interm_types) - 1;
           VEC_iterate (tree, interm_types, i, intermediate_type); i--)
        {
          vec_dest = vect_create_destination_var (scalar_dest,
                                                  intermediate_type);
          VEC_quick_push (tree, vec_dsts, vec_dest);
        }
    }
  
  if (!slp_node)
    {
      vec_oprnds0 = VEC_alloc (tree, heap, 
                            (multi_step_cvt ? vect_pow2 (multi_step_cvt) : 1));
      if (op_type == binary_op)
        vec_oprnds1 = VEC_alloc (tree, heap, 1);
    }

  /* In case the vectorization factor (VF) is bigger than the number
     of elements that we can fit in a vectype (nunits), we have to generate
     more than one vector stmt - i.e - we need to "unroll" the
     vector stmt by a factor VF/nunits.   */

  prev_stmt_info = NULL;
  for (j = 0; j < ncopies; j++)
    {
      /* Handle uses.  */
      if (j == 0)
        {
          if (slp_node)
              vect_get_slp_defs (slp_node, &vec_oprnds0, &vec_oprnds1);
          else
            {
              vec_oprnd0 = vect_get_vec_def_for_operand (op0, stmt, NULL);
              VEC_quick_push (tree, vec_oprnds0, vec_oprnd0);
              if (op_type == binary_op)
                {
                  vec_oprnd1 = vect_get_vec_def_for_operand (op1, stmt, NULL);
                  VEC_quick_push (tree, vec_oprnds1, vec_oprnd1);
                }
            }
        }
      else
        {
          vec_oprnd0 = vect_get_vec_def_for_stmt_copy (dt[0], vec_oprnd0);
          VEC_replace (tree, vec_oprnds0, 0, vec_oprnd0);
          if (op_type == binary_op)
            {
              vec_oprnd1 = vect_get_vec_def_for_stmt_copy (dt[1], vec_oprnd1);
              VEC_replace (tree, vec_oprnds1, 0, vec_oprnd1);
            }
        }

      /* Arguments are ready. Create the new vector stmts.  */
      tmp_vec_dsts = VEC_copy (tree, heap, vec_dsts);
      vect_create_vectorized_promotion_stmts (&vec_oprnds0, &vec_oprnds1,
                                              multi_step_cvt, stmt, 
                                              tmp_vec_dsts,
                                              gsi, slp_node, code1, code2,
                                              decl1, decl2, op_type,
                                              &prev_stmt_info);
    }

  VEC_free (tree, heap, vec_dsts);
  VEC_free (tree, heap, tmp_vec_dsts);
  VEC_free (tree, heap, interm_types);
  VEC_free (tree, heap, vec_oprnds0);
  VEC_free (tree, heap, vec_oprnds1);

  *vec_stmt = STMT_VINFO_VEC_STMT (stmt_info);
  return true;
}


/* Function vect_strided_store_supported.

   Returns TRUE is INTERLEAVE_HIGH and INTERLEAVE_LOW operations are supported,
   and FALSE otherwise.  */

static bool
vect_strided_store_supported (tree vectype)
{
  optab interleave_high_optab, interleave_low_optab;
  int mode;

  mode = (int) TYPE_MODE (vectype);
      
  /* Check that the operation is supported.  */
  interleave_high_optab = optab_for_tree_code (VEC_INTERLEAVE_HIGH_EXPR, 
                                               vectype, optab_default);
  interleave_low_optab = optab_for_tree_code (VEC_INTERLEAVE_LOW_EXPR, 
                                              vectype, optab_default);
  if (!interleave_high_optab || !interleave_low_optab)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "no optab for interleave.");
      return false;
    }

  if (optab_handler (interleave_high_optab, mode)->insn_code 
      == CODE_FOR_nothing
      || optab_handler (interleave_low_optab, mode)->insn_code 
      == CODE_FOR_nothing)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "interleave op not supported by target.");
      return false;
    }

  return true;
}


/* Function vect_permute_store_chain.

   Given a chain of interleaved stores in DR_CHAIN of LENGTH that must be
   a power of 2, generate interleave_high/low stmts to reorder the data 
   correctly for the stores. Return the final references for stores in
   RESULT_CHAIN.

   E.g., LENGTH is 4 and the scalar type is short, i.e., VF is 8.
   The input is 4 vectors each containing 8 elements. We assign a number to each
   element, the input sequence is:

   1st vec:   0  1  2  3  4  5  6  7
   2nd vec:   8  9 10 11 12 13 14 15
   3rd vec:  16 17 18 19 20 21 22 23 
   4th vec:  24 25 26 27 28 29 30 31

   The output sequence should be:

   1st vec:  0  8 16 24  1  9 17 25
   2nd vec:  2 10 18 26  3 11 19 27
   3rd vec:  4 12 20 28  5 13 21 30
   4th vec:  6 14 22 30  7 15 23 31

   i.e., we interleave the contents of the four vectors in their order.

   We use interleave_high/low instructions to create such output. The input of 
   each interleave_high/low operation is two vectors:
   1st vec    2nd vec 
   0 1 2 3    4 5 6 7 
   the even elements of the result vector are obtained left-to-right from the 
   high/low elements of the first vector. The odd elements of the result are 
   obtained left-to-right from the high/low elements of the second vector.
   The output of interleave_high will be:   0 4 1 5
   and of interleave_low:                   2 6 3 7

   
   The permutation is done in log LENGTH stages. In each stage interleave_high
   and interleave_low stmts are created for each pair of vectors in DR_CHAIN, 
   where the first argument is taken from the first half of DR_CHAIN and the 
   second argument from it's second half. 
   In our example, 

   I1: interleave_high (1st vec, 3rd vec)
   I2: interleave_low (1st vec, 3rd vec)
   I3: interleave_high (2nd vec, 4th vec)
   I4: interleave_low (2nd vec, 4th vec)

   The output for the first stage is:

   I1:  0 16  1 17  2 18  3 19
   I2:  4 20  5 21  6 22  7 23
   I3:  8 24  9 25 10 26 11 27
   I4: 12 28 13 29 14 30 15 31

   The output of the second stage, i.e. the final result is:

   I1:  0  8 16 24  1  9 17 25
   I2:  2 10 18 26  3 11 19 27
   I3:  4 12 20 28  5 13 21 30
   I4:  6 14 22 30  7 15 23 31.  */
 
static bool
vect_permute_store_chain (VEC(tree,heap) *dr_chain, 
                          unsigned int length, 
                          gimple stmt,
                          gimple_stmt_iterator *gsi,
                          VEC(tree,heap) **result_chain)
{
  tree perm_dest, vect1, vect2, high, low;
  gimple perm_stmt;
  tree vectype = STMT_VINFO_VECTYPE (vinfo_for_stmt (stmt));
  tree scalar_dest;
  int i;
  unsigned int j;
  enum tree_code high_code, low_code;
  
  scalar_dest = gimple_assign_lhs (stmt);

  /* Check that the operation is supported.  */
  if (!vect_strided_store_supported (vectype))
    return false;

  *result_chain = VEC_copy (tree, heap, dr_chain);

  for (i = 0; i < exact_log2 (length); i++)
    {
      for (j = 0; j < length/2; j++)
        {
          vect1 = VEC_index (tree, dr_chain, j);
          vect2 = VEC_index (tree, dr_chain, j+length/2);

          /* Create interleaving stmt:
             in the case of big endian: 
                                high = interleave_high (vect1, vect2) 
             and in the case of little endian: 
                                high = interleave_low (vect1, vect2).  */
          perm_dest = create_tmp_var (vectype, "vect_inter_high");
          DECL_GIMPLE_REG_P (perm_dest) = 1;
          add_referenced_var (perm_dest);
          if (BYTES_BIG_ENDIAN)
            {
              high_code = VEC_INTERLEAVE_HIGH_EXPR;
              low_code = VEC_INTERLEAVE_LOW_EXPR;
            }
          else
            {
              low_code = VEC_INTERLEAVE_HIGH_EXPR;
              high_code = VEC_INTERLEAVE_LOW_EXPR;
            }
          perm_stmt = gimple_build_assign_with_ops (high_code, perm_dest,
                                                    vect1, vect2);
          high = make_ssa_name (perm_dest, perm_stmt);
          gimple_assign_set_lhs (perm_stmt, high);
          vect_finish_stmt_generation (stmt, perm_stmt, gsi);
          VEC_replace (tree, *result_chain, 2*j, high);

          /* Create interleaving stmt:
             in the case of big endian:
                               low  = interleave_low (vect1, vect2) 
             and in the case of little endian:
                               low  = interleave_high (vect1, vect2).  */     
          perm_dest = create_tmp_var (vectype, "vect_inter_low");
          DECL_GIMPLE_REG_P (perm_dest) = 1;
          add_referenced_var (perm_dest);
          perm_stmt = gimple_build_assign_with_ops (low_code, perm_dest,
                                                    vect1, vect2);
          low = make_ssa_name (perm_dest, perm_stmt);
          gimple_assign_set_lhs (perm_stmt, low);
          vect_finish_stmt_generation (stmt, perm_stmt, gsi);
          VEC_replace (tree, *result_chain, 2*j+1, low);
        }
      dr_chain = VEC_copy (tree, heap, *result_chain);
    }
  return true;
}


/* Function vectorizable_store.

   Check if STMT defines a non scalar data-ref (array/pointer/structure) that 
   can be vectorized. 
   If VEC_STMT is also passed, vectorize the STMT: create a vectorized 
   stmt to replace it, put it in VEC_STMT, and insert it at BSI.
   Return FALSE if not a vectorizable STMT, TRUE otherwise.  */

bool
vectorizable_store (gimple stmt, gimple_stmt_iterator *gsi, gimple *vec_stmt,
                    slp_tree slp_node)
{
  tree scalar_dest;
  tree data_ref;
  tree op;
  tree vec_oprnd = NULL_TREE;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  struct data_reference *dr = STMT_VINFO_DATA_REF (stmt_info), *first_dr = NULL;
  tree vectype = STMT_VINFO_VECTYPE (stmt_info);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  enum machine_mode vec_mode;
  tree dummy;
  enum dr_alignment_support alignment_support_scheme;
  tree def;
  gimple def_stmt;
  enum vect_def_type dt;
  stmt_vec_info prev_stmt_info = NULL;
  tree dataref_ptr = NULL_TREE;
  int nunits = TYPE_VECTOR_SUBPARTS (vectype);
  int ncopies;
  int j;
  gimple next_stmt, first_stmt = NULL;
  bool strided_store = false;
  unsigned int group_size, i;
  VEC(tree,heap) *dr_chain = NULL, *oprnds = NULL, *result_chain = NULL;
  bool inv_p;
  VEC(tree,heap) *vec_oprnds = NULL;
  bool slp = (slp_node != NULL);
  stmt_vec_info first_stmt_vinfo;
  unsigned int vec_num;

  /* Multiple types in SLP are handled by creating the appropriate number of
     vectorized stmts for each SLP node. Hence, NCOPIES is always 1 in
     case of SLP.  */
  if (slp)
    ncopies = 1;
  else
    ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits;

  gcc_assert (ncopies >= 1);

  /* FORNOW. This restriction should be relaxed.  */
  if (nested_in_vect_loop_p (loop, stmt) && ncopies > 1)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "multiple types in nested loop.");
      return false;
    }

  if (!STMT_VINFO_RELEVANT_P (stmt_info))
    return false;

  if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_loop_def)
    return false;

  /* Is vectorizable store? */

  if (!is_gimple_assign (stmt))
    return false;

  scalar_dest = gimple_assign_lhs (stmt);
  if (TREE_CODE (scalar_dest) != ARRAY_REF
      && TREE_CODE (scalar_dest) != INDIRECT_REF
      && !STMT_VINFO_STRIDED_ACCESS (stmt_info))
    return false;

  gcc_assert (gimple_assign_single_p (stmt));
  op = gimple_assign_rhs1 (stmt);
  if (!vect_is_simple_use (op, loop_vinfo, &def_stmt, &def, &dt))
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "use not simple.");
      return false;
    }

  /* The scalar rhs type needs to be trivially convertible to the vector
     component type.  This should always be the case.  */
  if (!useless_type_conversion_p (TREE_TYPE (vectype), TREE_TYPE (op)))
    {      
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "???  operands of different types");
      return false;
    }

  vec_mode = TYPE_MODE (vectype);
  /* FORNOW. In some cases can vectorize even if data-type not supported
     (e.g. - array initialization with 0).  */
  if (optab_handler (mov_optab, (int)vec_mode)->insn_code == CODE_FOR_nothing)
    return false;

  if (!STMT_VINFO_DATA_REF (stmt_info))
    return false;

  if (STMT_VINFO_STRIDED_ACCESS (stmt_info))
    {
      strided_store = true;
      first_stmt = DR_GROUP_FIRST_DR (stmt_info);
      if (!vect_strided_store_supported (vectype)
          && !PURE_SLP_STMT (stmt_info) && !slp)
        return false;
     
      if (first_stmt == stmt)
        {
          /* STMT is the leader of the group. Check the operands of all the
             stmts of the group.  */
          next_stmt = DR_GROUP_NEXT_DR (stmt_info);
          while (next_stmt)
            {
              gcc_assert (gimple_assign_single_p (next_stmt));
              op = gimple_assign_rhs1 (next_stmt);
              if (!vect_is_simple_use (op, loop_vinfo, &def_stmt, &def, &dt))
                {
                  if (vect_print_dump_info (REPORT_DETAILS))
                    fprintf (vect_dump, "use not simple.");
                  return false;
                }
              next_stmt = DR_GROUP_NEXT_DR (vinfo_for_stmt (next_stmt));
            }
        }
    }

  if (!vec_stmt) /* transformation not required.  */
    {
      STMT_VINFO_TYPE (stmt_info) = store_vec_info_type;
      vect_model_store_cost (stmt_info, ncopies, dt, NULL);
      return true;
    }

  /** Transform.  **/

  if (strided_store)
    {
      first_dr = STMT_VINFO_DATA_REF (vinfo_for_stmt (first_stmt));
      group_size = DR_GROUP_SIZE (vinfo_for_stmt (first_stmt));

      DR_GROUP_STORE_COUNT (vinfo_for_stmt (first_stmt))++;

      /* FORNOW */
      gcc_assert (!nested_in_vect_loop_p (loop, stmt));

      /* We vectorize all the stmts of the interleaving group when we
         reach the last stmt in the group.  */
      if (DR_GROUP_STORE_COUNT (vinfo_for_stmt (first_stmt)) 
          < DR_GROUP_SIZE (vinfo_for_stmt (first_stmt))
          && !slp)
        {
          *vec_stmt = NULL;
          return true;
        }

      if (slp)
        strided_store = false;

      /* VEC_NUM is the number of vect stmts to be created for this group.  */
      if (slp)
        vec_num = SLP_TREE_NUMBER_OF_VEC_STMTS (slp_node);
      else
        vec_num = group_size;
    }
  else 
    {
      first_stmt = stmt;
      first_dr = dr;
      group_size = vec_num = 1;
      first_stmt_vinfo = stmt_info;
    }
  
  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "transform store. ncopies = %d",ncopies);

  dr_chain = VEC_alloc (tree, heap, group_size);
  oprnds = VEC_alloc (tree, heap, group_size);

  alignment_support_scheme = vect_supportable_dr_alignment (first_dr);
  gcc_assert (alignment_support_scheme);
  gcc_assert (alignment_support_scheme == dr_aligned);  /* FORNOW */

  /* In case the vectorization factor (VF) is bigger than the number
     of elements that we can fit in a vectype (nunits), we have to generate
     more than one vector stmt - i.e - we need to "unroll" the
     vector stmt by a factor VF/nunits.  For more details see documentation in 
     vect_get_vec_def_for_copy_stmt.  */

  /* In case of interleaving (non-unit strided access):

        S1:  &base + 2 = x2
        S2:  &base = x0
        S3:  &base + 1 = x1
        S4:  &base + 3 = x3

     We create vectorized stores starting from base address (the access of the
     first stmt in the chain (S2 in the above example), when the last store stmt
     of the chain (S4) is reached:

        VS1: &base = vx2
        VS2: &base + vec_size*1 = vx0
        VS3: &base + vec_size*2 = vx1
        VS4: &base + vec_size*3 = vx3

     Then permutation statements are generated:

        VS5: vx5 = VEC_INTERLEAVE_HIGH_EXPR < vx0, vx3 >
        VS6: vx6 = VEC_INTERLEAVE_LOW_EXPR < vx0, vx3 >
        ...
        
     And they are put in STMT_VINFO_VEC_STMT of the corresponding scalar stmts
     (the order of the data-refs in the output of vect_permute_store_chain
     corresponds to the order of scalar stmts in the interleaving chain - see
     the documentation of vect_permute_store_chain()).

