2 Copyright (C) 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010
3 Free Software Foundation, Inc.
4 Contributed by Dorit Naishlos <dorit@il.ibm.com> and
5 Ira Rosen <irar@il.ibm.com>
7 This file is part of GCC.
9 GCC is free software; you can redistribute it and/or modify it under
10 the terms of the GNU General Public License as published by the Free
11 Software Foundation; either version 3, or (at your option) any later
14 GCC is distributed in the hope that it will be useful, but WITHOUT ANY
15 WARRANTY; without even the implied warranty of MERCHANTABILITY or
16 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
19 You should have received a copy of the GNU General Public License
20 along with GCC; see the file COPYING3. If not see
21 <http://www.gnu.org/licenses/>. */
25 #include "coretypes.h"
29 #include "basic-block.h"
30 #include "tree-pretty-print.h"
31 #include "gimple-pretty-print.h"
32 #include "tree-flow.h"
33 #include "tree-dump.h"
35 #include "cfglayout.h"
40 #include "diagnostic-core.h"
41 #include "tree-chrec.h"
42 #include "tree-scalar-evolution.h"
43 #include "tree-vectorizer.h"
46 /* Loop Vectorization Pass.
48 This pass tries to vectorize loops.
50 For example, the vectorizer transforms the following simple loop:
52 short a[N]; short b[N]; short c[N]; int i;
58 as if it was manually vectorized by rewriting the source code into:
60 typedef int __attribute__((mode(V8HI))) v8hi;
61 short a[N]; short b[N]; short c[N]; int i;
62 v8hi *pa = (v8hi*)a, *pb = (v8hi*)b, *pc = (v8hi*)c;
65 for (i=0; i<N/8; i++){
72 The main entry to this pass is vectorize_loops(), in which
73 the vectorizer applies a set of analyses on a given set of loops,
74 followed by the actual vectorization transformation for the loops that
75 had successfully passed the analysis phase.
76 Throughout this pass we make a distinction between two types of
77 data: scalars (which are represented by SSA_NAMES), and memory references
78 ("data-refs"). These two types of data require different handling both
79 during analysis and transformation. The types of data-refs that the
80 vectorizer currently supports are ARRAY_REFS which base is an array DECL
81 (not a pointer), and INDIRECT_REFS through pointers; both array and pointer
82 accesses are required to have a simple (consecutive) access pattern.
86 The driver for the analysis phase is vect_analyze_loop().
87 It applies a set of analyses, some of which rely on the scalar evolution
88 analyzer (scev) developed by Sebastian Pop.
90 During the analysis phase the vectorizer records some information
91 per stmt in a "stmt_vec_info" struct which is attached to each stmt in the
92 loop, as well as general information about the loop as a whole, which is
93 recorded in a "loop_vec_info" struct attached to each loop.
97 The loop transformation phase scans all the stmts in the loop, and
98 creates a vector stmt (or a sequence of stmts) for each scalar stmt S in
99 the loop that needs to be vectorized. It inserts the vector code sequence
100 just before the scalar stmt S, and records a pointer to the vector code
101 in STMT_VINFO_VEC_STMT (stmt_info) (stmt_info is the stmt_vec_info struct
102 attached to S). This pointer will be used for the vectorization of following
103 stmts which use the def of stmt S. Stmt S is removed if it writes to memory;
104 otherwise, we rely on dead code elimination for removing it.
106 For example, say stmt S1 was vectorized into stmt VS1:
109 S1: b = x[i]; STMT_VINFO_VEC_STMT (stmt_info (S1)) = VS1
112 To vectorize stmt S2, the vectorizer first finds the stmt that defines
113 the operand 'b' (S1), and gets the relevant vector def 'vb' from the
114 vector stmt VS1 pointed to by STMT_VINFO_VEC_STMT (stmt_info (S1)). The
115 resulting sequence would be:
118 S1: b = x[i]; STMT_VINFO_VEC_STMT (stmt_info (S1)) = VS1
120 S2: a = b; STMT_VINFO_VEC_STMT (stmt_info (S2)) = VS2
122 Operands that are not SSA_NAMEs, are data-refs that appear in
123 load/store operations (like 'x[i]' in S1), and are handled differently.
127 Currently the only target specific information that is used is the
128 size of the vector (in bytes) - "TARGET_VECTORIZE_UNITS_PER_SIMD_WORD".
129 Targets that can support different sizes of vectors, for now will need
130 to specify one value for "TARGET_VECTORIZE_UNITS_PER_SIMD_WORD". More
131 flexibility will be added in the future.
133 Since we only vectorize operations which vector form can be
134 expressed using existing tree codes, to verify that an operation is
135 supported, the vectorizer checks the relevant optab at the relevant
136 machine_mode (e.g, optab_handler (add_optab, V8HImode)). If
137 the value found is CODE_FOR_nothing, then there's no target support, and
138 we can't vectorize the stmt.
140 For additional information on this project see:
141 http://gcc.gnu.org/projects/tree-ssa/vectorization.html
144 /* Function vect_determine_vectorization_factor
146 Determine the vectorization factor (VF). VF is the number of data elements
147 that are operated upon in parallel in a single iteration of the vectorized
148 loop. For example, when vectorizing a loop that operates on 4byte elements,
149 on a target with vector size (VS) 16byte, the VF is set to 4, since 4
150 elements can fit in a single vector register.