     In case of both multiple types and interleaving, above vector stores and
     permutation stmts are created for every copy. The result vector stmts are
     put in STMT_VINFO_VEC_STMT for the first copy and in the corresponding
     STMT_VINFO_RELATED_STMT for the next copies.     
  */

  prev_stmt_info = NULL;
  for (j = 0; j < ncopies; j++)
    {
      gimple new_stmt;
      gimple ptr_incr;

      if (j == 0)
        {
          if (slp)
            {
              /* Get vectorized arguments for SLP_NODE.  */
              vect_get_slp_defs (slp_node, &vec_oprnds, NULL);

              vec_oprnd = VEC_index (tree, vec_oprnds, 0);
            }
          else
            {
              /* For interleaved stores we collect vectorized defs for all the 
                 stores in the group in DR_CHAIN and OPRNDS. DR_CHAIN is then 
                 used as an input to vect_permute_store_chain(), and OPRNDS as 
                 an input to vect_get_vec_def_for_stmt_copy() for the next copy.

                 If the store is not strided, GROUP_SIZE is 1, and DR_CHAIN and
                 OPRNDS are of size 1.  */
              next_stmt = first_stmt;     
              for (i = 0; i < group_size; i++)
                {
                  /* Since gaps are not supported for interleaved stores, 
                     GROUP_SIZE is the exact number of stmts in the chain. 
                     Therefore, NEXT_STMT can't be NULL_TREE.  In case that 
                     there is no interleaving, GROUP_SIZE is 1, and only one 
                     iteration of the loop will be executed.  */
                  gcc_assert (next_stmt
                              && gimple_assign_single_p (next_stmt));
                  op = gimple_assign_rhs1 (next_stmt);

                  vec_oprnd = vect_get_vec_def_for_operand (op, next_stmt, 
                                                            NULL);
                  VEC_quick_push(tree, dr_chain, vec_oprnd); 
                  VEC_quick_push(tree, oprnds, vec_oprnd); 
                  next_stmt = DR_GROUP_NEXT_DR (vinfo_for_stmt (next_stmt));
                }
            }

          /* We should have catched mismatched types earlier.  */
          gcc_assert (useless_type_conversion_p (vectype,
                                                 TREE_TYPE (vec_oprnd)));
          dataref_ptr = vect_create_data_ref_ptr (first_stmt, NULL, NULL_TREE, 
                                                  &dummy, &ptr_incr, false, 
                                                  &inv_p, NULL);
          gcc_assert (!inv_p);
        }
      else 
        {
          /* For interleaved stores we created vectorized defs for all the 
             defs stored in OPRNDS in the previous iteration (previous copy). 
             DR_CHAIN is then used as an input to vect_permute_store_chain(), 
             and OPRNDS as an input to vect_get_vec_def_for_stmt_copy() for the
             next copy.
             If the store is not strided, GROUP_SIZE is 1, and DR_CHAIN and
             OPRNDS are of size 1.  */
          for (i = 0; i < group_size; i++)
            {
              op = VEC_index (tree, oprnds, i);
              vect_is_simple_use (op, loop_vinfo, &def_stmt, &def, &dt);
              vec_oprnd = vect_get_vec_def_for_stmt_copy (dt, op); 
              VEC_replace(tree, dr_chain, i, vec_oprnd);
              VEC_replace(tree, oprnds, i, vec_oprnd);
            }
          dataref_ptr = 
                bump_vector_ptr (dataref_ptr, ptr_incr, gsi, stmt, NULL_TREE);
        }

      if (strided_store)
        {
          result_chain = VEC_alloc (tree, heap, group_size);     
          /* Permute.  */
          if (!vect_permute_store_chain (dr_chain, group_size, stmt, gsi,
                                         &result_chain))
            return false;
        }

      next_stmt = first_stmt;
      for (i = 0; i < vec_num; i++)
        {
          if (i > 0)
            /* Bump the vector pointer.  */
            dataref_ptr = bump_vector_ptr (dataref_ptr, ptr_incr, gsi, stmt,
                                           NULL_TREE);

          if (slp)
            vec_oprnd = VEC_index (tree, vec_oprnds, i);
          else if (strided_store)
            /* For strided stores vectorized defs are interleaved in 
               vect_permute_store_chain().  */
            vec_oprnd = VEC_index (tree, result_chain, i);

          data_ref = build_fold_indirect_ref (dataref_ptr);

          /* Arguments are ready. Create the new vector stmt.  */
          new_stmt = gimple_build_assign (data_ref, vec_oprnd);
          vect_finish_stmt_generation (stmt, new_stmt, gsi);
          mark_symbols_for_renaming (new_stmt);

          if (slp)
            continue;
          
          if (j == 0)
            STMT_VINFO_VEC_STMT (stmt_info) = *vec_stmt =  new_stmt;
          else
            STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;

          prev_stmt_info = vinfo_for_stmt (new_stmt);
          next_stmt = DR_GROUP_NEXT_DR (vinfo_for_stmt (next_stmt));
          if (!next_stmt)
            break;
        }
    }

  VEC_free (tree, heap, dr_chain);  
  VEC_free (tree, heap, oprnds);  
  if (result_chain)
    VEC_free (tree, heap, result_chain);  

  return true;
}


/* Function vect_setup_realignment
  
   This function is called when vectorizing an unaligned load using
   the dr_explicit_realign[_optimized] scheme.
   This function generates the following code at the loop prolog:

      p = initial_addr;
   x  msq_init = *(floor(p));   # prolog load
      realignment_token = call target_builtin; 
    loop:
   x  msq = phi (msq_init, ---)

   The stmts marked with x are generated only for the case of 
   dr_explicit_realign_optimized.

   The code above sets up a new (vector) pointer, pointing to the first 
   location accessed by STMT, and a "floor-aligned" load using that pointer.
   It also generates code to compute the "realignment-token" (if the relevant
   target hook was defined), and creates a phi-node at the loop-header bb
   whose arguments are the result of the prolog-load (created by this
   function) and the result of a load that takes place in the loop (to be
   created by the caller to this function).

   For the case of dr_explicit_realign_optimized:
   The caller to this function uses the phi-result (msq) to create the 
   realignment code inside the loop, and sets up the missing phi argument,
   as follows:
    loop: 
      msq = phi (msq_init, lsq)
      lsq = *(floor(p'));        # load in loop
      result = realign_load (msq, lsq, realignment_token);

   For the case of dr_explicit_realign:
    loop:
      msq = *(floor(p));        # load in loop
      p' = p + (VS-1);
      lsq = *(floor(p'));       # load in loop
      result = realign_load (msq, lsq, realignment_token);

   Input:
   STMT - (scalar) load stmt to be vectorized. This load accesses
          a memory location that may be unaligned.
   BSI - place where new code is to be inserted.
   ALIGNMENT_SUPPORT_SCHEME - which of the two misalignment handling schemes
                              is used.  
   
   Output:
   REALIGNMENT_TOKEN - the result of a call to the builtin_mask_for_load
                       target hook, if defined.
   Return value - the result of the loop-header phi node.  */

static tree
vect_setup_realignment (gimple stmt, gimple_stmt_iterator *gsi,
                        tree *realignment_token,
                        enum dr_alignment_support alignment_support_scheme,
                        tree init_addr,
                        struct loop **at_loop)
{
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  tree vectype = STMT_VINFO_VECTYPE (stmt_info);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  edge pe;
  tree scalar_dest = gimple_assign_lhs (stmt);
  tree vec_dest;
  gimple inc;
  tree ptr;
  tree data_ref;
  gimple new_stmt;
  basic_block new_bb;
  tree msq_init = NULL_TREE;
  tree new_temp;
  gimple phi_stmt;
  tree msq = NULL_TREE;
  gimple_seq stmts = NULL;
  bool inv_p;
  bool compute_in_loop = false;
  bool nested_in_vect_loop = nested_in_vect_loop_p (loop, stmt);
  struct loop *containing_loop = (gimple_bb (stmt))->loop_father;
  struct loop *loop_for_initial_load;

  gcc_assert (alignment_support_scheme == dr_explicit_realign
              || alignment_support_scheme == dr_explicit_realign_optimized);

  /* We need to generate three things:
     1. the misalignment computation
     2. the extra vector load (for the optimized realignment scheme).
     3. the phi node for the two vectors from which the realignment is
      done (for the optimized realignment scheme).
   */

  /* 1. Determine where to generate the misalignment computation.

     If INIT_ADDR is NULL_TREE, this indicates that the misalignment
     calculation will be generated by this function, outside the loop (in the
     preheader).  Otherwise, INIT_ADDR had already been computed for us by the
     caller, inside the loop.

     Background: If the misalignment remains fixed throughout the iterations of
     the loop, then both realignment schemes are applicable, and also the
     misalignment computation can be done outside LOOP.  This is because we are
     vectorizing LOOP, and so the memory accesses in LOOP advance in steps that
     are a multiple of VS (the Vector Size), and therefore the misalignment in
     different vectorized LOOP iterations is always the same.
     The problem arises only if the memory access is in an inner-loop nested
     inside LOOP, which is now being vectorized using outer-loop vectorization.
     This is the only case when the misalignment of the memory access may not
     remain fixed throughout the iterations of the inner-loop (as explained in
     detail in vect_supportable_dr_alignment).  In this case, not only is the
     optimized realignment scheme not applicable, but also the misalignment
     computation (and generation of the realignment token that is passed to
     REALIGN_LOAD) have to be done inside the loop.

     In short, INIT_ADDR indicates whether we are in a COMPUTE_IN_LOOP mode
     or not, which in turn determines if the misalignment is computed inside
     the inner-loop, or outside LOOP.  */

  if (init_addr != NULL_TREE)
    {
      compute_in_loop = true;
      gcc_assert (alignment_support_scheme == dr_explicit_realign);
    }


  /* 2. Determine where to generate the extra vector load.

     For the optimized realignment scheme, instead of generating two vector
     loads in each iteration, we generate a single extra vector load in the
     preheader of the loop, and in each iteration reuse the result of the
     vector load from the previous iteration.  In case the memory access is in
     an inner-loop nested inside LOOP, which is now being vectorized using
     outer-loop vectorization, we need to determine whether this initial vector
     load should be generated at the preheader of the inner-loop, or can be
     generated at the preheader of LOOP.  If the memory access has no evolution
     in LOOP, it can be generated in the preheader of LOOP. Otherwise, it has
     to be generated inside LOOP (in the preheader of the inner-loop).  */

  if (nested_in_vect_loop)
    {
      tree outerloop_step = STMT_VINFO_DR_STEP (stmt_info);
      bool invariant_in_outerloop =
            (tree_int_cst_compare (outerloop_step, size_zero_node) == 0);
      loop_for_initial_load = (invariant_in_outerloop ? loop : loop->inner);
    }
  else
    loop_for_initial_load = loop;
  if (at_loop)
    *at_loop = loop_for_initial_load;

  /* 3. For the case of the optimized realignment, create the first vector
      load at the loop preheader.  */

  if (alignment_support_scheme == dr_explicit_realign_optimized)
    {
      /* Create msq_init = *(floor(p1)) in the loop preheader  */

      gcc_assert (!compute_in_loop);
      pe = loop_preheader_edge (loop_for_initial_load);
      vec_dest = vect_create_destination_var (scalar_dest, vectype);
      ptr = vect_create_data_ref_ptr (stmt, loop_for_initial_load, NULL_TREE,
                                  &init_addr, &inc, true, &inv_p, NULL_TREE);
      data_ref = build1 (ALIGN_INDIRECT_REF, vectype, ptr);
      new_stmt = gimple_build_assign (vec_dest, data_ref);
      new_temp = make_ssa_name (vec_dest, new_stmt);
      gimple_assign_set_lhs (new_stmt, new_temp);
      mark_symbols_for_renaming (new_stmt);
      new_bb = gsi_insert_on_edge_immediate (pe, new_stmt);
      gcc_assert (!new_bb);
      msq_init = gimple_assign_lhs (new_stmt);
    }

  /* 4. Create realignment token using a target builtin, if available.
      It is done either inside the containing loop, or before LOOP (as
      determined above).  */

  if (targetm.vectorize.builtin_mask_for_load)
    {
      tree builtin_decl;

      /* Compute INIT_ADDR - the initial addressed accessed by this memref.  */
      if (compute_in_loop)
        gcc_assert (init_addr); /* already computed by the caller.  */
      else
        {
          /* Generate the INIT_ADDR computation outside LOOP.  */
          init_addr = vect_create_addr_base_for_vector_ref (stmt, &stmts,
                                                        NULL_TREE, loop);
          pe = loop_preheader_edge (loop);
          new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts);
          gcc_assert (!new_bb);
        }

      builtin_decl = targetm.vectorize.builtin_mask_for_load ();
      new_stmt = gimple_build_call (builtin_decl, 1, init_addr);
      vec_dest =
        vect_create_destination_var (scalar_dest,
                                     gimple_call_return_type (new_stmt));
      new_temp = make_ssa_name (vec_dest, new_stmt);
      gimple_call_set_lhs (new_stmt, new_temp);

      if (compute_in_loop)
        gsi_insert_before (gsi, new_stmt, GSI_SAME_STMT);
      else
        {
          /* Generate the misalignment computation outside LOOP.  */
          pe = loop_preheader_edge (loop);
          new_bb = gsi_insert_on_edge_immediate (pe, new_stmt);
          gcc_assert (!new_bb);
        }

      *realignment_token = gimple_call_lhs (new_stmt);

      /* The result of the CALL_EXPR to this builtin is determined from
         the value of the parameter and no global variables are touched
         which makes the builtin a "const" function.  Requiring the
         builtin to have the "const" attribute makes it unnecessary
         to call mark_call_clobbered.  */
      gcc_assert (TREE_READONLY (builtin_decl));
    }

  if (alignment_support_scheme == dr_explicit_realign)
    return msq;

  gcc_assert (!compute_in_loop);
  gcc_assert (alignment_support_scheme == dr_explicit_realign_optimized);


  /* 5. Create msq = phi <msq_init, lsq> in loop  */

  pe = loop_preheader_edge (containing_loop);
  vec_dest = vect_create_destination_var (scalar_dest, vectype);
  msq = make_ssa_name (vec_dest, NULL);
  phi_stmt = create_phi_node (msq, containing_loop->header);
  SSA_NAME_DEF_STMT (msq) = phi_stmt;
  add_phi_arg (phi_stmt, msq_init, pe);

  return msq;
}


/* Function vect_strided_load_supported.

   Returns TRUE is EXTRACT_EVEN and EXTRACT_ODD operations are supported,
   and FALSE otherwise.  */

static bool
vect_strided_load_supported (tree vectype)
{
  optab perm_even_optab, perm_odd_optab;
  int mode;

  mode = (int) TYPE_MODE (vectype);

  perm_even_optab = optab_for_tree_code (VEC_EXTRACT_EVEN_EXPR, vectype,
                                         optab_default);
  if (!perm_even_optab)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "no optab for perm_even.");
      return false;
    }

  if (optab_handler (perm_even_optab, mode)->insn_code == CODE_FOR_nothing)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "perm_even op not supported by target.");
      return false;
    }

  perm_odd_optab = optab_for_tree_code (VEC_EXTRACT_ODD_EXPR, vectype,
                                        optab_default);
  if (!perm_odd_optab)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "no optab for perm_odd.");
      return false;
    }

  if (optab_handler (perm_odd_optab, mode)->insn_code == CODE_FOR_nothing)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "perm_odd op not supported by target.");
      return false;
    }
  return true;
}


/* Function vect_permute_load_chain.

   Given a chain of interleaved loads in DR_CHAIN of LENGTH that must be
   a power of 2, generate extract_even/odd stmts to reorder the input data 
   correctly. Return the final references for loads in RESULT_CHAIN.

   E.g., LENGTH is 4 and the scalar type is short, i.e., VF is 8.
   The input is 4 vectors each containing 8 elements. We assign a number to each
   element, the input sequence is:

   1st vec:   0  1  2  3  4  5  6  7
   2nd vec:   8  9 10 11 12 13 14 15
   3rd vec:  16 17 18 19 20 21 22 23 
   4th vec:  24 25 26 27 28 29 30 31

   The output sequence should be:

   1st vec:  0 4  8 12 16 20 24 28
   2nd vec:  1 5  9 13 17 21 25 29
   3rd vec:  2 6 10 14 18 22 26 30 
   4th vec:  3 7 11 15 19 23 27 31

   i.e., the first output vector should contain the first elements of each
   interleaving group, etc.