152 We currently support vectorization of loops in which all types operated upon
153 are of the same size. Therefore this function currently sets VF according to
154 the size of the types operated upon, and fails if there are multiple sizes
157 VF is also the factor by which the loop iterations are strip-mined, e.g.:
164 for (i=0; i<N; i+=VF){
165 a[i:VF] = b[i:VF] + c[i:VF];
170 vect_determine_vectorization_factor (loop_vec_info loop_vinfo)
172 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
173 basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
174 int nbbs = loop->num_nodes;
175 gimple_stmt_iterator si;
176 unsigned int vectorization_factor = 0;
181 stmt_vec_info stmt_info;
184 gimple stmt, pattern_stmt = NULL;
185 bool analyze_pattern_stmt = false;
187 if (vect_print_dump_info (REPORT_DETAILS))
188 fprintf (vect_dump, "=== vect_determine_vectorization_factor ===");
190 for (i = 0; i < nbbs; i++)
192 basic_block bb = bbs[i];
194 for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
197 stmt_info = vinfo_for_stmt (phi);
198 if (vect_print_dump_info (REPORT_DETAILS))
200 fprintf (vect_dump, "==> examining phi: ");
201 print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
204 gcc_assert (stmt_info);
206 if (STMT_VINFO_RELEVANT_P (stmt_info))
208 gcc_assert (!STMT_VINFO_VECTYPE (stmt_info));
209 scalar_type = TREE_TYPE (PHI_RESULT (phi));
211 if (vect_print_dump_info (REPORT_DETAILS))
213 fprintf (vect_dump, "get vectype for scalar type: ");
214 print_generic_expr (vect_dump, scalar_type, TDF_SLIM);
217 vectype = get_vectype_for_scalar_type (scalar_type);
220 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
223 "not vectorized: unsupported data-type ");
224 print_generic_expr (vect_dump, scalar_type, TDF_SLIM);
228 STMT_VINFO_VECTYPE (stmt_info) = vectype;
230 if (vect_print_dump_info (REPORT_DETAILS))
232 fprintf (vect_dump, "vectype: ");
233 print_generic_expr (vect_dump, vectype, TDF_SLIM);
236 nunits = TYPE_VECTOR_SUBPARTS (vectype);
237 if (vect_print_dump_info (REPORT_DETAILS))
238 fprintf (vect_dump, "nunits = %d", nunits);
240 if (!vectorization_factor
241 || (nunits > vectorization_factor))
242 vectorization_factor = nunits;
246 for (si = gsi_start_bb (bb); !gsi_end_p (si) || analyze_pattern_stmt;)
250 if (analyze_pattern_stmt)
253 analyze_pattern_stmt = false;
256 stmt = gsi_stmt (si);
258 stmt_info = vinfo_for_stmt (stmt);
260 if (vect_print_dump_info (REPORT_DETAILS))
262 fprintf (vect_dump, "==> examining statement: ");
263 print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
266 gcc_assert (stmt_info);
268 /* Skip stmts which do not need to be vectorized. */
269 if (!STMT_VINFO_RELEVANT_P (stmt_info)
270 && !STMT_VINFO_LIVE_P (stmt_info))
272 if (STMT_VINFO_IN_PATTERN_P (stmt_info)
273 && (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info))
274 && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt))
275 || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt))))
278 stmt_info = vinfo_for_stmt (pattern_stmt);
279 if (vect_print_dump_info (REPORT_DETAILS))
281 fprintf (vect_dump, "==> examining pattern statement: ");
282 print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
287 if (vect_print_dump_info (REPORT_DETAILS))
288 fprintf (vect_dump, "skip.");
293 else if (STMT_VINFO_IN_PATTERN_P (stmt_info)
294 && (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info))
295 && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt))
296 || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt))))
297 analyze_pattern_stmt = true;
299 if (gimple_get_lhs (stmt) == NULL_TREE)
301 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
303 fprintf (vect_dump, "not vectorized: irregular stmt.");
304 print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
309 if (VECTOR_MODE_P (TYPE_MODE (gimple_expr_type (stmt))))
311 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
313 fprintf (vect_dump, "not vectorized: vector stmt in loop:");
314 print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
319 if (STMT_VINFO_VECTYPE (stmt_info))
321 /* The only case when a vectype had been already set is for stmts
322 that contain a dataref, or for "pattern-stmts" (stmts generated
323 by the vectorizer to represent/replace a certain idiom). */
324 gcc_assert (STMT_VINFO_DATA_REF (stmt_info)
325 || is_pattern_stmt_p (stmt_info));
326 vectype = STMT_VINFO_VECTYPE (stmt_info);
330 gcc_assert (!STMT_VINFO_DATA_REF (stmt_info));
331 scalar_type = TREE_TYPE (gimple_get_lhs (stmt));
332 if (vect_print_dump_info (REPORT_DETAILS))
334 fprintf (vect_dump, "get vectype for scalar type: ");
335 print_generic_expr (vect_dump, scalar_type, TDF_SLIM);
337 vectype = get_vectype_for_scalar_type (scalar_type);
340 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
343 "not vectorized: unsupported data-type ");
344 print_generic_expr (vect_dump, scalar_type, TDF_SLIM);
349 STMT_VINFO_VECTYPE (stmt_info) = vectype;
352 /* The vectorization factor is according to the smallest
353 scalar type (or the largest vector size, but we only
354 support one vector size per loop). */
355 scalar_type = vect_get_smallest_scalar_type (stmt, &dummy,
357 if (vect_print_dump_info (REPORT_DETAILS))
359 fprintf (vect_dump, "get vectype for scalar type: ");
360 print_generic_expr (vect_dump, scalar_type, TDF_SLIM);
362 vf_vectype = get_vectype_for_scalar_type (scalar_type);
365 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
368 "not vectorized: unsupported data-type ");
369 print_generic_expr (vect_dump, scalar_type, TDF_SLIM);
374 if ((GET_MODE_SIZE (TYPE_MODE (vectype))
375 != GET_MODE_SIZE (TYPE_MODE (vf_vectype))))
377 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
380 "not vectorized: different sized vector "
381 "types in statement, ");
382 print_generic_expr (vect_dump, vectype, TDF_SLIM);
383 fprintf (vect_dump, " and ");
384 print_generic_expr (vect_dump, vf_vectype, TDF_SLIM);
389 if (vect_print_dump_info (REPORT_DETAILS))
391 fprintf (vect_dump, "vectype: ");
392 print_generic_expr (vect_dump, vf_vectype, TDF_SLIM);
395 nunits = TYPE_VECTOR_SUBPARTS (vf_vectype);
396 if (vect_print_dump_info (REPORT_DETAILS))
397 fprintf (vect_dump, "nunits = %d", nunits);
399 if (!vectorization_factor
400 || (nunits > vectorization_factor))
401 vectorization_factor = nunits;
403 if (!analyze_pattern_stmt)
408 /* TODO: Analyze cost. Decide if worth while to vectorize. */
409 if (vect_print_dump_info (REPORT_DETAILS))
410 fprintf (vect_dump, "vectorization factor = %d", vectorization_factor);
411 if (vectorization_factor <= 1)
413 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
414 fprintf (vect_dump, "not vectorized: unsupported data-type");
417 LOOP_VINFO_VECT_FACTOR (loop_vinfo) = vectorization_factor;
423 /* Function vect_is_simple_iv_evolution.
425 FORNOW: A simple evolution of an induction variables in the loop is
426 considered a polynomial evolution with constant step. */
429 vect_is_simple_iv_evolution (unsigned loop_nb, tree access_fn, tree * init,
434 tree evolution_part = evolution_part_in_loop_num (access_fn, loop_nb);
436 /* When there is no evolution in this loop, the evolution function
438 if (evolution_part == NULL_TREE)
441 /* When the evolution is a polynomial of degree >= 2
442 the evolution function is not "simple". */
443 if (tree_is_chrec (evolution_part))
446 step_expr = evolution_part;
447 init_expr = unshare_expr (initial_condition_in_loop_num (access_fn, loop_nb));
449 if (vect_print_dump_info (REPORT_DETAILS))
451 fprintf (vect_dump, "step: ");
452 print_generic_expr (vect_dump, step_expr, TDF_SLIM);
453 fprintf (vect_dump, ", init: ");
454 print_generic_expr (vect_dump, init_expr, TDF_SLIM);
460 if (TREE_CODE (step_expr) != INTEGER_CST)
462 if (vect_print_dump_info (REPORT_DETAILS))
463 fprintf (vect_dump, "step unknown.");
470 /* Function vect_analyze_scalar_cycles_1.