   We use extract_even/odd instructions to create such output. The input of each
   extract_even/odd operation is two vectors
   1st vec    2nd vec 
   0 1 2 3    4 5 6 7 

   and the output is the vector of extracted even/odd elements. The output of 
   extract_even will be:   0 2 4 6
   and of extract_odd:     1 3 5 7

   
   The permutation is done in log LENGTH stages. In each stage extract_even and
   extract_odd stmts are created for each pair of vectors in DR_CHAIN in their 
   order. In our example, 

   E1: extract_even (1st vec, 2nd vec)
   E2: extract_odd (1st vec, 2nd vec)
   E3: extract_even (3rd vec, 4th vec)
   E4: extract_odd (3rd vec, 4th vec)

   The output for the first stage will be:

   E1:  0  2  4  6  8 10 12 14
   E2:  1  3  5  7  9 11 13 15
   E3: 16 18 20 22 24 26 28 30 
   E4: 17 19 21 23 25 27 29 31

   In order to proceed and create the correct sequence for the next stage (or
   for the correct output, if the second stage is the last one, as in our 
   example), we first put the output of extract_even operation and then the 
   output of extract_odd in RESULT_CHAIN (which is then copied to DR_CHAIN).
   The input for the second stage is:

   1st vec (E1):  0  2  4  6  8 10 12 14
   2nd vec (E3): 16 18 20 22 24 26 28 30  
   3rd vec (E2):  1  3  5  7  9 11 13 15    
   4th vec (E4): 17 19 21 23 25 27 29 31

   The output of the second stage:

   E1: 0 4  8 12 16 20 24 28
   E2: 2 6 10 14 18 22 26 30
   E3: 1 5  9 13 17 21 25 29
   E4: 3 7 11 15 19 23 27 31

   And RESULT_CHAIN after reordering:

   1st vec (E1):  0 4  8 12 16 20 24 28
   2nd vec (E3):  1 5  9 13 17 21 25 29
   3rd vec (E2):  2 6 10 14 18 22 26 30 
   4th vec (E4):  3 7 11 15 19 23 27 31.  */

static bool
vect_permute_load_chain (VEC(tree,heap) *dr_chain, 
                         unsigned int length, 
                         gimple stmt,
                         gimple_stmt_iterator *gsi,
                         VEC(tree,heap) **result_chain)
{
  tree perm_dest, data_ref, first_vect, second_vect;
  gimple perm_stmt;
  tree vectype = STMT_VINFO_VECTYPE (vinfo_for_stmt (stmt));
  int i;
  unsigned int j;

  /* Check that the operation is supported.  */
  if (!vect_strided_load_supported (vectype))
    return false;

  *result_chain = VEC_copy (tree, heap, dr_chain);
  for (i = 0; i < exact_log2 (length); i++)
    {
      for (j = 0; j < length; j +=2)
        {
          first_vect = VEC_index (tree, dr_chain, j);
          second_vect = VEC_index (tree, dr_chain, j+1);

          /* data_ref = permute_even (first_data_ref, second_data_ref);  */
          perm_dest = create_tmp_var (vectype, "vect_perm_even");
          DECL_GIMPLE_REG_P (perm_dest) = 1;
          add_referenced_var (perm_dest);

          perm_stmt = gimple_build_assign_with_ops (VEC_EXTRACT_EVEN_EXPR,
                                                    perm_dest, first_vect,
                                                    second_vect);

          data_ref = make_ssa_name (perm_dest, perm_stmt);
          gimple_assign_set_lhs (perm_stmt, data_ref);
          vect_finish_stmt_generation (stmt, perm_stmt, gsi);
          mark_symbols_for_renaming (perm_stmt);

          VEC_replace (tree, *result_chain, j/2, data_ref);           
              
          /* data_ref = permute_odd (first_data_ref, second_data_ref);  */
          perm_dest = create_tmp_var (vectype, "vect_perm_odd");
          DECL_GIMPLE_REG_P (perm_dest) = 1;
          add_referenced_var (perm_dest);

          perm_stmt = gimple_build_assign_with_ops (VEC_EXTRACT_ODD_EXPR,
                                                    perm_dest, first_vect,
                                                    second_vect);
          data_ref = make_ssa_name (perm_dest, perm_stmt);
          gimple_assign_set_lhs (perm_stmt, data_ref);
          vect_finish_stmt_generation (stmt, perm_stmt, gsi);
          mark_symbols_for_renaming (perm_stmt);

          VEC_replace (tree, *result_chain, j/2+length/2, data_ref);
        }
      dr_chain = VEC_copy (tree, heap, *result_chain);
    }
  return true;
}


/* Function vect_transform_strided_load.

   Given a chain of input interleaved data-refs (in DR_CHAIN), build statements
   to perform their permutation and ascribe the result vectorized statements to
   the scalar statements.
*/

static bool
vect_transform_strided_load (gimple stmt, VEC(tree,heap) *dr_chain, int size,
                             gimple_stmt_iterator *gsi)
{
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  gimple first_stmt = DR_GROUP_FIRST_DR (stmt_info);
  gimple next_stmt, new_stmt;
  VEC(tree,heap) *result_chain = NULL;
  unsigned int i, gap_count;
  tree tmp_data_ref;

  /* DR_CHAIN contains input data-refs that are a part of the interleaving. 
     RESULT_CHAIN is the output of vect_permute_load_chain, it contains permuted 
     vectors, that are ready for vector computation.  */
  result_chain = VEC_alloc (tree, heap, size);
  /* Permute.  */
  if (!vect_permute_load_chain (dr_chain, size, stmt, gsi, &result_chain))
    return false;

  /* Put a permuted data-ref in the VECTORIZED_STMT field.  
     Since we scan the chain starting from it's first node, their order 
     corresponds the order of data-refs in RESULT_CHAIN.  */
  next_stmt = first_stmt;
  gap_count = 1;
  for (i = 0; VEC_iterate (tree, result_chain, i, tmp_data_ref); i++)
    {
      if (!next_stmt)
        break;

      /* Skip the gaps. Loads created for the gaps will be removed by dead
       code elimination pass later. No need to check for the first stmt in
       the group, since it always exists.
       DR_GROUP_GAP is the number of steps in elements from the previous
       access (if there is no gap DR_GROUP_GAP is 1). We skip loads that
       correspond to the gaps.
      */
      if (next_stmt != first_stmt 
          && gap_count < DR_GROUP_GAP (vinfo_for_stmt (next_stmt)))
      {
        gap_count++;
        continue;
      }

      while (next_stmt)
        {
          new_stmt = SSA_NAME_DEF_STMT (tmp_data_ref);
          /* We assume that if VEC_STMT is not NULL, this is a case of multiple
             copies, and we put the new vector statement in the first available
             RELATED_STMT.  */
          if (!STMT_VINFO_VEC_STMT (vinfo_for_stmt (next_stmt)))
            STMT_VINFO_VEC_STMT (vinfo_for_stmt (next_stmt)) = new_stmt;
          else
            {
              if (!DR_GROUP_SAME_DR_STMT (vinfo_for_stmt (next_stmt)))
                {
                  gimple prev_stmt =
                    STMT_VINFO_VEC_STMT (vinfo_for_stmt (next_stmt));
                  gimple rel_stmt =
                    STMT_VINFO_RELATED_STMT (vinfo_for_stmt (prev_stmt));
                  while (rel_stmt)
                    {
                      prev_stmt = rel_stmt;
                      rel_stmt = 
                        STMT_VINFO_RELATED_STMT (vinfo_for_stmt (rel_stmt));
                    }

                  STMT_VINFO_RELATED_STMT (vinfo_for_stmt (prev_stmt)) = 
                    new_stmt;
                }
            }

          next_stmt = DR_GROUP_NEXT_DR (vinfo_for_stmt (next_stmt));
          gap_count = 1;
          /* If NEXT_STMT accesses the same DR as the previous statement,
             put the same TMP_DATA_REF as its vectorized statement; otherwise
             get the next data-ref from RESULT_CHAIN.  */
          if (!next_stmt || !DR_GROUP_SAME_DR_STMT (vinfo_for_stmt (next_stmt)))
            break;
        }
    }

  VEC_free (tree, heap, result_chain);
  return true;
}


/* Create NCOPIES permutation statements using the mask MASK_BYTES (by 
   building a vector of type MASK_TYPE from it) and two input vectors placed in
   DR_CHAIN at FIRST_VEC_INDX and SECOND_VEC_INDX for the first copy and
   shifting by STRIDE elements of DR_CHAIN for every copy.
   (STRIDE is the number of vectorized stmts for NODE divided by the number of
   copies).  
   VECT_STMTS_COUNTER specifies the index in the vectorized stmts of NODE, where
   the created stmts must be inserted.  */

static inline void
vect_create_mask_and_perm (gimple stmt, gimple next_scalar_stmt, 
                           int *mask_array, int mask_nunits, 
                           tree mask_element_type, tree mask_type,
                           int first_vec_indx, int second_vec_indx, 
                           gimple_stmt_iterator *gsi, slp_tree node, 
                           tree builtin_decl, tree vectype, 
                           VEC(tree,heap) *dr_chain,
                           int ncopies, int vect_stmts_counter)
{
  tree t = NULL_TREE, mask_vec, mask, perm_dest;
  gimple perm_stmt = NULL;
  stmt_vec_info next_stmt_info;
  int i, group_size, stride, dr_chain_size;
  tree first_vec, second_vec, data_ref;
  tree sym;
  ssa_op_iter iter;
  VEC (tree, heap) *params = NULL;

  /* Create a vector mask.  */
  for (i = mask_nunits - 1; i >= 0; --i)
    t = tree_cons (NULL_TREE, build_int_cst (mask_element_type, mask_array[i]),
                   t);
  mask_vec = build_vector (mask_type, t);
  mask = vect_init_vector (stmt, mask_vec, mask_type, NULL);

  group_size = VEC_length (gimple, SLP_TREE_SCALAR_STMTS (node));
  stride = SLP_TREE_NUMBER_OF_VEC_STMTS (node) / ncopies;
  dr_chain_size = VEC_length (tree, dr_chain); 

  /* Initialize the vect stmts of NODE to properly insert the generated 
     stmts later.  */
  for (i = VEC_length (gimple, SLP_TREE_VEC_STMTS (node)); 
       i < (int) SLP_TREE_NUMBER_OF_VEC_STMTS (node); i++)
    VEC_quick_push (gimple, SLP_TREE_VEC_STMTS (node), NULL);

  perm_dest = vect_create_destination_var (gimple_assign_lhs (stmt), vectype);
  for (i = 0; i < ncopies; i++)
    {
      first_vec = VEC_index (tree, dr_chain, first_vec_indx);
      second_vec = VEC_index (tree, dr_chain, second_vec_indx);

      /* Build argument list for the vectorized call.  */
      VEC_free (tree, heap, params);
      params = VEC_alloc (tree, heap, 3);
      VEC_quick_push (tree, params, first_vec);
      VEC_quick_push (tree, params, second_vec);
      VEC_quick_push (tree, params, mask);

      /* Generate the permute statement.  */
      perm_stmt = gimple_build_call_vec (builtin_decl, params);
      data_ref = make_ssa_name (perm_dest, perm_stmt);
      gimple_call_set_lhs (perm_stmt, data_ref);
      vect_finish_stmt_generation (stmt, perm_stmt, gsi);
      FOR_EACH_SSA_TREE_OPERAND (sym, perm_stmt, iter, SSA_OP_ALL_VIRTUALS)
        {
          if (TREE_CODE (sym) == SSA_NAME)
            sym = SSA_NAME_VAR (sym);
          mark_sym_for_renaming (sym);
        }

      /* Store the vector statement in NODE.  */ 
      VEC_replace (gimple, SLP_TREE_VEC_STMTS (node), 
                   stride * i + vect_stmts_counter, perm_stmt);

      first_vec_indx += stride;
      second_vec_indx += stride;
    }

  /* Mark the scalar stmt as vectorized.  */
  next_stmt_info = vinfo_for_stmt (next_scalar_stmt);
  STMT_VINFO_VEC_STMT (next_stmt_info) = perm_stmt;
}


/* Given FIRST_MASK_ELEMENT - the mask element in element representation, 
   return in CURRENT_MASK_ELEMENT its equivalent in target specific
   representation. Check that the mask is valid and return FALSE if not. 
   Return TRUE in NEED_NEXT_VECTOR if the permutation requires to move to
   the next vector, i.e., the current first vector is not needed.  */
   
static bool
vect_get_mask_element (gimple stmt, int first_mask_element, int m, 
                       int mask_nunits, bool only_one_vec, int index,
                       int *mask, int *current_mask_element, 
                       bool *need_next_vector)
{
  int i;
  static int number_of_mask_fixes = 1;
  static bool mask_fixed = false;
  static bool needs_first_vector = false;

  /* Convert to target specific representation.  */
  *current_mask_element = first_mask_element + m;
  /* Adjust the value in case it's a mask for second and third vectors.  */
  *current_mask_element -= mask_nunits * (number_of_mask_fixes - 1);

  if (*current_mask_element < mask_nunits)
    needs_first_vector = true;

  /* We have only one input vector to permute but the mask accesses values in
     the next vector as well.  */
  if (only_one_vec && *current_mask_element >= mask_nunits)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        {
          fprintf (vect_dump, "permutation requires at least two vectors ");
          print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
        }

      return false;
    }

  /* The mask requires the next vector.  */
  if (*current_mask_element >= mask_nunits * 2)
    {
      if (needs_first_vector || mask_fixed)
        {
          /* We either need the first vector too or have already moved to the
             next vector. In both cases, this permutation needs three   
             vectors.  */
          if (vect_print_dump_info (REPORT_DETAILS))
            {
              fprintf (vect_dump, "permutation requires at "
                                  "least three vectors ");
              print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
            }

          return false;
        }

      /* We move to the next vector, dropping the first one and working with
         the second and the third - we need to adjust the values of the mask
         accordingly.  */
      *current_mask_element -= mask_nunits * number_of_mask_fixes;

      for (i = 0; i < index; i++)
        mask[i] -= mask_nunits * number_of_mask_fixes;

      (number_of_mask_fixes)++;
      mask_fixed = true;
    }

  *need_next_vector = mask_fixed;

  /* This was the last element of this mask. Start a new one.  */
  if (index == mask_nunits - 1)
    {
      number_of_mask_fixes = 1;
      mask_fixed = false;
      needs_first_vector = false;
    }

  return true;
}


/* Generate vector permute statements from a list of loads in DR_CHAIN.
   If ANALYZE_ONLY is TRUE, only check that it is possible to create valid
   permute statements for SLP_NODE_INSTANCE.  */
bool
vect_transform_slp_perm_load (gimple stmt, VEC (tree, heap) *dr_chain,
                              gimple_stmt_iterator *gsi, int vf,
                              slp_instance slp_node_instance, bool analyze_only)
{
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  tree mask_element_type = NULL_TREE, mask_type;
  int i, j, k, m, scale, mask_nunits, nunits, vec_index = 0, scalar_index;
  slp_tree node;
  tree vectype = STMT_VINFO_VECTYPE (stmt_info), builtin_decl;
  gimple next_scalar_stmt;
  int group_size = SLP_INSTANCE_GROUP_SIZE (slp_node_instance);
  int first_mask_element;
  int index, unroll_factor, *mask, current_mask_element, ncopies;
  bool only_one_vec = false, need_next_vector = false;
  int first_vec_index, second_vec_index, orig_vec_stmts_num, vect_stmts_counter;

  if (!targetm.vectorize.builtin_vec_perm)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        {
          fprintf (vect_dump, "no builtin for vect permute for ");
          print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
        }

       return false;
    }

  builtin_decl = targetm.vectorize.builtin_vec_perm (vectype,
                                                     &mask_element_type);
  if (!builtin_decl || !mask_element_type)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        {
          fprintf (vect_dump, "no builtin for vect permute for ");
          print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
        }

       return false;
    }

  mask_type = get_vectype_for_scalar_type (mask_element_type);
  mask_nunits = TYPE_VECTOR_SUBPARTS (mask_type);
  mask = (int *) xmalloc (sizeof (int) * mask_nunits);
  nunits = TYPE_VECTOR_SUBPARTS (vectype);
  scale = mask_nunits / nunits;
  unroll_factor = SLP_INSTANCE_UNROLLING_FACTOR (slp_node_instance);

  /* The number of vector stmts to generate based only on SLP_NODE_INSTANCE
     unrolling factor.  */
  orig_vec_stmts_num = group_size * 
                SLP_INSTANCE_UNROLLING_FACTOR (slp_node_instance) / nunits;
  if (orig_vec_stmts_num == 1)
    only_one_vec = true;

  /* Number of copies is determined by the final vectorization factor 
     relatively to SLP_NODE_INSTANCE unrolling factor.  */
  ncopies = vf / SLP_INSTANCE_UNROLLING_FACTOR (slp_node_instance); 

  /* Generate permutation masks for every NODE. Number of masks for each NODE 
     is equal to GROUP_SIZE.  
     E.g., we have a group of three nodes with three loads from the same 
     location in each node, and the vector size is 4. I.e., we have a 
     a0b0c0a1b1c1... sequence and we need to create the following vectors: 
     for a's: a0a0a0a1 a1a1a2a2 a2a3a3a3
     for b's: b0b0b0b1 b1b1b2b2 b2b3b3b3
     ...

     The masks for a's should be: {0,0,0,3} {3,3,6,6} {6,9,9,9} (in target
     scpecific type, e.g., in bytes for Altivec.
     The last mask is illegal since we assume two operands for permute 
     operation, and the mask element values can't be outside that range. Hence,
     the last mask must be converted into {2,5,5,5}.
     For the first two permutations we need the first and the second input 
     vectors: {a0,b0,c0,a1} and {b1,c1,a2,b2}, and for the last permutation
     we need the second and the third vectors: {b1,c1,a2,b2} and 
     {c2,a3,b3,c3}.  */

  for (i = 0;
       VEC_iterate (slp_tree, SLP_INSTANCE_LOADS (slp_node_instance),
                    i, node);
       i++)
    {
      scalar_index = 0;
      index = 0;
      vect_stmts_counter = 0;
      vec_index = 0;
      first_vec_index = vec_index++;
      if (only_one_vec)
        second_vec_index = first_vec_index;
      else
        second_vec_index =  vec_index++;

      for (j = 0; j < unroll_factor; j++)
        {
          for (k = 0; k < group_size; k++)
            {
              first_mask_element = (i + j * group_size) * scale;
              for (m = 0; m < scale; m++)
                {
                  if (!vect_get_mask_element (stmt, first_mask_element, m, 
                                   mask_nunits, only_one_vec, index, mask,
                                   &current_mask_element, &need_next_vector))
                    return false;

                  mask[index++] = current_mask_element;
                } 

              if (index == mask_nunits)
                {
                  index = 0;
                  if (!analyze_only)
                    {
                      if (need_next_vector)
                        {
                          first_vec_index = second_vec_index;
                          second_vec_index = vec_index;
                        }

                      next_scalar_stmt = VEC_index (gimple,
                                SLP_TREE_SCALAR_STMTS (node), scalar_index++);

                      vect_create_mask_and_perm (stmt, next_scalar_stmt,
                               mask, mask_nunits, mask_element_type, mask_type, 
                               first_vec_index, second_vec_index, gsi, node, 
                               builtin_decl, vectype, dr_chain, ncopies, 
                               vect_stmts_counter++);
                    }
                } 
            } 
        } 
    } 

  free (mask);
  return true;
}

/* vectorizable_load.

   Check if STMT reads a non scalar data-ref (array/pointer/structure) that 
   can be vectorized. 
   If VEC_STMT is also passed, vectorize the STMT: create a vectorized 
   stmt to replace it, put it in VEC_STMT, and insert it at BSI.
   Return FALSE if not a vectorizable STMT, TRUE otherwise.  */

bool
vectorizable_load (gimple stmt, gimple_stmt_iterator *gsi, gimple *vec_stmt,
                   slp_tree slp_node, slp_instance slp_node_instance)
{
  tree scalar_dest;
  tree vec_dest = NULL;
  tree data_ref = NULL;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  stmt_vec_info prev_stmt_info; 
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  struct loop *containing_loop = (gimple_bb (stmt))->loop_father;
  bool nested_in_vect_loop = nested_in_vect_loop_p (loop, stmt);
  struct data_reference *dr = STMT_VINFO_DATA_REF (stmt_info), *first_dr;
  tree vectype = STMT_VINFO_VECTYPE (stmt_info);
  tree new_temp;
  int mode;
  gimple new_stmt = NULL;
  tree dummy;
  enum dr_alignment_support alignment_support_scheme;
  tree dataref_ptr = NULL_TREE;
  gimple ptr_incr;
  int nunits = TYPE_VECTOR_SUBPARTS (vectype);
  int ncopies;
  int i, j, group_size;
  tree msq = NULL_TREE, lsq;
  tree offset = NULL_TREE;
  tree realignment_token = NULL_TREE;
  gimple phi = NULL;
  VEC(tree,heap) *dr_chain = NULL;
  bool strided_load = false;
  gimple first_stmt;
  tree scalar_type;
  bool inv_p;
  bool compute_in_loop = false;
  struct loop *at_loop;
  int vec_num;
  bool slp = (slp_node != NULL);
  bool slp_perm = false;
  enum tree_code code;

  /* Multiple types in SLP are handled by creating the appropriate number of
     vectorized stmts for each SLP node. Hence, NCOPIES is always 1 in
     case of SLP.  */
  if (slp)
    ncopies = 1;
  else
    ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits;

  gcc_assert (ncopies >= 1);

  /* FORNOW. This restriction should be relaxed.  */
  if (nested_in_vect_loop && ncopies > 1)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "multiple types in nested loop.");
      return false;
    }

  if (slp && SLP_INSTANCE_LOAD_PERMUTATION (slp_node_instance))
    slp_perm = true;
 
  if (!STMT_VINFO_RELEVANT_P (stmt_info))
    return false;

  if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_loop_def)
    return false;

  /* Is vectorizable load? */
  if (!is_gimple_assign (stmt))
    return false;

  scalar_dest = gimple_assign_lhs (stmt);
  if (TREE_CODE (scalar_dest) != SSA_NAME)
    return false;

  code = gimple_assign_rhs_code (stmt);
  if (code != ARRAY_REF
      && code != INDIRECT_REF
      && !STMT_VINFO_STRIDED_ACCESS (stmt_info))
    return false;

  if (!STMT_VINFO_DATA_REF (stmt_info))
    return false;

  scalar_type = TREE_TYPE (DR_REF (dr));
  mode = (int) TYPE_MODE (vectype);

  /* FORNOW. In some cases can vectorize even if data-type not supported
    (e.g. - data copies).  */
  if (optab_handler (mov_optab, mode)->insn_code == CODE_FOR_nothing)
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "Aligned load, but unsupported type.");
      return false;
    }

  /* The vector component type needs to be trivially convertible to the
     scalar lhs.  This should always be the case.  */
  if (!useless_type_conversion_p (TREE_TYPE (scalar_dest), TREE_TYPE (vectype)))
    {      
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "???  operands of different types");
      return false;
    }

  /* Check if the load is a part of an interleaving chain.  */
  if (STMT_VINFO_STRIDED_ACCESS (stmt_info))
    {
      strided_load = true;
      /* FORNOW */
      gcc_assert (! nested_in_vect_loop);

      /* Check if interleaving is supported.  */
      if (!vect_strided_load_supported (vectype)
          && !PURE_SLP_STMT (stmt_info) && !slp)
        return false;
    }

  if (!vec_stmt) /* transformation not required.  */
    {
      STMT_VINFO_TYPE (stmt_info) = load_vec_info_type;
      vect_model_load_cost (stmt_info, ncopies, NULL);
      return true;
    }

  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "transform load.");

  /** Transform.  **/

  if (strided_load)
    {
      first_stmt = DR_GROUP_FIRST_DR (stmt_info);
      /* Check if the chain of loads is already vectorized.  */
      if (STMT_VINFO_VEC_STMT (vinfo_for_stmt (first_stmt)))
        {
          *vec_stmt = STMT_VINFO_VEC_STMT (stmt_info);
          return true;
        }
      first_dr = STMT_VINFO_DATA_REF (vinfo_for_stmt (first_stmt));
      group_size = DR_GROUP_SIZE (vinfo_for_stmt (first_stmt));

      /* VEC_NUM is the number of vect stmts to be created for this group.  */
      if (slp)
        {
          strided_load = false;
          vec_num = SLP_TREE_NUMBER_OF_VEC_STMTS (slp_node);
        }
      else
        vec_num = group_size;

      dr_chain = VEC_alloc (tree, heap, vec_num);
    }
  else
    {
      first_stmt = stmt;
      first_dr = dr;
      group_size = vec_num = 1;
    }

  alignment_support_scheme = vect_supportable_dr_alignment (first_dr);
  gcc_assert (alignment_support_scheme);

  /* In case the vectorization factor (VF) is bigger than the number
     of elements that we can fit in a vectype (nunits), we have to generate
     more than one vector stmt - i.e - we need to "unroll" the
     vector stmt by a factor VF/nunits. In doing so, we record a pointer
     from one copy of the vector stmt to the next, in the field
     STMT_VINFO_RELATED_STMT. This is necessary in order to allow following
     stages to find the correct vector defs to be used when vectorizing
     stmts that use the defs of the current stmt. The example below illustrates
     the vectorization process when VF=16 and nunits=4 (i.e - we need to create
     4 vectorized stmts):

     before vectorization:
                                RELATED_STMT    VEC_STMT
        S1:     x = memref      -               -
        S2:     z = x + 1       -               -

     step 1: vectorize stmt S1:
        We first create the vector stmt VS1_0, and, as usual, record a
        pointer to it in the STMT_VINFO_VEC_STMT of the scalar stmt S1.
        Next, we create the vector stmt VS1_1, and record a pointer to
        it in the STMT_VINFO_RELATED_STMT of the vector stmt VS1_0.
        Similarly, for VS1_2 and VS1_3. This is the resulting chain of
        stmts and pointers:
                                RELATED_STMT    VEC_STMT
        VS1_0:  vx0 = memref0   VS1_1           -
        VS1_1:  vx1 = memref1   VS1_2           -
        VS1_2:  vx2 = memref2   VS1_3           -
        VS1_3:  vx3 = memref3   -               -
        S1:     x = load        -               VS1_0
        S2:     z = x + 1       -               -

     See in documentation in vect_get_vec_def_for_stmt_copy for how the 
     information we recorded in RELATED_STMT field is used to vectorize 
     stmt S2.  */

  /* In case of interleaving (non-unit strided access):

     S1:  x2 = &base + 2
     S2:  x0 = &base
     S3:  x1 = &base + 1
     S4:  x3 = &base + 3

     Vectorized loads are created in the order of memory accesses 
     starting from the access of the first stmt of the chain:

     VS1: vx0 = &base
     VS2: vx1 = &base + vec_size*1
     VS3: vx3 = &base + vec_size*2
     VS4: vx4 = &base + vec_size*3

     Then permutation statements are generated:

     VS5: vx5 = VEC_EXTRACT_EVEN_EXPR < vx0, vx1 >
     VS6: vx6 = VEC_EXTRACT_ODD_EXPR < vx0, vx1 >
       ...

     And they are put in STMT_VINFO_VEC_STMT of the corresponding scalar stmts
     (the order of the data-refs in the output of vect_permute_load_chain
     corresponds to the order of scalar stmts in the interleaving chain - see
     the documentation of vect_permute_load_chain()).
     The generation of permutation stmts and recording them in
     STMT_VINFO_VEC_STMT is done in vect_transform_strided_load().

     In case of both multiple types and interleaving, the vector loads and 
     permutation stmts above are created for every copy. The result vector stmts
     are put in STMT_VINFO_VEC_STMT for the first copy and in the corresponding
     STMT_VINFO_RELATED_STMT for the next copies.  */

  /* If the data reference is aligned (dr_aligned) or potentially unaligned
     on a target that supports unaligned accesses (dr_unaligned_supported)
     we generate the following code:
         p = initial_addr;
         indx = 0;
         loop {
           p = p + indx * vectype_size;
           vec_dest = *(p);
           indx = indx + 1;
         }

     Otherwise, the data reference is potentially unaligned on a target that
     does not support unaligned accesses (dr_explicit_realign_optimized) - 
     then generate the following code, in which the data in each iteration is
     obtained by two vector loads, one from the previous iteration, and one
     from the current iteration:
         p1 = initial_addr;
         msq_init = *(floor(p1))
         p2 = initial_addr + VS - 1;
         realignment_token = call target_builtin;
         indx = 0;
         loop {
           p2 = p2 + indx * vectype_size
           lsq = *(floor(p2))
           vec_dest = realign_load (msq, lsq, realignment_token)
           indx = indx + 1;
           msq = lsq;
         }   */

  /* If the misalignment remains the same throughout the execution of the
     loop, we can create the init_addr and permutation mask at the loop
     preheader. Otherwise, it needs to be created inside the loop.
     This can only occur when vectorizing memory accesses in the inner-loop
     nested within an outer-loop that is being vectorized.  */

  if (nested_in_vect_loop_p (loop, stmt)
      && (TREE_INT_CST_LOW (DR_STEP (dr))
          % GET_MODE_SIZE (TYPE_MODE (vectype)) != 0))
    {
      gcc_assert (alignment_support_scheme != dr_explicit_realign_optimized);
      compute_in_loop = true;
    }

  if ((alignment_support_scheme == dr_explicit_realign_optimized
       || alignment_support_scheme == dr_explicit_realign)
      && !compute_in_loop)
    {
      msq = vect_setup_realignment (first_stmt, gsi, &realignment_token,
                                    alignment_support_scheme, NULL_TREE,
                                    &at_loop);
      if (alignment_support_scheme == dr_explicit_realign_optimized)
        {
          phi = SSA_NAME_DEF_STMT (msq);
          offset = size_int (TYPE_VECTOR_SUBPARTS (vectype) - 1);
        }
    }
  else
    at_loop = loop;

  prev_stmt_info = NULL;
  for (j = 0; j < ncopies; j++)
    { 
      /* 1. Create the vector pointer update chain.  */
      if (j == 0)
        dataref_ptr = vect_create_data_ref_ptr (first_stmt,
                                                at_loop, offset, 
                                                &dummy, &ptr_incr, false, 
                                                &inv_p, NULL_TREE);
      else
        dataref_ptr = 
                bump_vector_ptr (dataref_ptr, ptr_incr, gsi, stmt, NULL_TREE);

      for (i = 0; i < vec_num; i++)
        {
          if (i > 0)
            dataref_ptr = bump_vector_ptr (dataref_ptr, ptr_incr, gsi, stmt,
                                           NULL_TREE);

          /* 2. Create the vector-load in the loop.  */
          switch (alignment_support_scheme)
            {
            case dr_aligned:
              gcc_assert (aligned_access_p (first_dr));
              data_ref = build_fold_indirect_ref (dataref_ptr);
              break;
            case dr_unaligned_supported:
              {
                int mis = DR_MISALIGNMENT (first_dr);
                tree tmis = (mis == -1 ? size_zero_node : size_int (mis));

                tmis = size_binop (MULT_EXPR, tmis, size_int(BITS_PER_UNIT));
                data_ref =
                  build2 (MISALIGNED_INDIRECT_REF, vectype, dataref_ptr, tmis);
                break;
              }
            case dr_explicit_realign:
              {
                tree ptr, bump;
                tree vs_minus_1 = size_int (TYPE_VECTOR_SUBPARTS (vectype) - 1);

                if (compute_in_loop)
                  msq = vect_setup_realignment (first_stmt, gsi,
                                                &realignment_token,
                                                dr_explicit_realign, 
                                                dataref_ptr, NULL);

                data_ref = build1 (ALIGN_INDIRECT_REF, vectype, dataref_ptr);
                vec_dest = vect_create_destination_var (scalar_dest, vectype);
                new_stmt = gimple_build_assign (vec_dest, data_ref);
                new_temp = make_ssa_name (vec_dest, new_stmt);
                gimple_assign_set_lhs (new_stmt, new_temp);
                vect_finish_stmt_generation (stmt, new_stmt, gsi);
                copy_virtual_operands (new_stmt, stmt);
                mark_symbols_for_renaming (new_stmt);
                msq = new_temp;

                bump = size_binop (MULT_EXPR, vs_minus_1,
                                   TYPE_SIZE_UNIT (scalar_type));
                ptr = bump_vector_ptr (dataref_ptr, NULL, gsi, stmt, bump);
                data_ref = build1 (ALIGN_INDIRECT_REF, vectype, ptr);
                break;
              }
            case dr_explicit_realign_optimized:
              data_ref = build1 (ALIGN_INDIRECT_REF, vectype, dataref_ptr);
              break;
            default:
              gcc_unreachable ();
            }
          vec_dest = vect_create_destination_var (scalar_dest, vectype);
          new_stmt = gimple_build_assign (vec_dest, data_ref);
          new_temp = make_ssa_name (vec_dest, new_stmt);
          gimple_assign_set_lhs (new_stmt, new_temp);
          vect_finish_stmt_generation (stmt, new_stmt, gsi);
          mark_symbols_for_renaming (new_stmt);