472 Examine the cross iteration def-use cycles of scalar variables
473 in LOOP. LOOP_VINFO represents the loop that is now being
474 considered for vectorization (can be LOOP, or an outer-loop
478 vect_analyze_scalar_cycles_1 (loop_vec_info loop_vinfo, struct loop *loop)
480 basic_block bb = loop->header;
482 VEC(gimple,heap) *worklist = VEC_alloc (gimple, heap, 64);
483 gimple_stmt_iterator gsi;
486 if (vect_print_dump_info (REPORT_DETAILS))
487 fprintf (vect_dump, "=== vect_analyze_scalar_cycles ===");
489 /* First - identify all inductions. Reduction detection assumes that all the
490 inductions have been identified, therefore, this order must not be
492 for (gsi = gsi_start_phis (bb); !gsi_end_p (gsi); gsi_next (&gsi))
494 gimple phi = gsi_stmt (gsi);
495 tree access_fn = NULL;
496 tree def = PHI_RESULT (phi);
497 stmt_vec_info stmt_vinfo = vinfo_for_stmt (phi);
499 if (vect_print_dump_info (REPORT_DETAILS))
501 fprintf (vect_dump, "Analyze phi: ");
502 print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
505 /* Skip virtual phi's. The data dependences that are associated with
506 virtual defs/uses (i.e., memory accesses) are analyzed elsewhere. */
507 if (!is_gimple_reg (SSA_NAME_VAR (def)))
510 STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_unknown_def_type;
512 /* Analyze the evolution function. */
513 access_fn = analyze_scalar_evolution (loop, def);
515 STRIP_NOPS (access_fn);
516 if (access_fn && vect_print_dump_info (REPORT_DETAILS))
518 fprintf (vect_dump, "Access function of PHI: ");
519 print_generic_expr (vect_dump, access_fn, TDF_SLIM);
523 || !vect_is_simple_iv_evolution (loop->num, access_fn, &dumy, &dumy))
525 VEC_safe_push (gimple, heap, worklist, phi);
529 if (vect_print_dump_info (REPORT_DETAILS))
530 fprintf (vect_dump, "Detected induction.");
531 STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_induction_def;
535 /* Second - identify all reductions and nested cycles. */
536 while (VEC_length (gimple, worklist) > 0)
538 gimple phi = VEC_pop (gimple, worklist);
539 tree def = PHI_RESULT (phi);
540 stmt_vec_info stmt_vinfo = vinfo_for_stmt (phi);
544 if (vect_print_dump_info (REPORT_DETAILS))
546 fprintf (vect_dump, "Analyze phi: ");
547 print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
550 gcc_assert (is_gimple_reg (SSA_NAME_VAR (def)));
551 gcc_assert (STMT_VINFO_DEF_TYPE (stmt_vinfo) == vect_unknown_def_type);
553 nested_cycle = (loop != LOOP_VINFO_LOOP (loop_vinfo));
554 reduc_stmt = vect_force_simple_reduction (loop_vinfo, phi, !nested_cycle,
560 if (vect_print_dump_info (REPORT_DETAILS))
561 fprintf (vect_dump, "Detected double reduction.");
563 STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_double_reduction_def;
564 STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) =
565 vect_double_reduction_def;
571 if (vect_print_dump_info (REPORT_DETAILS))
572 fprintf (vect_dump, "Detected vectorizable nested cycle.");
574 STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_nested_cycle;
575 STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) =
580 if (vect_print_dump_info (REPORT_DETAILS))
581 fprintf (vect_dump, "Detected reduction.");
583 STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_reduction_def;
584 STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) =
586 /* Store the reduction cycles for possible vectorization in
588 VEC_safe_push (gimple, heap,
589 LOOP_VINFO_REDUCTIONS (loop_vinfo),
595 if (vect_print_dump_info (REPORT_DETAILS))
596 fprintf (vect_dump, "Unknown def-use cycle pattern.");
599 VEC_free (gimple, heap, worklist);
603 /* Function vect_analyze_scalar_cycles.
605 Examine the cross iteration def-use cycles of scalar variables, by
606 analyzing the loop-header PHIs of scalar variables. Classify each
607 cycle as one of the following: invariant, induction, reduction, unknown.
608 We do that for the loop represented by LOOP_VINFO, and also to its
609 inner-loop, if exists.
610 Examples for scalar cycles:
625 vect_analyze_scalar_cycles (loop_vec_info loop_vinfo)
627 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
629 vect_analyze_scalar_cycles_1 (loop_vinfo, loop);
631 /* When vectorizing an outer-loop, the inner-loop is executed sequentially.
632 Reductions in such inner-loop therefore have different properties than
633 the reductions in the nest that gets vectorized:
634 1. When vectorized, they are executed in the same order as in the original
635 scalar loop, so we can't change the order of computation when
637 2. FIXME: Inner-loop reductions can be used in the inner-loop, so the
638 current checks are too strict. */
641 vect_analyze_scalar_cycles_1 (loop_vinfo, loop->inner);
644 /* Function vect_get_loop_niters.
646 Determine how many iterations the loop is executed.
647 If an expression that represents the number of iterations
648 can be constructed, place it in NUMBER_OF_ITERATIONS.
649 Return the loop exit condition. */
652 vect_get_loop_niters (struct loop *loop, tree *number_of_iterations)
656 if (vect_print_dump_info (REPORT_DETAILS))
657 fprintf (vect_dump, "=== get_loop_niters ===");
659 niters = number_of_exit_cond_executions (loop);
661 if (niters != NULL_TREE
662 && niters != chrec_dont_know)
664 *number_of_iterations = niters;
666 if (vect_print_dump_info (REPORT_DETAILS))
668 fprintf (vect_dump, "==> get_loop_niters:" );
669 print_generic_expr (vect_dump, *number_of_iterations, TDF_SLIM);
673 return get_loop_exit_condition (loop);
677 /* Function bb_in_loop_p
679 Used as predicate for dfs order traversal of the loop bbs. */
682 bb_in_loop_p (const_basic_block bb, const void *data)
684 const struct loop *const loop = (const struct loop *)data;
685 if (flow_bb_inside_loop_p (loop, bb))
691 /* Function new_loop_vec_info.