          /* 3. Handle explicit realignment if necessary/supported. Create in
                loop: vec_dest = realign_load (msq, lsq, realignment_token)  */
          if (alignment_support_scheme == dr_explicit_realign_optimized
              || alignment_support_scheme == dr_explicit_realign)
            {
              tree tmp;

              lsq = gimple_assign_lhs (new_stmt);
              if (!realignment_token)
                realignment_token = dataref_ptr;
              vec_dest = vect_create_destination_var (scalar_dest, vectype);
              tmp = build3 (REALIGN_LOAD_EXPR, vectype, msq, lsq,
                            realignment_token);
              new_stmt = gimple_build_assign (vec_dest, tmp);
              new_temp = make_ssa_name (vec_dest, new_stmt);
              gimple_assign_set_lhs (new_stmt, new_temp);
              vect_finish_stmt_generation (stmt, new_stmt, gsi);

              if (alignment_support_scheme == dr_explicit_realign_optimized)
                {
                  gcc_assert (phi);
                  if (i == vec_num - 1 && j == ncopies - 1)
                    add_phi_arg (phi, lsq, loop_latch_edge (containing_loop));
                  msq = lsq;
                }
            }

          /* 4. Handle invariant-load.  */
          if (inv_p)
            {
              gcc_assert (!strided_load);
              gcc_assert (nested_in_vect_loop_p (loop, stmt));
              if (j == 0)
                {
                  int k;
                  tree t = NULL_TREE;
                  tree vec_inv, bitpos, bitsize = TYPE_SIZE (scalar_type);

                  /* CHECKME: bitpos depends on endianess?  */
                  bitpos = bitsize_zero_node;
                  vec_inv = build3 (BIT_FIELD_REF, scalar_type, new_temp, 
                                    bitsize, bitpos);
                  vec_dest = 
                        vect_create_destination_var (scalar_dest, NULL_TREE);
                  new_stmt = gimple_build_assign (vec_dest, vec_inv);
                  new_temp = make_ssa_name (vec_dest, new_stmt);
                  gimple_assign_set_lhs (new_stmt, new_temp);
                  vect_finish_stmt_generation (stmt, new_stmt, gsi);

                  for (k = nunits - 1; k >= 0; --k)
                    t = tree_cons (NULL_TREE, new_temp, t);
                  /* FIXME: use build_constructor directly.  */
                  vec_inv = build_constructor_from_list (vectype, t);
                  new_temp = vect_init_vector (stmt, vec_inv, vectype, gsi);
                  new_stmt = SSA_NAME_DEF_STMT (new_temp);
                }
              else
                gcc_unreachable (); /* FORNOW. */
            }

          /* Collect vector loads and later create their permutation in
             vect_transform_strided_load ().  */
          if (strided_load || slp_perm)
            VEC_quick_push (tree, dr_chain, new_temp);

         /* Store vector loads in the corresponding SLP_NODE.  */
          if (slp && !slp_perm)
            VEC_quick_push (gimple, SLP_TREE_VEC_STMTS (slp_node), new_stmt);
        }

      if (slp && !slp_perm)
        continue;

      if (slp_perm)
        {
          if (!vect_transform_slp_perm_load (stmt, dr_chain, gsi,
                                   LOOP_VINFO_VECT_FACTOR (loop_vinfo),
                                             slp_node_instance, false))
            {
              VEC_free (tree, heap, dr_chain);
              return false;
            }
        }
      else
        {
          if (strided_load)
            {
              if (!vect_transform_strided_load (stmt, dr_chain, group_size, gsi))
                return false;     

              *vec_stmt = STMT_VINFO_VEC_STMT (stmt_info);
              VEC_free (tree, heap, dr_chain);
              dr_chain = VEC_alloc (tree, heap, group_size);
            }
          else
            {
              if (j == 0)
                STMT_VINFO_VEC_STMT (stmt_info) = *vec_stmt = new_stmt;
              else
                STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;
              prev_stmt_info = vinfo_for_stmt (new_stmt);
            }
        }
    }

  if (dr_chain)
    VEC_free (tree, heap, dr_chain);

  return true;
}


/* Function vectorizable_live_operation.

   STMT computes a value that is used outside the loop. Check if 
   it can be supported.  */

bool
vectorizable_live_operation (gimple stmt,
                             gimple_stmt_iterator *gsi ATTRIBUTE_UNUSED,
                             gimple *vec_stmt ATTRIBUTE_UNUSED)
{
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  int i;
  int op_type;
  tree op;
  tree def;
  gimple def_stmt;
  enum vect_def_type dt; 
  enum tree_code code;
  enum gimple_rhs_class rhs_class;

  gcc_assert (STMT_VINFO_LIVE_P (stmt_info));

  if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_reduction_def)
    return false;

  if (!is_gimple_assign (stmt))
    return false;

  if (TREE_CODE (gimple_assign_lhs (stmt)) != SSA_NAME)
    return false;

  /* FORNOW. CHECKME. */
  if (nested_in_vect_loop_p (loop, stmt))
    return false;

  code = gimple_assign_rhs_code (stmt);
  op_type = TREE_CODE_LENGTH (code);
  rhs_class = get_gimple_rhs_class (code);
  gcc_assert (rhs_class != GIMPLE_UNARY_RHS || op_type == unary_op);
  gcc_assert (rhs_class != GIMPLE_BINARY_RHS || op_type == binary_op);

  /* FORNOW: support only if all uses are invariant. This means
     that the scalar operations can remain in place, unvectorized.
     The original last scalar value that they compute will be used.  */

  for (i = 0; i < op_type; i++)
    {
      if (rhs_class == GIMPLE_SINGLE_RHS)
        op = TREE_OPERAND (gimple_op (stmt, 1), i);
      else
        op = gimple_op (stmt, i + 1);
      if (op && !vect_is_simple_use (op, loop_vinfo, &def_stmt, &def, &dt))
        {
          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "use not simple.");
          return false;
        }

      if (dt != vect_invariant_def && dt != vect_constant_def)
        return false;
    }

  /* No transformation is required for the cases we currently support.  */
  return true;
}


/* Function vect_is_simple_cond.
  
   Input:
   LOOP - the loop that is being vectorized.
   COND - Condition that is checked for simple use.

   Returns whether a COND can be vectorized.  Checks whether
   condition operands are supportable using vec_is_simple_use.  */

static bool
vect_is_simple_cond (tree cond, loop_vec_info loop_vinfo)
{
  tree lhs, rhs;
  tree def;
  enum vect_def_type dt;

  if (!COMPARISON_CLASS_P (cond))
    return false;

  lhs = TREE_OPERAND (cond, 0);
  rhs = TREE_OPERAND (cond, 1);

  if (TREE_CODE (lhs) == SSA_NAME)
    {
      gimple lhs_def_stmt = SSA_NAME_DEF_STMT (lhs);
      if (!vect_is_simple_use (lhs, loop_vinfo, &lhs_def_stmt, &def, &dt))
        return false;
    }
  else if (TREE_CODE (lhs) != INTEGER_CST && TREE_CODE (lhs) != REAL_CST
           && TREE_CODE (lhs) != FIXED_CST)
    return false;

  if (TREE_CODE (rhs) == SSA_NAME)
    {
      gimple rhs_def_stmt = SSA_NAME_DEF_STMT (rhs);
      if (!vect_is_simple_use (rhs, loop_vinfo, &rhs_def_stmt, &def, &dt))
        return false;
    }
  else if (TREE_CODE (rhs) != INTEGER_CST  && TREE_CODE (rhs) != REAL_CST
           && TREE_CODE (rhs) != FIXED_CST)
    return false;

  return true;
}

/* vectorizable_condition.

   Check if STMT is conditional modify expression that can be vectorized. 
   If VEC_STMT is also passed, vectorize the STMT: create a vectorized 
   stmt using VEC_COND_EXPR  to replace it, put it in VEC_STMT, and insert it 
   at BSI.

   Return FALSE if not a vectorizable STMT, TRUE otherwise.  */

bool
vectorizable_condition (gimple stmt, gimple_stmt_iterator *gsi,
                        gimple *vec_stmt)
{
  tree scalar_dest = NULL_TREE;
  tree vec_dest = NULL_TREE;
  tree op = NULL_TREE;
  tree cond_expr, then_clause, else_clause;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  tree vectype = STMT_VINFO_VECTYPE (stmt_info);
  tree vec_cond_lhs, vec_cond_rhs, vec_then_clause, vec_else_clause;
  tree vec_compare, vec_cond_expr;
  tree new_temp;
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  enum machine_mode vec_mode;
  tree def;
  enum vect_def_type dt;
  int nunits = TYPE_VECTOR_SUBPARTS (vectype);
  int ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits;
  enum tree_code code;

  gcc_assert (ncopies >= 1);
  if (ncopies > 1)
    return false; /* FORNOW */

  if (!STMT_VINFO_RELEVANT_P (stmt_info))
    return false;

  if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_loop_def)
    return false;

  /* FORNOW: SLP not supported.  */
  if (STMT_SLP_TYPE (stmt_info))
    return false;

  /* FORNOW: not yet supported.  */
  if (STMT_VINFO_LIVE_P (stmt_info))
    {
      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "value used after loop.");
      return false;
    }

  /* Is vectorizable conditional operation?  */
  if (!is_gimple_assign (stmt))
    return false;

  code = gimple_assign_rhs_code (stmt);

  if (code != COND_EXPR)
    return false;

  gcc_assert (gimple_assign_single_p (stmt));
  op = gimple_assign_rhs1 (stmt);
  cond_expr = TREE_OPERAND (op, 0);
  then_clause = TREE_OPERAND (op, 1);
  else_clause = TREE_OPERAND (op, 2);

  if (!vect_is_simple_cond (cond_expr, loop_vinfo))
    return false;

  /* We do not handle two different vector types for the condition
     and the values.  */
  if (TREE_TYPE (TREE_OPERAND (cond_expr, 0)) != TREE_TYPE (vectype))
    return false;

  if (TREE_CODE (then_clause) == SSA_NAME)
    {
      gimple then_def_stmt = SSA_NAME_DEF_STMT (then_clause);
      if (!vect_is_simple_use (then_clause, loop_vinfo, 
                               &then_def_stmt, &def, &dt))
        return false;
    }
  else if (TREE_CODE (then_clause) != INTEGER_CST 
           && TREE_CODE (then_clause) != REAL_CST
           && TREE_CODE (then_clause) != FIXED_CST)
    return false;

  if (TREE_CODE (else_clause) == SSA_NAME)
    {
      gimple else_def_stmt = SSA_NAME_DEF_STMT (else_clause);
      if (!vect_is_simple_use (else_clause, loop_vinfo, 
                               &else_def_stmt, &def, &dt))
        return false;
    }
  else if (TREE_CODE (else_clause) != INTEGER_CST 
           && TREE_CODE (else_clause) != REAL_CST
           && TREE_CODE (else_clause) != FIXED_CST)
    return false;


  vec_mode = TYPE_MODE (vectype);

  if (!vec_stmt) 
    {
      STMT_VINFO_TYPE (stmt_info) = condition_vec_info_type;
      return expand_vec_cond_expr_p (op, vec_mode);
    }

  /* Transform */

  /* Handle def.  */
  scalar_dest = gimple_assign_lhs (stmt);
  vec_dest = vect_create_destination_var (scalar_dest, vectype);

  /* Handle cond expr.  */
  vec_cond_lhs = 
    vect_get_vec_def_for_operand (TREE_OPERAND (cond_expr, 0), stmt, NULL);
  vec_cond_rhs = 
    vect_get_vec_def_for_operand (TREE_OPERAND (cond_expr, 1), stmt, NULL);
  vec_then_clause = vect_get_vec_def_for_operand (then_clause, stmt, NULL);
  vec_else_clause = vect_get_vec_def_for_operand (else_clause, stmt, NULL);

  /* Arguments are ready. Create the new vector stmt.  */
  vec_compare = build2 (TREE_CODE (cond_expr), vectype, 
                        vec_cond_lhs, vec_cond_rhs);
  vec_cond_expr = build3 (VEC_COND_EXPR, vectype, 
                          vec_compare, vec_then_clause, vec_else_clause);

  *vec_stmt = gimple_build_assign (vec_dest, vec_cond_expr);
  new_temp = make_ssa_name (vec_dest, *vec_stmt);
  gimple_assign_set_lhs (*vec_stmt, new_temp);
  vect_finish_stmt_generation (stmt, *vec_stmt, gsi);
  
  return true;
}


/* Function vect_transform_stmt.

   Create a vectorized stmt to replace STMT, and insert it at BSI.  */

static bool
vect_transform_stmt (gimple stmt, gimple_stmt_iterator *gsi,
                     bool *strided_store, slp_tree slp_node, 
                     slp_instance slp_node_instance)
{
  bool is_store = false;
  gimple vec_stmt = NULL;
  stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
  gimple orig_stmt_in_pattern;
  bool done;
  loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);

  switch (STMT_VINFO_TYPE (stmt_info))
    {
    case type_demotion_vec_info_type:
      done = vectorizable_type_demotion (stmt, gsi, &vec_stmt, slp_node);
      gcc_assert (done);
      break;

    case type_promotion_vec_info_type:
      done = vectorizable_type_promotion (stmt, gsi, &vec_stmt, slp_node);
      gcc_assert (done);
      break;

    case type_conversion_vec_info_type:
      done = vectorizable_conversion (stmt, gsi, &vec_stmt, slp_node);
      gcc_assert (done);
      break;

    case induc_vec_info_type:
      gcc_assert (!slp_node);
      done = vectorizable_induction (stmt, gsi, &vec_stmt);
      gcc_assert (done);
      break;

    case op_vec_info_type:
      done = vectorizable_operation (stmt, gsi, &vec_stmt, slp_node);
      gcc_assert (done);
      break;

    case assignment_vec_info_type:
      done = vectorizable_assignment (stmt, gsi, &vec_stmt, slp_node);
      gcc_assert (done);
      break;

    case load_vec_info_type:
      done = vectorizable_load (stmt, gsi, &vec_stmt, slp_node, 
                                slp_node_instance);
      gcc_assert (done);
      break;

    case store_vec_info_type:
      done = vectorizable_store (stmt, gsi, &vec_stmt, slp_node);
      gcc_assert (done);
      if (STMT_VINFO_STRIDED_ACCESS (stmt_info) && !slp_node)
        {
          /* In case of interleaving, the whole chain is vectorized when the
             last store in the chain is reached. Store stmts before the last
             one are skipped, and there vec_stmt_info shouldn't be freed
             meanwhile.  */
          *strided_store = true;
          if (STMT_VINFO_VEC_STMT (stmt_info))
            is_store = true;
          }
      else
        is_store = true;
      break;

    case condition_vec_info_type:
      gcc_assert (!slp_node);
      done = vectorizable_condition (stmt, gsi, &vec_stmt);
      gcc_assert (done);
      break;

    case call_vec_info_type:
      gcc_assert (!slp_node);
      done = vectorizable_call (stmt, gsi, &vec_stmt);
      break;

    case reduc_vec_info_type:
      gcc_assert (!slp_node);
      done = vectorizable_reduction (stmt, gsi, &vec_stmt);
      gcc_assert (done);
      break;

    default:
      if (!STMT_VINFO_LIVE_P (stmt_info))
        {
          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "stmt not supported.");
          gcc_unreachable ();
        }
    }

  /* Handle inner-loop stmts whose DEF is used in the loop-nest that
     is being vectorized, but outside the immediately enclosing loop.  */
  if (vec_stmt
      && nested_in_vect_loop_p (loop, stmt)
      && STMT_VINFO_TYPE (stmt_info) != reduc_vec_info_type
      && (STMT_VINFO_RELEVANT (stmt_info) == vect_used_in_outer
          || STMT_VINFO_RELEVANT (stmt_info) == vect_used_in_outer_by_reduction))
    {
      struct loop *innerloop = loop->inner;
      imm_use_iterator imm_iter;
      use_operand_p use_p;
      tree scalar_dest;
      gimple exit_phi;

      if (vect_print_dump_info (REPORT_DETAILS))
       fprintf (vect_dump, "Record the vdef for outer-loop vectorization.");

      /* Find the relevant loop-exit phi-node, and reord the vec_stmt there
        (to be used when vectorizing outer-loop stmts that use the DEF of
        STMT).  */
      if (gimple_code (stmt) == GIMPLE_PHI)
        scalar_dest = PHI_RESULT (stmt);
      else
        scalar_dest = gimple_assign_lhs (stmt);

      FOR_EACH_IMM_USE_FAST (use_p, imm_iter, scalar_dest)
       {
         if (!flow_bb_inside_loop_p (innerloop, gimple_bb (USE_STMT (use_p))))
           {
             exit_phi = USE_STMT (use_p);
             STMT_VINFO_VEC_STMT (vinfo_for_stmt (exit_phi)) = vec_stmt;
           }
       }
    }