693 Create and initialize a new loop_vec_info struct for LOOP, as well as
694 stmt_vec_info structs for all the stmts in LOOP. */
697 new_loop_vec_info (struct loop *loop)
701 gimple_stmt_iterator si;
702 unsigned int i, nbbs;
704 res = (loop_vec_info) xcalloc (1, sizeof (struct _loop_vec_info));
705 LOOP_VINFO_LOOP (res) = loop;
707 bbs = get_loop_body (loop);
709 /* Create/Update stmt_info for all stmts in the loop. */
710 for (i = 0; i < loop->num_nodes; i++)
712 basic_block bb = bbs[i];
714 /* BBs in a nested inner-loop will have been already processed (because
715 we will have called vect_analyze_loop_form for any nested inner-loop).
716 Therefore, for stmts in an inner-loop we just want to update the
717 STMT_VINFO_LOOP_VINFO field of their stmt_info to point to the new
718 loop_info of the outer-loop we are currently considering to vectorize
719 (instead of the loop_info of the inner-loop).
720 For stmts in other BBs we need to create a stmt_info from scratch. */
721 if (bb->loop_father != loop)
724 gcc_assert (loop->inner && bb->loop_father == loop->inner);
725 for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
727 gimple phi = gsi_stmt (si);
728 stmt_vec_info stmt_info = vinfo_for_stmt (phi);
729 loop_vec_info inner_loop_vinfo =
730 STMT_VINFO_LOOP_VINFO (stmt_info);
731 gcc_assert (loop->inner == LOOP_VINFO_LOOP (inner_loop_vinfo));
732 STMT_VINFO_LOOP_VINFO (stmt_info) = res;
734 for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
736 gimple stmt = gsi_stmt (si);
737 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
738 loop_vec_info inner_loop_vinfo =
739 STMT_VINFO_LOOP_VINFO (stmt_info);
740 gcc_assert (loop->inner == LOOP_VINFO_LOOP (inner_loop_vinfo));
741 STMT_VINFO_LOOP_VINFO (stmt_info) = res;
746 /* bb in current nest. */
747 for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
749 gimple phi = gsi_stmt (si);
750 gimple_set_uid (phi, 0);
751 set_vinfo_for_stmt (phi, new_stmt_vec_info (phi, res, NULL));
754 for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
756 gimple stmt = gsi_stmt (si);
757 gimple_set_uid (stmt, 0);
758 set_vinfo_for_stmt (stmt, new_stmt_vec_info (stmt, res, NULL));
763 /* CHECKME: We want to visit all BBs before their successors (except for
764 latch blocks, for which this assertion wouldn't hold). In the simple
765 case of the loop forms we allow, a dfs order of the BBs would the same
766 as reversed postorder traversal, so we are safe. */
769 bbs = XCNEWVEC (basic_block, loop->num_nodes);
770 nbbs = dfs_enumerate_from (loop->header, 0, bb_in_loop_p,
771 bbs, loop->num_nodes, loop);
772 gcc_assert (nbbs == loop->num_nodes);
774 LOOP_VINFO_BBS (res) = bbs;
775 LOOP_VINFO_NITERS (res) = NULL;
776 LOOP_VINFO_NITERS_UNCHANGED (res) = NULL;
777 LOOP_VINFO_COST_MODEL_MIN_ITERS (res) = 0;
778 LOOP_VINFO_VECTORIZABLE_P (res) = 0;
779 LOOP_PEELING_FOR_ALIGNMENT (res) = 0;
780 LOOP_VINFO_VECT_FACTOR (res) = 0;
781 LOOP_VINFO_LOOP_NEST (res) = VEC_alloc (loop_p, heap, 3);
782 LOOP_VINFO_DATAREFS (res) = VEC_alloc (data_reference_p, heap, 10);
783 LOOP_VINFO_DDRS (res) = VEC_alloc (ddr_p, heap, 10 * 10);
784 LOOP_VINFO_UNALIGNED_DR (res) = NULL;
785 LOOP_VINFO_MAY_MISALIGN_STMTS (res) =
786 VEC_alloc (gimple, heap,
787 PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIGNMENT_CHECKS));
788 LOOP_VINFO_MAY_ALIAS_DDRS (res) =
789 VEC_alloc (ddr_p, heap,
790 PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIAS_CHECKS));
791 LOOP_VINFO_STRIDED_STORES (res) = VEC_alloc (gimple, heap, 10);
792 LOOP_VINFO_REDUCTIONS (res) = VEC_alloc (gimple, heap, 10);
793 LOOP_VINFO_REDUCTION_CHAINS (res) = VEC_alloc (gimple, heap, 10);
794 LOOP_VINFO_SLP_INSTANCES (res) = VEC_alloc (slp_instance, heap, 10);
795 LOOP_VINFO_SLP_UNROLLING_FACTOR (res) = 1;
796 LOOP_VINFO_PEELING_HTAB (res) = NULL;
797 LOOP_VINFO_PEELING_FOR_GAPS (res) = false;
803 /* Function destroy_loop_vec_info.
805 Free LOOP_VINFO struct, as well as all the stmt_vec_info structs of all the
806 stmts in the loop. */
809 destroy_loop_vec_info (loop_vec_info loop_vinfo, bool clean_stmts)
814 gimple_stmt_iterator si;
816 VEC (slp_instance, heap) *slp_instances;
817 slp_instance instance;
822 loop = LOOP_VINFO_LOOP (loop_vinfo);
824 bbs = LOOP_VINFO_BBS (loop_vinfo);
825 nbbs = loop->num_nodes;
829 free (LOOP_VINFO_BBS (loop_vinfo));
830 free_data_refs (LOOP_VINFO_DATAREFS (loop_vinfo));
831 free_dependence_relations (LOOP_VINFO_DDRS (loop_vinfo));
832 VEC_free (loop_p, heap, LOOP_VINFO_LOOP_NEST (loop_vinfo));
833 VEC_free (gimple, heap, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo));
834 VEC_free (ddr_p, heap, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo));
841 for (j = 0; j < nbbs; j++)
843 basic_block bb = bbs[j];
844 for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
845 free_stmt_vec_info (gsi_stmt (si));
847 for (si = gsi_start_bb (bb); !gsi_end_p (si); )
849 gimple stmt = gsi_stmt (si);
850 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
854 /* Check if this statement has a related "pattern stmt"
855 (introduced by the vectorizer during the pattern recognition
856 pass). Free pattern's stmt_vec_info. */
857 if (STMT_VINFO_IN_PATTERN_P (stmt_info)
858 && vinfo_for_stmt (STMT_VINFO_RELATED_STMT (stmt_info)))
859 free_stmt_vec_info (STMT_VINFO_RELATED_STMT (stmt_info));
861 /* Free stmt_vec_info. */
862 free_stmt_vec_info (stmt);
869 free (LOOP_VINFO_BBS (loop_vinfo));
870 free_data_refs (LOOP_VINFO_DATAREFS (loop_vinfo));
871 free_dependence_relations (LOOP_VINFO_DDRS (loop_vinfo));
872 VEC_free (loop_p, heap, LOOP_VINFO_LOOP_NEST (loop_vinfo));
873 VEC_free (gimple, heap, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo));
874 VEC_free (ddr_p, heap, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo));
875 slp_instances = LOOP_VINFO_SLP_INSTANCES (loop_vinfo);
876 FOR_EACH_VEC_ELT (slp_instance, slp_instances, j, instance)
877 vect_free_slp_instance (instance);
879 VEC_free (slp_instance, heap, LOOP_VINFO_SLP_INSTANCES (loop_vinfo));
880 VEC_free (gimple, heap, LOOP_VINFO_STRIDED_STORES (loop_vinfo));
881 VEC_free (gimple, heap, LOOP_VINFO_REDUCTIONS (loop_vinfo));
882 VEC_free (gimple, heap, LOOP_VINFO_REDUCTION_CHAINS (loop_vinfo));
884 if (LOOP_VINFO_PEELING_HTAB (loop_vinfo))
885 htab_delete (LOOP_VINFO_PEELING_HTAB (loop_vinfo));
892 /* Function vect_analyze_loop_1.