  /* Handle stmts whose DEF is used outside the loop-nest that is
     being vectorized.  */
  if (STMT_VINFO_LIVE_P (stmt_info)
      && STMT_VINFO_TYPE (stmt_info) != reduc_vec_info_type)
    {
      done = vectorizable_live_operation (stmt, gsi, &vec_stmt);
      gcc_assert (done);
    }

  if (vec_stmt)
    {
      STMT_VINFO_VEC_STMT (stmt_info) = vec_stmt;
      orig_stmt_in_pattern = STMT_VINFO_RELATED_STMT (stmt_info);
      if (orig_stmt_in_pattern)
        {
          stmt_vec_info stmt_vinfo = vinfo_for_stmt (orig_stmt_in_pattern);
          /* STMT was inserted by the vectorizer to replace a computation idiom.
             ORIG_STMT_IN_PATTERN is a stmt in the original sequence that 
             computed this idiom.  We need to record a pointer to VEC_STMT in 
             the stmt_info of ORIG_STMT_IN_PATTERN.  See more details in the 
             documentation of vect_pattern_recog.  */
          if (STMT_VINFO_IN_PATTERN_P (stmt_vinfo))
            {
              gcc_assert (STMT_VINFO_RELATED_STMT (stmt_vinfo) == stmt);
              STMT_VINFO_VEC_STMT (stmt_vinfo) = vec_stmt;
            }
        }
    }

  return is_store; 
}


/* This function builds ni_name = number of iterations loop executes
   on the loop preheader.  */

static tree
vect_build_loop_niters (loop_vec_info loop_vinfo)
{
  tree ni_name, var;
  gimple_seq stmts = NULL;
  edge pe;
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  tree ni = unshare_expr (LOOP_VINFO_NITERS (loop_vinfo));

  var = create_tmp_var (TREE_TYPE (ni), "niters");
  add_referenced_var (var);
  ni_name = force_gimple_operand (ni, &stmts, false, var);

  pe = loop_preheader_edge (loop);
  if (stmts)
    {
      basic_block new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts);
      gcc_assert (!new_bb);
    }
      
  return ni_name;
}


/* This function generates the following statements:

 ni_name = number of iterations loop executes
 ratio = ni_name / vf
 ratio_mult_vf_name = ratio * vf

 and places them at the loop preheader edge.  */

static void 
vect_generate_tmps_on_preheader (loop_vec_info loop_vinfo, 
                                 tree *ni_name_ptr,
                                 tree *ratio_mult_vf_name_ptr, 
                                 tree *ratio_name_ptr)
{

  edge pe;
  basic_block new_bb;
  gimple_seq stmts;
  tree ni_name;
  tree var;
  tree ratio_name;
  tree ratio_mult_vf_name;
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  tree ni = LOOP_VINFO_NITERS (loop_vinfo);
  int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
  tree log_vf;

  pe = loop_preheader_edge (loop);

  /* Generate temporary variable that contains 
     number of iterations loop executes.  */

  ni_name = vect_build_loop_niters (loop_vinfo);
  log_vf = build_int_cst (TREE_TYPE (ni), exact_log2 (vf));

  /* Create: ratio = ni >> log2(vf) */

  ratio_name = fold_build2 (RSHIFT_EXPR, TREE_TYPE (ni_name), ni_name, log_vf);
  if (!is_gimple_val (ratio_name))
    {
      var = create_tmp_var (TREE_TYPE (ni), "bnd");
      add_referenced_var (var);

      stmts = NULL;
      ratio_name = force_gimple_operand (ratio_name, &stmts, true, var);
      pe = loop_preheader_edge (loop);
      new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts);
      gcc_assert (!new_bb);
    }
       
  /* Create: ratio_mult_vf = ratio << log2 (vf).  */

  ratio_mult_vf_name = fold_build2 (LSHIFT_EXPR, TREE_TYPE (ratio_name),
                                    ratio_name, log_vf);
  if (!is_gimple_val (ratio_mult_vf_name))
    {
      var = create_tmp_var (TREE_TYPE (ni), "ratio_mult_vf");
      add_referenced_var (var);

      stmts = NULL;
      ratio_mult_vf_name = force_gimple_operand (ratio_mult_vf_name, &stmts,
                                                 true, var);
      pe = loop_preheader_edge (loop);
      new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts);
      gcc_assert (!new_bb);
    }

  *ni_name_ptr = ni_name;
  *ratio_mult_vf_name_ptr = ratio_mult_vf_name;
  *ratio_name_ptr = ratio_name;
    
  return;  
}


/*   Function vect_update_ivs_after_vectorizer.

     "Advance" the induction variables of LOOP to the value they should take
     after the execution of LOOP.  This is currently necessary because the
     vectorizer does not handle induction variables that are used after the
     loop.  Such a situation occurs when the last iterations of LOOP are
     peeled, because:
     1. We introduced new uses after LOOP for IVs that were not originally used
        after LOOP: the IVs of LOOP are now used by an epilog loop.
     2. LOOP is going to be vectorized; this means that it will iterate N/VF
        times, whereas the loop IVs should be bumped N times.

     Input:
     - LOOP - a loop that is going to be vectorized. The last few iterations
              of LOOP were peeled.
     - NITERS - the number of iterations that LOOP executes (before it is
                vectorized). i.e, the number of times the ivs should be bumped.
     - UPDATE_E - a successor edge of LOOP->exit that is on the (only) path
                  coming out from LOOP on which there are uses of the LOOP ivs
                  (this is the path from LOOP->exit to epilog_loop->preheader).

                  The new definitions of the ivs are placed in LOOP->exit.
                  The phi args associated with the edge UPDATE_E in the bb
                  UPDATE_E->dest are updated accordingly.

     Assumption 1: Like the rest of the vectorizer, this function assumes
     a single loop exit that has a single predecessor.

     Assumption 2: The phi nodes in the LOOP header and in update_bb are
     organized in the same order.

     Assumption 3: The access function of the ivs is simple enough (see
     vect_can_advance_ivs_p).  This assumption will be relaxed in the future.

     Assumption 4: Exactly one of the successors of LOOP exit-bb is on a path
     coming out of LOOP on which the ivs of LOOP are used (this is the path 
     that leads to the epilog loop; other paths skip the epilog loop).  This
     path starts with the edge UPDATE_E, and its destination (denoted update_bb)
     needs to have its phis updated.
 */

static void
vect_update_ivs_after_vectorizer (loop_vec_info loop_vinfo, tree niters, 
                                  edge update_e)
{
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  basic_block exit_bb = single_exit (loop)->dest;
  gimple phi, phi1;
  gimple_stmt_iterator gsi, gsi1;
  basic_block update_bb = update_e->dest;

  /* gcc_assert (vect_can_advance_ivs_p (loop_vinfo)); */

  /* Make sure there exists a single-predecessor exit bb:  */
  gcc_assert (single_pred_p (exit_bb));

  for (gsi = gsi_start_phis (loop->header), gsi1 = gsi_start_phis (update_bb);
       !gsi_end_p (gsi) && !gsi_end_p (gsi1);
       gsi_next (&gsi), gsi_next (&gsi1))
    {
      tree access_fn = NULL;
      tree evolution_part;
      tree init_expr;
      tree step_expr;
      tree var, ni, ni_name;
      gimple_stmt_iterator last_gsi;

      phi = gsi_stmt (gsi);
      phi1 = gsi_stmt (gsi1);
      if (vect_print_dump_info (REPORT_DETAILS))
        {
          fprintf (vect_dump, "vect_update_ivs_after_vectorizer: phi: ");
          print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
        }

      /* Skip virtual phi's.  */
      if (!is_gimple_reg (SSA_NAME_VAR (PHI_RESULT (phi))))
        {
          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "virtual phi. skip.");
          continue;
        }

      /* Skip reduction phis.  */
      if (STMT_VINFO_DEF_TYPE (vinfo_for_stmt (phi)) == vect_reduction_def)
        { 
          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "reduc phi. skip.");
          continue;
        } 

      access_fn = analyze_scalar_evolution (loop, PHI_RESULT (phi)); 
      gcc_assert (access_fn);
      STRIP_NOPS (access_fn);
      evolution_part =
         unshare_expr (evolution_part_in_loop_num (access_fn, loop->num));
      gcc_assert (evolution_part != NULL_TREE);
      
      /* FORNOW: We do not support IVs whose evolution function is a polynomial
         of degree >= 2 or exponential.  */
      gcc_assert (!tree_is_chrec (evolution_part));

      step_expr = evolution_part;
      init_expr = unshare_expr (initial_condition_in_loop_num (access_fn, 
                                                               loop->num));

      if (POINTER_TYPE_P (TREE_TYPE (init_expr)))
        ni = fold_build2 (POINTER_PLUS_EXPR, TREE_TYPE (init_expr), 
                          init_expr, 
                          fold_convert (sizetype, 
                                        fold_build2 (MULT_EXPR, TREE_TYPE (niters),
                                                     niters, step_expr)));
      else
        ni = fold_build2 (PLUS_EXPR, TREE_TYPE (init_expr),
                          fold_build2 (MULT_EXPR, TREE_TYPE (init_expr),
                                       fold_convert (TREE_TYPE (init_expr),
                                                     niters),
                                       step_expr),
                          init_expr);



      var = create_tmp_var (TREE_TYPE (init_expr), "tmp");
      add_referenced_var (var);

      last_gsi = gsi_last_bb (exit_bb);
      ni_name = force_gimple_operand_gsi (&last_gsi, ni, false, var,
                                          true, GSI_SAME_STMT);
      
      /* Fix phi expressions in the successor bb.  */
      SET_PHI_ARG_DEF (phi1, update_e->dest_idx, ni_name);
    }
}

/* Return the more conservative threshold between the
   min_profitable_iters returned by the cost model and the user
   specified threshold, if provided.  */

static unsigned int
conservative_cost_threshold (loop_vec_info loop_vinfo,
                             int min_profitable_iters)
{
  unsigned int th;
  int min_scalar_loop_bound;

  min_scalar_loop_bound = ((PARAM_VALUE (PARAM_MIN_VECT_LOOP_BOUND)
                            * LOOP_VINFO_VECT_FACTOR (loop_vinfo)) - 1);

  /* Use the cost model only if it is more conservative than user specified
     threshold.  */
  th = (unsigned) min_scalar_loop_bound;
  if (min_profitable_iters
      && (!min_scalar_loop_bound
          || min_profitable_iters > min_scalar_loop_bound))
    th = (unsigned) min_profitable_iters;

  if (th && vect_print_dump_info (REPORT_COST))
    fprintf (vect_dump, "Vectorization may not be profitable.");

  return th;
}

/* Function vect_do_peeling_for_loop_bound

   Peel the last iterations of the loop represented by LOOP_VINFO.
   The peeled iterations form a new epilog loop.  Given that the loop now 
   iterates NITERS times, the new epilog loop iterates
   NITERS % VECTORIZATION_FACTOR times.
   
   The original loop will later be made to iterate 
   NITERS / VECTORIZATION_FACTOR times (this value is placed into RATIO).  */

static void 
vect_do_peeling_for_loop_bound (loop_vec_info loop_vinfo, tree *ratio)
{
  tree ni_name, ratio_mult_vf_name;
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  struct loop *new_loop;
  edge update_e;
  basic_block preheader;
  int loop_num;
  bool check_profitability = false;
  unsigned int th = 0;
  int min_profitable_iters;

  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "=== vect_do_peeling_for_loop_bound ===");

  initialize_original_copy_tables ();

  /* Generate the following variables on the preheader of original loop:
         
     ni_name = number of iteration the original loop executes
     ratio = ni_name / vf
     ratio_mult_vf_name = ratio * vf  */
  vect_generate_tmps_on_preheader (loop_vinfo, &ni_name,
                                   &ratio_mult_vf_name, ratio);

  loop_num  = loop->num; 

  /* If cost model check not done during versioning and 
     peeling for alignment.  */
  if (!VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo))
      && !VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo))
      && !LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo))
    {
      check_profitability = true;

      /* Get profitability threshold for vectorized loop.  */
      min_profitable_iters = LOOP_VINFO_COST_MODEL_MIN_ITERS (loop_vinfo);

      th = conservative_cost_threshold (loop_vinfo, 
                                        min_profitable_iters);
    }

  new_loop = slpeel_tree_peel_loop_to_edge (loop, single_exit (loop),
                                            ratio_mult_vf_name, ni_name, false,
                                            th, check_profitability);
  gcc_assert (new_loop);
  gcc_assert (loop_num == loop->num);
#ifdef ENABLE_CHECKING
  slpeel_verify_cfg_after_peeling (loop, new_loop);
#endif

  /* A guard that controls whether the new_loop is to be executed or skipped
     is placed in LOOP->exit.  LOOP->exit therefore has two successors - one
     is the preheader of NEW_LOOP, where the IVs from LOOP are used.  The other
     is a bb after NEW_LOOP, where these IVs are not used.  Find the edge that
     is on the path where the LOOP IVs are used and need to be updated.  */

  preheader = loop_preheader_edge (new_loop)->src;
  if (EDGE_PRED (preheader, 0)->src == single_exit (loop)->dest)
    update_e = EDGE_PRED (preheader, 0);
  else
    update_e = EDGE_PRED (preheader, 1);

  /* Update IVs of original loop as if they were advanced 
     by ratio_mult_vf_name steps.  */
  vect_update_ivs_after_vectorizer (loop_vinfo, ratio_mult_vf_name, update_e); 

  /* After peeling we have to reset scalar evolution analyzer.  */
  scev_reset ();

  free_original_copy_tables ();
}


/* Function vect_gen_niters_for_prolog_loop

   Set the number of iterations for the loop represented by LOOP_VINFO
   to the minimum between LOOP_NITERS (the original iteration count of the loop)
   and the misalignment of DR - the data reference recorded in
   LOOP_VINFO_UNALIGNED_DR (LOOP_VINFO).  As a result, after the execution of 
   this loop, the data reference DR will refer to an aligned location.

   The following computation is generated:

   If the misalignment of DR is known at compile time:
     addr_mis = int mis = DR_MISALIGNMENT (dr);
   Else, compute address misalignment in bytes:
     addr_mis = addr & (vectype_size - 1)

   prolog_niters = min (LOOP_NITERS, ((VF - addr_mis/elem_size)&(VF-1))/step)

   (elem_size = element type size; an element is the scalar element whose type
   is the inner type of the vectype)

   When the step of the data-ref in the loop is not 1 (as in interleaved data
   and SLP), the number of iterations of the prolog must be divided by the step
   (which is equal to the size of interleaved group).