894 Apply a set of analyses on LOOP, and create a loop_vec_info struct
895 for it. The different analyses will record information in the
896 loop_vec_info struct. This is a subset of the analyses applied in
897 vect_analyze_loop, to be applied on an inner-loop nested in the loop
898 that is now considered for (outer-loop) vectorization. */
901 vect_analyze_loop_1 (struct loop *loop)
903 loop_vec_info loop_vinfo;
905 if (vect_print_dump_info (REPORT_DETAILS))
906 fprintf (vect_dump, "===== analyze_loop_nest_1 =====");
908 /* Check the CFG characteristics of the loop (nesting, entry/exit, etc. */
910 loop_vinfo = vect_analyze_loop_form (loop);
913 if (vect_print_dump_info (REPORT_DETAILS))
914 fprintf (vect_dump, "bad inner-loop form.");
922 /* Function vect_analyze_loop_form.
924 Verify that certain CFG restrictions hold, including:
925 - the loop has a pre-header
926 - the loop has a single entry and exit
927 - the loop exit condition is simple enough, and the number of iterations
928 can be analyzed (a countable loop). */
931 vect_analyze_loop_form (struct loop *loop)
933 loop_vec_info loop_vinfo;
935 tree number_of_iterations = NULL;
936 loop_vec_info inner_loop_vinfo = NULL;
938 if (vect_print_dump_info (REPORT_DETAILS))
939 fprintf (vect_dump, "=== vect_analyze_loop_form ===");
941 /* Different restrictions apply when we are considering an inner-most loop,
942 vs. an outer (nested) loop.
943 (FORNOW. May want to relax some of these restrictions in the future). */
947 /* Inner-most loop. We currently require that the number of BBs is
948 exactly 2 (the header and latch). Vectorizable inner-most loops
959 if (loop->num_nodes != 2)
961 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
962 fprintf (vect_dump, "not vectorized: control flow in loop.");
966 if (empty_block_p (loop->header))
968 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
969 fprintf (vect_dump, "not vectorized: empty loop.");
975 struct loop *innerloop = loop->inner;
978 /* Nested loop. We currently require that the loop is doubly-nested,
979 contains a single inner loop, and the number of BBs is exactly 5.
980 Vectorizable outer-loops look like this:
992 The inner-loop has the properties expected of inner-most loops
993 as described above. */
995 if ((loop->inner)->inner || (loop->inner)->next)
997 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
998 fprintf (vect_dump, "not vectorized: multiple nested loops.");
1002 /* Analyze the inner-loop. */
1003 inner_loop_vinfo = vect_analyze_loop_1 (loop->inner);
1004 if (!inner_loop_vinfo)
1006 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
1007 fprintf (vect_dump, "not vectorized: Bad inner loop.");
1011 if (!expr_invariant_in_loop_p (loop,
1012 LOOP_VINFO_NITERS (inner_loop_vinfo)))
1014 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
1016 "not vectorized: inner-loop count not invariant.");
1017 destroy_loop_vec_info (inner_loop_vinfo, true);
1021 if (loop->num_nodes != 5)
1023 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
1024 fprintf (vect_dump, "not vectorized: control flow in loop.");
1025 destroy_loop_vec_info (inner_loop_vinfo, true);
1029 gcc_assert (EDGE_COUNT (innerloop->header->preds) == 2);
1030 entryedge = EDGE_PRED (innerloop->header, 0);
1031 if (EDGE_PRED (innerloop->header, 0)->src == innerloop->latch)
1032 entryedge = EDGE_PRED (innerloop->header, 1);
1034 if (entryedge->src != loop->header
1035 || !single_exit (innerloop)
1036 || single_exit (innerloop)->dest != EDGE_PRED (loop->latch, 0)->src)
1038 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
1039 fprintf (vect_dump, "not vectorized: unsupported outerloop form.");
1040 destroy_loop_vec_info (inner_loop_vinfo, true);
1044 if (vect_print_dump_info (REPORT_DETAILS))
1045 fprintf (vect_dump, "Considering outer-loop vectorization.");
1048 if (!single_exit (loop)
1049 || EDGE_COUNT (loop->header->preds) != 2)
1051 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
1053 if (!single_exit (loop))
1054 fprintf (vect_dump, "not vectorized: multiple exits.");
1055 else if (EDGE_COUNT (loop->header->preds) != 2)
1056 fprintf (vect_dump, "not vectorized: too many incoming edges.");
1058 if (inner_loop_vinfo)
1059 destroy_loop_vec_info (inner_loop_vinfo, true);
1063 /* We assume that the loop exit condition is at the end of the loop. i.e,
1064 that the loop is represented as a do-while (with a proper if-guard
1065 before the loop if needed), where the loop header contains all the
1066 executable statements, and the latch is empty. */
1067 if (!empty_block_p (loop->latch)
1068 || !gimple_seq_empty_p (phi_nodes (loop->latch)))
1070 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
1071 fprintf (vect_dump, "not vectorized: unexpected loop form.");
1072 if (inner_loop_vinfo)
1073 destroy_loop_vec_info (inner_loop_vinfo, true);
1077 /* Make sure there exists a single-predecessor exit bb: */
1078 if (!single_pred_p (single_exit (loop)->dest))
1080 edge e = single_exit (loop);
1081 if (!(e->flags & EDGE_ABNORMAL))
1083 split_loop_exit_edge (e);
1084 if (vect_print_dump_info (REPORT_DETAILS))
1085 fprintf (vect_dump, "split exit edge.");
1089 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
1090 fprintf (vect_dump, "not vectorized: abnormal loop exit edge.");
1091 if (inner_loop_vinfo)
1092 destroy_loop_vec_info (inner_loop_vinfo, true);
1097 loop_cond = vect_get_loop_niters (loop, &number_of_iterations);
1100 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
1101 fprintf (vect_dump, "not vectorized: complicated exit condition.");
1102 if (inner_loop_vinfo)
1103 destroy_loop_vec_info (inner_loop_vinfo, true);
1107 if (!number_of_iterations)
1109 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
1111 "not vectorized: number of iterations cannot be computed.");
1112 if (inner_loop_vinfo)
1113 destroy_loop_vec_info (inner_loop_vinfo, true);
1117 if (chrec_contains_undetermined (number_of_iterations))
1119 if (vect_print_dump_info (REPORT_BAD_FORM_LOOPS))
1120 fprintf (vect_dump, "Infinite number of iterations.");
1121 if (inner_loop_vinfo)
1122 destroy_loop_vec_info (inner_loop_vinfo, true);
1126 if (!NITERS_KNOWN_P (number_of_iterations))
1128 if (vect_print_dump_info (REPORT_DETAILS))
1130 fprintf (vect_dump, "Symbolic number of iterations is ");
1131 print_generic_expr (vect_dump, number_of_iterations, TDF_DETAILS);
1134 else if (TREE_INT_CST_LOW (number_of_iterations) == 0)
1136 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
1137 fprintf (vect_dump, "not vectorized: number of iterations = 0.");
1138 if (inner_loop_vinfo)
1139 destroy_loop_vec_info (inner_loop_vinfo, false);
1143 loop_vinfo = new_loop_vec_info (loop);
1144 LOOP_VINFO_NITERS (loop_vinfo) = number_of_iterations;
1145 LOOP_VINFO_NITERS_UNCHANGED (loop_vinfo) = number_of_iterations;
1147 STMT_VINFO_TYPE (vinfo_for_stmt (loop_cond)) = loop_exit_ctrl_vec_info_type;
1149 /* CHECKME: May want to keep it around it in the future. */
1150 if (inner_loop_vinfo)
1151 destroy_loop_vec_info (inner_loop_vinfo, false);
1153 gcc_assert (!loop->aux);
1154 loop->aux = loop_vinfo;
1159 /* Get cost by calling cost target builtin. */
1162 vect_get_cost (enum vect_cost_for_stmt type_of_cost)
1164 tree dummy_type = NULL;
1167 return targetm.vectorize.builtin_vectorization_cost (type_of_cost,
1172 /* Function vect_analyze_loop_operations.
1174 Scan the loop stmts and make sure they are all vectorizable. */
1177 vect_analyze_loop_operations (loop_vec_info loop_vinfo, bool slp)
1179 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
1180 basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
1181 int nbbs = loop->num_nodes;
1182 gimple_stmt_iterator si;
1183 unsigned int vectorization_factor = 0;
1186 stmt_vec_info stmt_info;
1187 bool need_to_vectorize = false;
1188 int min_profitable_iters;
1189 int min_scalar_loop_bound;
1191 bool only_slp_in_loop = true, ok;
1193 if (vect_print_dump_info (REPORT_DETAILS))
1194 fprintf (vect_dump, "=== vect_analyze_loop_operations ===");
1196 gcc_assert (LOOP_VINFO_VECT_FACTOR (loop_vinfo));
1197 vectorization_factor = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
1200 /* If all the stmts in the loop can be SLPed, we perform only SLP, and
1201 vectorization factor of the loop is the unrolling factor required by
1202 the SLP instances. If that unrolling factor is 1, we say, that we
1203 perform pure SLP on loop - cross iteration parallelism is not
1205 for (i = 0; i < nbbs; i++)
1207 basic_block bb = bbs[i];
1208 for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
1210 gimple stmt = gsi_stmt (si);
1211 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
1212 gcc_assert (stmt_info);
1213 if ((STMT_VINFO_RELEVANT_P (stmt_info)
1214 || VECTORIZABLE_CYCLE_DEF (STMT_VINFO_DEF_TYPE (stmt_info)))
1215 && !PURE_SLP_STMT (stmt_info))
1216 /* STMT needs both SLP and loop-based vectorization. */
1217 only_slp_in_loop = false;
1221 if (only_slp_in_loop)
1222 vectorization_factor = LOOP_VINFO_SLP_UNROLLING_FACTOR (loop_vinfo);
1224 vectorization_factor = least_common_multiple (vectorization_factor,
1225 LOOP_VINFO_SLP_UNROLLING_FACTOR (loop_vinfo));
1227 LOOP_VINFO_VECT_FACTOR (loop_vinfo) = vectorization_factor;
1228 if (vect_print_dump_info (REPORT_DETAILS))
1229 fprintf (vect_dump, "Updating vectorization factor to %d ",
1230 vectorization_factor);
1233 for (i = 0; i < nbbs; i++)
1235 basic_block bb = bbs[i];
1237 for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
1239 phi = gsi_stmt (si);
1242 stmt_info = vinfo_for_stmt (phi);
1243 if (vect_print_dump_info (REPORT_DETAILS))
1245 fprintf (vect_dump, "examining phi: ");
1246 print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
1249 /* Inner-loop loop-closed exit phi in outer-loop vectorization
1250 (i.e., a phi in the tail of the outer-loop). */
1251 if (! is_loop_header_bb_p (bb))
1253 /* FORNOW: we currently don't support the case that these phis
1254 are not used in the outerloop (unless it is double reduction,
1255 i.e., this phi is vect_reduction_def), cause this case
1256 requires to actually do something here. */
1257 if ((!STMT_VINFO_RELEVANT_P (stmt_info)
1258 || STMT_VINFO_LIVE_P (stmt_info))
1259 && STMT_VINFO_DEF_TYPE (stmt_info)
1260 != vect_double_reduction_def)
1262 if (vect_print_dump_info (REPORT_DETAILS))
1264 "Unsupported loop-closed phi in outer-loop.");
1268 /* If PHI is used in the outer loop, we check that its operand
1269 is defined in the inner loop. */
1270 if (STMT_VINFO_RELEVANT_P (stmt_info))
1275 if (gimple_phi_num_args (phi) != 1)
1278 phi_op = PHI_ARG_DEF (phi, 0);
1279 if (TREE_CODE (phi_op) != SSA_NAME)
1282 op_def_stmt = SSA_NAME_DEF_STMT (phi_op);
1283 if (!op_def_stmt || !vinfo_for_stmt (op_def_stmt))
1286 if (STMT_VINFO_RELEVANT (vinfo_for_stmt (op_def_stmt))
1287 != vect_used_in_outer
1288 && STMT_VINFO_RELEVANT (vinfo_for_stmt (op_def_stmt))
1289 != vect_used_in_outer_by_reduction)
1296 gcc_assert (stmt_info);
1298 if (STMT_VINFO_LIVE_P (stmt_info))
1300 /* FORNOW: not yet supported. */
1301 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
1302 fprintf (vect_dump, "not vectorized: value used after loop.");
1306 if (STMT_VINFO_RELEVANT (stmt_info) == vect_used_in_scope
1307 && STMT_VINFO_DEF_TYPE (stmt_info) != vect_induction_def)
1309 /* A scalar-dependence cycle that we don't support. */
1310 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
1311 fprintf (vect_dump, "not vectorized: scalar dependence cycle.");
1315 if (STMT_VINFO_RELEVANT_P (stmt_info))
1317 need_to_vectorize = true;
1318 if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def)