   The above formulas assume that VF == number of elements in the vector. This
   may not hold when there are multiple-types in the loop.
   In this case, for some data-references in the loop the VF does not represent
   the number of elements that fit in the vector.  Therefore, instead of VF we
   use TYPE_VECTOR_SUBPARTS.  */

static tree 
vect_gen_niters_for_prolog_loop (loop_vec_info loop_vinfo, tree loop_niters)
{
  struct data_reference *dr = LOOP_VINFO_UNALIGNED_DR (loop_vinfo);
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  tree var;
  gimple_seq stmts;
  tree iters, iters_name;
  edge pe;
  basic_block new_bb;
  gimple dr_stmt = DR_STMT (dr);
  stmt_vec_info stmt_info = vinfo_for_stmt (dr_stmt);
  tree vectype = STMT_VINFO_VECTYPE (stmt_info);
  int vectype_align = TYPE_ALIGN (vectype) / BITS_PER_UNIT;
  tree niters_type = TREE_TYPE (loop_niters);
  int step = 1;
  int element_size = GET_MODE_SIZE (TYPE_MODE (TREE_TYPE (DR_REF (dr))));
  int nelements = TYPE_VECTOR_SUBPARTS (vectype);

  if (STMT_VINFO_STRIDED_ACCESS (stmt_info))
    step = DR_GROUP_SIZE (vinfo_for_stmt (DR_GROUP_FIRST_DR (stmt_info)));

  pe = loop_preheader_edge (loop); 

  if (LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo) > 0)
    {
      int byte_misalign = LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo);
      int elem_misalign = byte_misalign / element_size;

      if (vect_print_dump_info (REPORT_DETAILS))
        fprintf (vect_dump, "known alignment = %d.", byte_misalign);

      iters = build_int_cst (niters_type,
                     (((nelements - elem_misalign) & (nelements - 1)) / step));
    }
  else
    {
      gimple_seq new_stmts = NULL;
      tree start_addr = vect_create_addr_base_for_vector_ref (dr_stmt, 
                                                &new_stmts, NULL_TREE, loop);
      tree ptr_type = TREE_TYPE (start_addr);
      tree size = TYPE_SIZE (ptr_type);
      tree type = lang_hooks.types.type_for_size (tree_low_cst (size, 1), 1);
      tree vectype_size_minus_1 = build_int_cst (type, vectype_align - 1);
      tree elem_size_log =
        build_int_cst (type, exact_log2 (vectype_align/nelements));
      tree nelements_minus_1 = build_int_cst (type, nelements - 1);
      tree nelements_tree = build_int_cst (type, nelements);
      tree byte_misalign;
      tree elem_misalign;

      new_bb = gsi_insert_seq_on_edge_immediate (pe, new_stmts);
      gcc_assert (!new_bb);
  
      /* Create:  byte_misalign = addr & (vectype_size - 1)  */
      byte_misalign = 
        fold_build2 (BIT_AND_EXPR, type, fold_convert (type, start_addr), vectype_size_minus_1);
  
      /* Create:  elem_misalign = byte_misalign / element_size  */
      elem_misalign =
        fold_build2 (RSHIFT_EXPR, type, byte_misalign, elem_size_log);

      /* Create:  (niters_type) (nelements - elem_misalign)&(nelements - 1)  */
      iters = fold_build2 (MINUS_EXPR, type, nelements_tree, elem_misalign);
      iters = fold_build2 (BIT_AND_EXPR, type, iters, nelements_minus_1);
      iters = fold_convert (niters_type, iters);
    }

  /* Create:  prolog_loop_niters = min (iters, loop_niters) */
  /* If the loop bound is known at compile time we already verified that it is
     greater than vf; since the misalignment ('iters') is at most vf, there's
     no need to generate the MIN_EXPR in this case.  */
  if (TREE_CODE (loop_niters) != INTEGER_CST)
    iters = fold_build2 (MIN_EXPR, niters_type, iters, loop_niters);

  if (vect_print_dump_info (REPORT_DETAILS))
    {
      fprintf (vect_dump, "niters for prolog loop: ");
      print_generic_expr (vect_dump, iters, TDF_SLIM);
    }

  var = create_tmp_var (niters_type, "prolog_loop_niters");
  add_referenced_var (var);
  stmts = NULL;
  iters_name = force_gimple_operand (iters, &stmts, false, var);

  /* Insert stmt on loop preheader edge.  */
  if (stmts)
    {
      basic_block new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts);
      gcc_assert (!new_bb);
    }

  return iters_name; 
}


/* Function vect_update_init_of_dr

   NITERS iterations were peeled from LOOP.  DR represents a data reference
   in LOOP.  This function updates the information recorded in DR to
   account for the fact that the first NITERS iterations had already been 
   executed.  Specifically, it updates the OFFSET field of DR.  */

static void
vect_update_init_of_dr (struct data_reference *dr, tree niters)
{
  tree offset = DR_OFFSET (dr);
      
  niters = fold_build2 (MULT_EXPR, sizetype,
                        fold_convert (sizetype, niters),
                        fold_convert (sizetype, DR_STEP (dr)));
  offset = fold_build2 (PLUS_EXPR, sizetype, offset, niters);
  DR_OFFSET (dr) = offset;
}


/* Function vect_update_inits_of_drs

   NITERS iterations were peeled from the loop represented by LOOP_VINFO.  
   This function updates the information recorded for the data references in 
   the loop to account for the fact that the first NITERS iterations had 
   already been executed.  Specifically, it updates the initial_condition of
   the access_function of all the data_references in the loop.  */

static void
vect_update_inits_of_drs (loop_vec_info loop_vinfo, tree niters)
{
  unsigned int i;
  VEC (data_reference_p, heap) *datarefs = LOOP_VINFO_DATAREFS (loop_vinfo);
  struct data_reference *dr;

  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "=== vect_update_inits_of_dr ===");

  for (i = 0; VEC_iterate (data_reference_p, datarefs, i, dr); i++)
    vect_update_init_of_dr (dr, niters);
}


/* Function vect_do_peeling_for_alignment

   Peel the first 'niters' iterations of the loop represented by LOOP_VINFO.
   'niters' is set to the misalignment of one of the data references in the
   loop, thereby forcing it to refer to an aligned location at the beginning
   of the execution of this loop.  The data reference for which we are
   peeling is recorded in LOOP_VINFO_UNALIGNED_DR.  */

static void
vect_do_peeling_for_alignment (loop_vec_info loop_vinfo)
{
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  tree niters_of_prolog_loop, ni_name;
  tree n_iters;
  struct loop *new_loop;
  bool check_profitability = false;
  unsigned int th = 0;
  int min_profitable_iters;

  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "=== vect_do_peeling_for_alignment ===");

  initialize_original_copy_tables ();

  ni_name = vect_build_loop_niters (loop_vinfo);
  niters_of_prolog_loop = vect_gen_niters_for_prolog_loop (loop_vinfo, ni_name);
  

  /* If cost model check not done during versioning.  */
  if (!VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo))
      && !VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo)))
    {
      check_profitability = true;

      /* Get profitability threshold for vectorized loop.  */
      min_profitable_iters = LOOP_VINFO_COST_MODEL_MIN_ITERS (loop_vinfo);

      th = conservative_cost_threshold (loop_vinfo, 
                                        min_profitable_iters);
    }

  /* Peel the prolog loop and iterate it niters_of_prolog_loop.  */
  new_loop =
    slpeel_tree_peel_loop_to_edge (loop, loop_preheader_edge (loop),
                                   niters_of_prolog_loop, ni_name, true,
                                   th, check_profitability);

  gcc_assert (new_loop);
#ifdef ENABLE_CHECKING
  slpeel_verify_cfg_after_peeling (new_loop, loop);
#endif

  /* Update number of times loop executes.  */
  n_iters = LOOP_VINFO_NITERS (loop_vinfo);
  LOOP_VINFO_NITERS (loop_vinfo) = fold_build2 (MINUS_EXPR,
                TREE_TYPE (n_iters), n_iters, niters_of_prolog_loop);

  /* Update the init conditions of the access functions of all data refs.  */
  vect_update_inits_of_drs (loop_vinfo, niters_of_prolog_loop);

  /* After peeling we have to reset scalar evolution analyzer.  */
  scev_reset ();

  free_original_copy_tables ();
}


/* Function vect_create_cond_for_align_checks.

   Create a conditional expression that represents the alignment checks for
   all of data references (array element references) whose alignment must be
   checked at runtime.

   Input:
   COND_EXPR  - input conditional expression.  New conditions will be chained
                with logical AND operation.
   LOOP_VINFO - two fields of the loop information are used.
                LOOP_VINFO_PTR_MASK is the mask used to check the alignment.
                LOOP_VINFO_MAY_MISALIGN_STMTS contains the refs to be checked.

   Output:
   COND_EXPR_STMT_LIST - statements needed to construct the conditional
                         expression.
   The returned value is the conditional expression to be used in the if
   statement that controls which version of the loop gets executed at runtime.

   The algorithm makes two assumptions:
     1) The number of bytes "n" in a vector is a power of 2.
     2) An address "a" is aligned if a%n is zero and that this
        test can be done as a&(n-1) == 0.  For example, for 16
        byte vectors the test is a&0xf == 0.  */

static void
vect_create_cond_for_align_checks (loop_vec_info loop_vinfo,
                                   tree *cond_expr,
                                   gimple_seq *cond_expr_stmt_list)
{
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  VEC(gimple,heap) *may_misalign_stmts
    = LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo);
  gimple ref_stmt;
  int mask = LOOP_VINFO_PTR_MASK (loop_vinfo);
  tree mask_cst;
  unsigned int i;
  tree psize;
  tree int_ptrsize_type;
  char tmp_name[20];
  tree or_tmp_name = NULL_TREE;
  tree and_tmp, and_tmp_name;
  gimple and_stmt;
  tree ptrsize_zero;
  tree part_cond_expr;

  /* Check that mask is one less than a power of 2, i.e., mask is
     all zeros followed by all ones.  */
  gcc_assert ((mask != 0) && ((mask & (mask+1)) == 0));

  /* CHECKME: what is the best integer or unsigned type to use to hold a
     cast from a pointer value?  */
  psize = TYPE_SIZE (ptr_type_node);
  int_ptrsize_type
    = lang_hooks.types.type_for_size (tree_low_cst (psize, 1), 0);

  /* Create expression (mask & (dr_1 || ... || dr_n)) where dr_i is the address
     of the first vector of the i'th data reference. */

  for (i = 0; VEC_iterate (gimple, may_misalign_stmts, i, ref_stmt); i++)
    {
      gimple_seq new_stmt_list = NULL;
      tree addr_base;
      tree addr_tmp, addr_tmp_name;
      tree or_tmp, new_or_tmp_name;
      gimple addr_stmt, or_stmt;

      /* create: addr_tmp = (int)(address_of_first_vector) */
      addr_base =
        vect_create_addr_base_for_vector_ref (ref_stmt, &new_stmt_list,
                                              NULL_TREE, loop);
      if (new_stmt_list != NULL)
        gimple_seq_add_seq (cond_expr_stmt_list, new_stmt_list);

      sprintf (tmp_name, "%s%d", "addr2int", i);
      addr_tmp = create_tmp_var (int_ptrsize_type, tmp_name);
      add_referenced_var (addr_tmp);
      addr_tmp_name = make_ssa_name (addr_tmp, NULL);
      addr_stmt = gimple_build_assign_with_ops (NOP_EXPR, addr_tmp_name,
                                                addr_base, NULL_TREE);
      SSA_NAME_DEF_STMT (addr_tmp_name) = addr_stmt;
      gimple_seq_add_stmt (cond_expr_stmt_list, addr_stmt);

      /* The addresses are OR together.  */

      if (or_tmp_name != NULL_TREE)
        {
          /* create: or_tmp = or_tmp | addr_tmp */
          sprintf (tmp_name, "%s%d", "orptrs", i);
          or_tmp = create_tmp_var (int_ptrsize_type, tmp_name);
          add_referenced_var (or_tmp);
          new_or_tmp_name = make_ssa_name (or_tmp, NULL);
          or_stmt = gimple_build_assign_with_ops (BIT_IOR_EXPR,
                                                  new_or_tmp_name,
                                                  or_tmp_name, addr_tmp_name);
          SSA_NAME_DEF_STMT (new_or_tmp_name) = or_stmt;
          gimple_seq_add_stmt (cond_expr_stmt_list, or_stmt);
          or_tmp_name = new_or_tmp_name;
        }
      else
        or_tmp_name = addr_tmp_name;

    } /* end for i */

  mask_cst = build_int_cst (int_ptrsize_type, mask);

  /* create: and_tmp = or_tmp & mask  */
  and_tmp = create_tmp_var (int_ptrsize_type, "andmask" );
  add_referenced_var (and_tmp);
  and_tmp_name = make_ssa_name (and_tmp, NULL);

  and_stmt = gimple_build_assign_with_ops (BIT_AND_EXPR, and_tmp_name,
                                           or_tmp_name, mask_cst);
  SSA_NAME_DEF_STMT (and_tmp_name) = and_stmt;
  gimple_seq_add_stmt (cond_expr_stmt_list, and_stmt);

  /* Make and_tmp the left operand of the conditional test against zero.
     if and_tmp has a nonzero bit then some address is unaligned.  */
  ptrsize_zero = build_int_cst (int_ptrsize_type, 0);
  part_cond_expr = fold_build2 (EQ_EXPR, boolean_type_node,
                                and_tmp_name, ptrsize_zero);
  if (*cond_expr)
    *cond_expr = fold_build2 (TRUTH_AND_EXPR, boolean_type_node,
                              *cond_expr, part_cond_expr);
  else
    *cond_expr = part_cond_expr;
}

/* Function vect_vfa_segment_size.

   Create an expression that computes the size of segment
   that will be accessed for a data reference.  The functions takes into
   account that realignment loads may access one more vector.

   Input:
     DR: The data reference.
     VECT_FACTOR: vectorization factor.

   Return an expression whose value is the size of segment which will be
   accessed by DR.  */

static tree
vect_vfa_segment_size (struct data_reference *dr, tree vect_factor)
{
  tree segment_length = fold_build2 (MULT_EXPR, integer_type_node,
                                     DR_STEP (dr), vect_factor);

  if (vect_supportable_dr_alignment (dr) == dr_explicit_realign_optimized)
    {
      tree vector_size = TYPE_SIZE_UNIT
                          (STMT_VINFO_VECTYPE (vinfo_for_stmt (DR_STMT (dr))));

      segment_length = fold_build2 (PLUS_EXPR, integer_type_node,
                                    segment_length, vector_size);
    }
  return fold_convert (sizetype, segment_length);
}

/* Function vect_create_cond_for_alias_checks.

   Create a conditional expression that represents the run-time checks for
   overlapping of address ranges represented by a list of data references
   relations passed as input.

   Input:
   COND_EXPR  - input conditional expression.  New conditions will be chained
                with logical AND operation.
   LOOP_VINFO - field LOOP_VINFO_MAY_ALIAS_STMTS contains the list of ddrs
                to be checked.

   Output:
   COND_EXPR - conditional expression.
   COND_EXPR_STMT_LIST - statements needed to construct the conditional
                         expression.


   The returned value is the conditional expression to be used in the if
   statement that controls which version of the loop gets executed at runtime.
*/

static void
vect_create_cond_for_alias_checks (loop_vec_info loop_vinfo,
                                   tree * cond_expr,
                                   gimple_seq * cond_expr_stmt_list)
{
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  VEC (ddr_p, heap) * may_alias_ddrs =
    LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo);
  tree vect_factor =
    build_int_cst (integer_type_node, LOOP_VINFO_VECT_FACTOR (loop_vinfo));

  ddr_p ddr;
  unsigned int i;
  tree part_cond_expr;

  /* Create expression
     ((store_ptr_0 + store_segment_length_0) < load_ptr_0)
     || (load_ptr_0 + load_segment_length_0) < store_ptr_0))
     &&         
     ...
     &&
     ((store_ptr_n + store_segment_length_n) < load_ptr_n)
     || (load_ptr_n + load_segment_length_n) < store_ptr_n))  */

  if (VEC_empty (ddr_p, may_alias_ddrs))
    return;

  for (i = 0; VEC_iterate (ddr_p, may_alias_ddrs, i, ddr); i++)
    {
      struct data_reference *dr_a, *dr_b;
      gimple dr_group_first_a, dr_group_first_b;
      tree addr_base_a, addr_base_b;
      tree segment_length_a, segment_length_b;
      gimple stmt_a, stmt_b;

      dr_a = DDR_A (ddr);
      stmt_a = DR_STMT (DDR_A (ddr));
      dr_group_first_a = DR_GROUP_FIRST_DR (vinfo_for_stmt (stmt_a));
      if (dr_group_first_a)
        {
          stmt_a = dr_group_first_a;
          dr_a = STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt_a));
        }

      dr_b = DDR_B (ddr);
      stmt_b = DR_STMT (DDR_B (ddr));
      dr_group_first_b = DR_GROUP_FIRST_DR (vinfo_for_stmt (stmt_b));
      if (dr_group_first_b)
        {
          stmt_b = dr_group_first_b;
          dr_b = STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt_b));
        }

      addr_base_a =
        vect_create_addr_base_for_vector_ref (stmt_a, cond_expr_stmt_list,
                                              NULL_TREE, loop);
      addr_base_b =
        vect_create_addr_base_for_vector_ref (stmt_b, cond_expr_stmt_list,
                                              NULL_TREE, loop);

      segment_length_a = vect_vfa_segment_size (dr_a, vect_factor);
      segment_length_b = vect_vfa_segment_size (dr_b, vect_factor);

      if (vect_print_dump_info (REPORT_DR_DETAILS))
        {
          fprintf (vect_dump,
                   "create runtime check for data references ");
          print_generic_expr (vect_dump, DR_REF (dr_a), TDF_SLIM);
          fprintf (vect_dump, " and ");
          print_generic_expr (vect_dump, DR_REF (dr_b), TDF_SLIM);
        }


      part_cond_expr = 
        fold_build2 (TRUTH_OR_EXPR, boolean_type_node,
          fold_build2 (LT_EXPR, boolean_type_node,
            fold_build2 (POINTER_PLUS_EXPR, TREE_TYPE (addr_base_a),
              addr_base_a,
              segment_length_a),
            addr_base_b),
          fold_build2 (LT_EXPR, boolean_type_node,
            fold_build2 (POINTER_PLUS_EXPR, TREE_TYPE (addr_base_b),
              addr_base_b,
              segment_length_b),
            addr_base_a));
      
      if (*cond_expr)
        *cond_expr = fold_build2 (TRUTH_AND_EXPR, boolean_type_node,
                                  *cond_expr, part_cond_expr);
      else
        *cond_expr = part_cond_expr;
    }
    if (vect_print_dump_info (REPORT_VECTORIZED_LOOPS))
      fprintf (vect_dump, "created %u versioning for alias checks.\n",
               VEC_length (ddr_p, may_alias_ddrs));

}

/* Function vect_loop_versioning.
 