1319 ok = vectorizable_induction (phi, NULL, NULL);
1324 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
1327 "not vectorized: relevant phi not supported: ");
1328 print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
1334 for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
1336 gimple stmt = gsi_stmt (si);
1337 if (!vect_analyze_stmt (stmt, &need_to_vectorize, NULL))
1342 /* All operations in the loop are either irrelevant (deal with loop
1343 control, or dead), or only used outside the loop and can be moved
1344 out of the loop (e.g. invariants, inductions). The loop can be
1345 optimized away by scalar optimizations. We're better off not
1346 touching this loop. */
1347 if (!need_to_vectorize)
1349 if (vect_print_dump_info (REPORT_DETAILS))
1351 "All the computation can be taken out of the loop.");
1352 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
1354 "not vectorized: redundant loop. no profit to vectorize.");
1358 if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
1359 && vect_print_dump_info (REPORT_DETAILS))
1361 "vectorization_factor = %d, niters = " HOST_WIDE_INT_PRINT_DEC,
1362 vectorization_factor, LOOP_VINFO_INT_NITERS (loop_vinfo));
1364 if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
1365 && (LOOP_VINFO_INT_NITERS (loop_vinfo) < vectorization_factor))
1367 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
1368 fprintf (vect_dump, "not vectorized: iteration count too small.");
1369 if (vect_print_dump_info (REPORT_DETAILS))
1370 fprintf (vect_dump,"not vectorized: iteration count smaller than "
1371 "vectorization factor.");
1375 /* Analyze cost. Decide if worth while to vectorize. */
1377 /* Once VF is set, SLP costs should be updated since the number of created
1378 vector stmts depends on VF. */
1379 vect_update_slp_costs_according_to_vf (loop_vinfo);
1381 min_profitable_iters = vect_estimate_min_profitable_iters (loop_vinfo);
1382 LOOP_VINFO_COST_MODEL_MIN_ITERS (loop_vinfo) = min_profitable_iters;
1384 if (min_profitable_iters < 0)
1386 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
1387 fprintf (vect_dump, "not vectorized: vectorization not profitable.");
1388 if (vect_print_dump_info (REPORT_DETAILS))
1389 fprintf (vect_dump, "not vectorized: vector version will never be "
1394 min_scalar_loop_bound = ((PARAM_VALUE (PARAM_MIN_VECT_LOOP_BOUND)
1395 * vectorization_factor) - 1);
1397 /* Use the cost model only if it is more conservative than user specified
1400 th = (unsigned) min_scalar_loop_bound;
1401 if (min_profitable_iters
1402 && (!min_scalar_loop_bound
1403 || min_profitable_iters > min_scalar_loop_bound))
1404 th = (unsigned) min_profitable_iters;
1406 if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
1407 && LOOP_VINFO_INT_NITERS (loop_vinfo) <= th)
1409 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
1410 fprintf (vect_dump, "not vectorized: vectorization not "
1412 if (vect_print_dump_info (REPORT_DETAILS))
1413 fprintf (vect_dump, "not vectorized: iteration count smaller than "
1414 "user specified loop bound parameter or minimum "
1415 "profitable iterations (whichever is more conservative).");
1419 if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
1420 || LOOP_VINFO_INT_NITERS (loop_vinfo) % vectorization_factor != 0
1421 || LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo))
1423 if (vect_print_dump_info (REPORT_DETAILS))
1424 fprintf (vect_dump, "epilog loop required.");
1425 if (!vect_can_advance_ivs_p (loop_vinfo))
1427 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
1429 "not vectorized: can't create epilog loop 1.");
1432 if (!slpeel_can_duplicate_loop_p (loop, single_exit (loop)))
1434 if (vect_print_dump_info (REPORT_UNVECTORIZED_LOCATIONS))
1436 "not vectorized: can't create epilog loop 2.");
1445 /* Function vect_analyze_loop_2.
1447 Apply a set of analyses on LOOP, and create a loop_vec_info struct
1448 for it. The different analyses will record information in the
1449 loop_vec_info struct. */
1451 vect_analyze_loop_2 (loop_vec_info loop_vinfo)
1453 bool ok, dummy, slp = false;
1454 int max_vf = MAX_VECTORIZATION_FACTOR;
1457 /* Find all data references in the loop (which correspond to vdefs/vuses)
1458 and analyze their evolution in the loop. Also adjust the minimal
1459 vectorization factor according to the loads and stores.
1461 FORNOW: Handle only simple, array references, which
1462 alignment can be forced, and aligned pointer-references. */
1464 ok = vect_analyze_data_refs (loop_vinfo, NULL, &min_vf);
1467 if (vect_print_dump_info (REPORT_DETAILS))
1468 fprintf (vect_dump, "bad data references.");
1472 /* Classify all cross-iteration scalar data-flow cycles.
1473 Cross-iteration cycles caused by virtual phis are analyzed separately. */
1475 vect_analyze_scalar_cycles (loop_vinfo);
1477 vect_pattern_recog (loop_vinfo);
1479 /* Data-flow analysis to detect stmts that do not need to be vectorized. */
1481 ok = vect_mark_stmts_to_be_vectorized (loop_vinfo);
1484 if (vect_print_dump_info (REPORT_DETAILS))
1485 fprintf (vect_dump, "unexpected pattern.");
1489 /* Analyze data dependences between the data-refs in the loop
1490 and adjust the maximum vectorization factor according to
1492 FORNOW: fail at the first data dependence that we encounter. */
1494 ok = vect_analyze_data_ref_dependences (loop_vinfo, NULL, &max_vf, &dummy);
1498 if (vect_print_dump_info (REPORT_DETAILS))
1499 fprintf (vect_dump, "bad data dependence.");
1503 ok = vect_determine_vectorization_factor (loop_vinfo);
1506 if (vect_print_dump_info (REPORT_DETAILS))
1507 fprintf (vect_dump, "can't determine vectorization factor.");
1510 if (max_vf < LOOP_VINFO_VECT_FACTOR (loop_vinfo))
1512 if (vect_print_dump_info (REPORT_DETAILS))
1513 fprintf (vect_dump, "bad data dependence.");
1517 /* Analyze the alignment of the data-refs in the loop.