   If the loop has data references that may or may not be aligned or/and
   has data reference relations whose independence was not proven then
   two versions of the loop need to be generated, one which is vectorized
   and one which isn't.  A test is then generated to control which of the
   loops is executed.  The test checks for the alignment of all of the
   data references that may or may not be aligned.  An additional
   sequence of runtime tests is generated for each pairs of DDRs whose
   independence was not proven.  The vectorized version of loop is 
   executed only if both alias and alignment tests are passed.  
  
   The test generated to check which version of loop is executed
   is modified to also check for profitability as indicated by the 
   cost model initially.  */

static void
vect_loop_versioning (loop_vec_info loop_vinfo)
{
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  struct loop *nloop;
  tree cond_expr = NULL_TREE;
  gimple_seq cond_expr_stmt_list = NULL;
  basic_block condition_bb;
  gimple_stmt_iterator gsi, cond_exp_gsi;
  basic_block merge_bb;
  basic_block new_exit_bb;
  edge new_exit_e, e;
  gimple orig_phi, new_phi;
  tree arg;
  unsigned prob = 4 * REG_BR_PROB_BASE / 5;
  gimple_seq gimplify_stmt_list = NULL;
  tree scalar_loop_iters = LOOP_VINFO_NITERS (loop_vinfo);
  int min_profitable_iters = 0;
  unsigned int th;

  /* Get profitability threshold for vectorized loop.  */
  min_profitable_iters = LOOP_VINFO_COST_MODEL_MIN_ITERS (loop_vinfo);

  th = conservative_cost_threshold (loop_vinfo,
                                    min_profitable_iters);

  cond_expr =
    build2 (GT_EXPR, boolean_type_node, scalar_loop_iters, 
            build_int_cst (TREE_TYPE (scalar_loop_iters), th));

  cond_expr = force_gimple_operand (cond_expr, &cond_expr_stmt_list,
                                    false, NULL_TREE);

  if (VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo)))
      vect_create_cond_for_align_checks (loop_vinfo, &cond_expr,
                                         &cond_expr_stmt_list);

  if (VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo)))
    vect_create_cond_for_alias_checks (loop_vinfo, &cond_expr, 
                                       &cond_expr_stmt_list);

  cond_expr =
    fold_build2 (NE_EXPR, boolean_type_node, cond_expr, integer_zero_node);
  cond_expr =
    force_gimple_operand (cond_expr, &gimplify_stmt_list, true, NULL_TREE);
  gimple_seq_add_seq (&cond_expr_stmt_list, gimplify_stmt_list);

  initialize_original_copy_tables ();
  nloop = loop_version (loop, cond_expr, &condition_bb,
                        prob, prob, REG_BR_PROB_BASE - prob, true);
  free_original_copy_tables();

  /* Loop versioning violates an assumption we try to maintain during 
     vectorization - that the loop exit block has a single predecessor.
     After versioning, the exit block of both loop versions is the same
     basic block (i.e. it has two predecessors). Just in order to simplify
     following transformations in the vectorizer, we fix this situation
     here by adding a new (empty) block on the exit-edge of the loop,
     with the proper loop-exit phis to maintain loop-closed-form.  */
  
  merge_bb = single_exit (loop)->dest;
  gcc_assert (EDGE_COUNT (merge_bb->preds) == 2);
  new_exit_bb = split_edge (single_exit (loop));
  new_exit_e = single_exit (loop);
  e = EDGE_SUCC (new_exit_bb, 0);

  for (gsi = gsi_start_phis (merge_bb); !gsi_end_p (gsi); gsi_next (&gsi))
    {
      orig_phi = gsi_stmt (gsi);
      new_phi = create_phi_node (SSA_NAME_VAR (PHI_RESULT (orig_phi)),
                                  new_exit_bb);
      arg = PHI_ARG_DEF_FROM_EDGE (orig_phi, e);
      add_phi_arg (new_phi, arg, new_exit_e);
      SET_PHI_ARG_DEF (orig_phi, e->dest_idx, PHI_RESULT (new_phi));
    } 

  /* End loop-exit-fixes after versioning.  */

  update_ssa (TODO_update_ssa);
  if (cond_expr_stmt_list)
    {
      cond_exp_gsi = gsi_last_bb (condition_bb);
      gsi_insert_seq_before (&cond_exp_gsi, cond_expr_stmt_list, GSI_SAME_STMT);
    }
}

/* Remove a group of stores (for SLP or interleaving), free their 
   stmt_vec_info.  */

static void
vect_remove_stores (gimple first_stmt)
{
  gimple next = first_stmt;
  gimple tmp;
  gimple_stmt_iterator next_si;

  while (next)
    {
      /* Free the attached stmt_vec_info and remove the stmt.  */
      next_si = gsi_for_stmt (next);
      gsi_remove (&next_si, true);
      tmp = DR_GROUP_NEXT_DR (vinfo_for_stmt (next));
      free_stmt_vec_info (next);
      next = tmp;
    }
}


/* Vectorize SLP instance tree in postorder.  */

static bool
vect_schedule_slp_instance (slp_tree node, slp_instance instance,
                            unsigned int vectorization_factor) 
{
  gimple stmt;
  bool strided_store, is_store;
  gimple_stmt_iterator si;
  stmt_vec_info stmt_info;
  unsigned int vec_stmts_size, nunits, group_size;
  tree vectype;
  int i;
  slp_tree loads_node;

  if (!node)
    return false;

  vect_schedule_slp_instance (SLP_TREE_LEFT (node), instance,
                              vectorization_factor);
  vect_schedule_slp_instance (SLP_TREE_RIGHT (node), instance,
                              vectorization_factor);
  
  stmt = VEC_index (gimple, SLP_TREE_SCALAR_STMTS (node), 0);
  stmt_info = vinfo_for_stmt (stmt);

  /* VECTYPE is the type of the destination.  */
  vectype = get_vectype_for_scalar_type (TREE_TYPE (gimple_assign_lhs (stmt)));
  nunits = (unsigned int) TYPE_VECTOR_SUBPARTS (vectype);
  group_size = SLP_INSTANCE_GROUP_SIZE (instance);

  /* For each SLP instance calculate number of vector stmts to be created
     for the scalar stmts in each node of the SLP tree. Number of vector
     elements in one vector iteration is the number of scalar elements in
     one scalar iteration (GROUP_SIZE) multiplied by VF divided by vector
     size.  */
  vec_stmts_size = (vectorization_factor * group_size) / nunits;

  /* In case of load permutation we have to allocate vectorized statements for
     all the nodes that participate in that permutation.  */
  if (SLP_INSTANCE_LOAD_PERMUTATION (instance))
    {
      for (i = 0;
           VEC_iterate (slp_tree, SLP_INSTANCE_LOADS (instance), i, loads_node);
           i++)
        {
          if (!SLP_TREE_VEC_STMTS (loads_node))
            {
              SLP_TREE_VEC_STMTS (loads_node) = VEC_alloc (gimple, heap,
                                                           vec_stmts_size);
              SLP_TREE_NUMBER_OF_VEC_STMTS (loads_node) = vec_stmts_size;
            }
        }
    }

  if (!SLP_TREE_VEC_STMTS (node))
    {
      SLP_TREE_VEC_STMTS (node) = VEC_alloc (gimple, heap, vec_stmts_size);
      SLP_TREE_NUMBER_OF_VEC_STMTS (node) = vec_stmts_size;
    }

  if (vect_print_dump_info (REPORT_DETAILS))
    {
      fprintf (vect_dump, "------>vectorizing SLP node starting from: ");
      print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
    }   

  /* Loads should be inserted before the first load.  */
  if (SLP_INSTANCE_FIRST_LOAD_STMT (instance)
      && STMT_VINFO_STRIDED_ACCESS (stmt_info)
      && !REFERENCE_CLASS_P (gimple_get_lhs (stmt)))
    si = gsi_for_stmt (SLP_INSTANCE_FIRST_LOAD_STMT (instance));
  else
    si = gsi_for_stmt (stmt);

  is_store = vect_transform_stmt (stmt, &si, &strided_store, node, instance);
  if (is_store)
    {
      if (DR_GROUP_FIRST_DR (stmt_info))
        /* If IS_STORE is TRUE, the vectorization of the
           interleaving chain was completed - free all the stores in
           the chain.  */
        vect_remove_stores (DR_GROUP_FIRST_DR (stmt_info));
      else
        /* FORNOW: SLP originates only from strided stores.  */
        gcc_unreachable ();

      return true;
    }

  /* FORNOW: SLP originates only from strided stores.  */
  return false;
}


static bool
vect_schedule_slp (loop_vec_info loop_vinfo)
{
  VEC (slp_instance, heap) *slp_instances = 
    LOOP_VINFO_SLP_INSTANCES (loop_vinfo);
  slp_instance instance;
  unsigned int i;
  bool is_store = false;

  for (i = 0; VEC_iterate (slp_instance, slp_instances, i, instance); i++)
    {
      /* Schedule the tree of INSTANCE.  */
      is_store = vect_schedule_slp_instance (SLP_INSTANCE_TREE (instance),
                            instance, LOOP_VINFO_VECT_FACTOR (loop_vinfo));
                          
      if (vect_print_dump_info (REPORT_VECTORIZED_LOOPS)
          || vect_print_dump_info (REPORT_UNVECTORIZED_LOOPS))
        fprintf (vect_dump, "vectorizing stmts using SLP.");
    }

  return is_store;
}

/* Function vect_transform_loop.

   The analysis phase has determined that the loop is vectorizable.
   Vectorize the loop - created vectorized stmts to replace the scalar
   stmts in the loop, and update the loop exit condition.  */

void
vect_transform_loop (loop_vec_info loop_vinfo)
{
  struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
  basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
  int nbbs = loop->num_nodes;
  gimple_stmt_iterator si;
  int i;
  tree ratio = NULL;
  int vectorization_factor = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
  bool strided_store;
  bool slp_scheduled = false;
  unsigned int nunits;

  if (vect_print_dump_info (REPORT_DETAILS))
    fprintf (vect_dump, "=== vec_transform_loop ===");

  if (VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo))
      || VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo)))
    vect_loop_versioning (loop_vinfo);

  /* CHECKME: we wouldn't need this if we called update_ssa once
     for all loops.  */
  bitmap_zero (vect_memsyms_to_rename);

  /* Peel the loop if there are data refs with unknown alignment.
     Only one data ref with unknown store is allowed.  */

  if (LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo))
    vect_do_peeling_for_alignment (loop_vinfo);
  
  /* If the loop has a symbolic number of iterations 'n' (i.e. it's not a
     compile time constant), or it is a constant that doesn't divide by the
     vectorization factor, then an epilog loop needs to be created.
     We therefore duplicate the loop: the original loop will be vectorized,
     and will compute the first (n/VF) iterations. The second copy of the loop
     will remain scalar and will compute the remaining (n%VF) iterations.
     (VF is the vectorization factor).  */

  if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
      || (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
          && LOOP_VINFO_INT_NITERS (loop_vinfo) % vectorization_factor != 0))
    vect_do_peeling_for_loop_bound (loop_vinfo, &ratio);
  else
    ratio = build_int_cst (TREE_TYPE (LOOP_VINFO_NITERS (loop_vinfo)),
                LOOP_VINFO_INT_NITERS (loop_vinfo) / vectorization_factor);

  /* 1) Make sure the loop header has exactly two entries
     2) Make sure we have a preheader basic block.  */

  gcc_assert (EDGE_COUNT (loop->header->preds) == 2);

  split_edge (loop_preheader_edge (loop));

  /* FORNOW: the vectorizer supports only loops which body consist
     of one basic block (header + empty latch). When the vectorizer will 
     support more involved loop forms, the order by which the BBs are 
     traversed need to be reconsidered.  */

  for (i = 0; i < nbbs; i++)
    {
      basic_block bb = bbs[i];
      stmt_vec_info stmt_info;
      gimple phi;

      for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
        {
          phi = gsi_stmt (si);
          if (vect_print_dump_info (REPORT_DETAILS))
            {
              fprintf (vect_dump, "------>vectorizing phi: ");
              print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
            }
          stmt_info = vinfo_for_stmt (phi);
          if (!stmt_info)
            continue;

          if (!STMT_VINFO_RELEVANT_P (stmt_info)
              && !STMT_VINFO_LIVE_P (stmt_info))
            continue;

          if ((TYPE_VECTOR_SUBPARTS (STMT_VINFO_VECTYPE (stmt_info))
                != (unsigned HOST_WIDE_INT) vectorization_factor)
              && vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "multiple-types.");

          if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def)
            {
              if (vect_print_dump_info (REPORT_DETAILS))
                fprintf (vect_dump, "transform phi.");
              vect_transform_stmt (phi, NULL, NULL, NULL, NULL);
            }
        }

      for (si = gsi_start_bb (bb); !gsi_end_p (si);)
        {
          gimple stmt = gsi_stmt (si);
          bool is_store;

          if (vect_print_dump_info (REPORT_DETAILS))
            {
              fprintf (vect_dump, "------>vectorizing statement: ");
              print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
            }   

          stmt_info = vinfo_for_stmt (stmt);

          /* vector stmts created in the outer-loop during vectorization of
             stmts in an inner-loop may not have a stmt_info, and do not
             need to be vectorized.  */
          if (!stmt_info)
            {
              gsi_next (&si);
              continue;
            }

          if (!STMT_VINFO_RELEVANT_P (stmt_info)
              && !STMT_VINFO_LIVE_P (stmt_info))
            {
              gsi_next (&si);
              continue;
            }

          gcc_assert (STMT_VINFO_VECTYPE (stmt_info));
          nunits =
            (unsigned int) TYPE_VECTOR_SUBPARTS (STMT_VINFO_VECTYPE (stmt_info));
          if (!STMT_SLP_TYPE (stmt_info)
              && nunits != (unsigned int) vectorization_factor
              && vect_print_dump_info (REPORT_DETAILS))
            /* For SLP VF is set according to unrolling factor, and not to
               vector size, hence for SLP this print is not valid.  */
            fprintf (vect_dump, "multiple-types.");

          /* SLP. Schedule all the SLP instances when the first SLP stmt is
             reached.  */
          if (STMT_SLP_TYPE (stmt_info))
            {
              if (!slp_scheduled)
                {
                  slp_scheduled = true;

                  if (vect_print_dump_info (REPORT_DETAILS))
                    fprintf (vect_dump, "=== scheduling SLP instances ===");

                  is_store = vect_schedule_slp (loop_vinfo);

                  /* IS_STORE is true if STMT is a store. Stores cannot be of
                     hybrid SLP type. They are removed in
                     vect_schedule_slp_instance and their vinfo is destroyed. */
                  if (is_store)
                    {
                      gsi_next (&si);
                      continue;
                    }
                }

              /* Hybrid SLP stmts must be vectorized in addition to SLP.  */
              if (PURE_SLP_STMT (stmt_info))
                {
                  gsi_next (&si);
                  continue;
                }
            }
          
          /* -------- vectorize statement ------------ */
          if (vect_print_dump_info (REPORT_DETAILS))
            fprintf (vect_dump, "transform statement.");

          strided_store = false;
          is_store = vect_transform_stmt (stmt, &si, &strided_store, NULL, NULL);
          if (is_store)
            {
              if (STMT_VINFO_STRIDED_ACCESS (stmt_info))
                {
                  /* Interleaving. If IS_STORE is TRUE, the vectorization of the
                     interleaving chain was completed - free all the stores in
                     the chain.  */
                  vect_remove_stores (DR_GROUP_FIRST_DR (stmt_info));
                  gsi_remove (&si, true);
                  continue;
                }
              else
                {
                  /* Free the attached stmt_vec_info and remove the stmt.  */
                  free_stmt_vec_info (stmt);
                  gsi_remove (&si, true);
                  continue;
                }
            }
          gsi_next (&si);
        }                       /* stmts in BB */
    }                           /* BBs in loop */

  slpeel_make_loop_iterate_ntimes (loop, ratio);

  mark_set_for_renaming (vect_memsyms_to_rename);

  /* The memory tags and pointers in vectorized statements need to
     have their SSA forms updated.  FIXME, why can't this be delayed
     until all the loops have been transformed?  */
  update_ssa (TODO_update_ssa);

  if (vect_print_dump_info (REPORT_VECTORIZED_LOOPS))
    fprintf (vect_dump, "LOOP VECTORIZED.");
  if (loop->inner && vect_print_dump_info (REPORT_VECTORIZED_LOOPS))
    fprintf (vect_dump, "OUTER LOOP VECTORIZED.");
}