1518 Fail if a data reference is found that cannot be vectorized. */
1520 ok = vect_analyze_data_refs_alignment (loop_vinfo, NULL);
1523 if (vect_print_dump_info (REPORT_DETAILS))
1524 fprintf (vect_dump, "bad data alignment.");
1528 /* Analyze the access patterns of the data-refs in the loop (consecutive,
1529 complex, etc.). FORNOW: Only handle consecutive access pattern. */
1531 ok = vect_analyze_data_ref_accesses (loop_vinfo, NULL);
1534 if (vect_print_dump_info (REPORT_DETAILS))
1535 fprintf (vect_dump, "bad data access.");
1539 /* Prune the list of ddrs to be tested at run-time by versioning for alias.
1540 It is important to call pruning after vect_analyze_data_ref_accesses,
1541 since we use grouping information gathered by interleaving analysis. */
1542 ok = vect_prune_runtime_alias_test_list (loop_vinfo);
1545 if (vect_print_dump_info (REPORT_DETAILS))
1546 fprintf (vect_dump, "too long list of versioning for alias "
1551 /* This pass will decide on using loop versioning and/or loop peeling in
1552 order to enhance the alignment of data references in the loop. */
1554 ok = vect_enhance_data_refs_alignment (loop_vinfo);
1557 if (vect_print_dump_info (REPORT_DETAILS))
1558 fprintf (vect_dump, "bad data alignment.");
1562 /* Check the SLP opportunities in the loop, analyze and build SLP trees. */
1563 ok = vect_analyze_slp (loop_vinfo, NULL);
1566 /* Decide which possible SLP instances to SLP. */
1567 slp = vect_make_slp_decision (loop_vinfo);
1569 /* Find stmts that need to be both vectorized and SLPed. */
1570 vect_detect_hybrid_slp (loop_vinfo);
1575 /* Scan all the operations in the loop and make sure they are
1578 ok = vect_analyze_loop_operations (loop_vinfo, slp);
1581 if (vect_print_dump_info (REPORT_DETAILS))
1582 fprintf (vect_dump, "bad operation or unsupported loop bound.");
1589 /* Function vect_analyze_loop.
1591 Apply a set of analyses on LOOP, and create a loop_vec_info struct
1592 for it. The different analyses will record information in the
1593 loop_vec_info struct. */
1595 vect_analyze_loop (struct loop *loop)
1597 loop_vec_info loop_vinfo;
1598 unsigned int vector_sizes;
1600 /* Autodetect first vector size we try. */
1601 current_vector_size = 0;
1602 vector_sizes = targetm.vectorize.autovectorize_vector_sizes ();
1604 if (vect_print_dump_info (REPORT_DETAILS))
1605 fprintf (vect_dump, "===== analyze_loop_nest =====");
1607 if (loop_outer (loop)
1608 && loop_vec_info_for_loop (loop_outer (loop))
1609 && LOOP_VINFO_VECTORIZABLE_P (loop_vec_info_for_loop (loop_outer (loop))))
1611 if (vect_print_dump_info (REPORT_DETAILS))
1612 fprintf (vect_dump, "outer-loop already vectorized.");
1618 /* Check the CFG characteristics of the loop (nesting, entry/exit). */
1619 loop_vinfo = vect_analyze_loop_form (loop);
1622 if (vect_print_dump_info (REPORT_DETAILS))
1623 fprintf (vect_dump, "bad loop form.");
1627 if (vect_analyze_loop_2 (loop_vinfo))
1629 LOOP_VINFO_VECTORIZABLE_P (loop_vinfo) = 1;
1634 destroy_loop_vec_info (loop_vinfo, true);
1636 vector_sizes &= ~current_vector_size;
1637 if (vector_sizes == 0
1638 || current_vector_size == 0)
1641 /* Try the next biggest vector size. */
1642 current_vector_size = 1 << floor_log2 (vector_sizes);
1643 if (vect_print_dump_info (REPORT_DETAILS))
1644 fprintf (vect_dump, "***** Re-trying analysis with "
1645 "vector size %d\n", current_vector_size);
1650 /* Function reduction_code_for_scalar_code
1653 CODE - tree_code of a reduction operations.
1656 REDUC_CODE - the corresponding tree-code to be used to reduce the
1657 vector of partial results into a single scalar result (which
1658 will also reside in a vector) or ERROR_MARK if the operation is
1659 a supported reduction operation, but does not have such tree-code.
1661 Return FALSE if CODE currently cannot be vectorized as reduction. */
1664 reduction_code_for_scalar_code (enum tree_code code,
1665 enum tree_code *reduc_code)
1670 *reduc_code = REDUC_MAX_EXPR;
1674 *reduc_code = REDUC_MIN_EXPR;
1678 *reduc_code = REDUC_PLUS_EXPR;
1686 *reduc_code = ERROR_MARK;
1695 /* Error reporting helper for vect_is_simple_reduction below. GIMPLE statement
1696 STMT is printed with a message MSG. */
1699 report_vect_op (gimple stmt, const char *msg)
1701 fprintf (vect_dump, "%s", msg);
1702 print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
1706 /* Detect SLP reduction of the form:
1716 PHI is the reduction phi node (#a1 = phi <a5, a0> above)
1717 FIRST_STMT is the first reduction stmt in the chain
1718 (a2 = operation (a1)).
1720 Return TRUE if a reduction chain was detected. */
1723 vect_is_slp_reduction (loop_vec_info loop_info, gimple phi, gimple first_stmt)
1725 struct loop *loop = (gimple_bb (phi))->loop_father;
1726 struct loop *vect_loop = LOOP_VINFO_LOOP (loop_info);
1727 enum tree_code code;
1728 gimple current_stmt = NULL, loop_use_stmt = NULL, first, next_stmt;
1729 stmt_vec_info use_stmt_info, current_stmt_info;
1731 imm_use_iterator imm_iter;
1732 use_operand_p use_p;
1733 int nloop_uses, size = 0;
1736 if (loop != vect_loop)
1739 lhs = PHI_RESULT (phi);
1740 code = gimple_assign_rhs_code (first_stmt);
1744 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, lhs)
1746 gimple use_stmt = USE_STMT (use_p);
1747 if (is_gimple_debug (use_stmt))
1750 use_stmt = USE_STMT (use_p);
1752 /* Check if we got back to the reduction phi. */
1753 if (use_stmt == phi)
1755 loop_use_stmt = use_stmt;
1760 if (flow_bb_inside_loop_p (loop, gimple_bb (use_stmt))
1761 && vinfo_for_stmt (use_stmt)
1762 && !STMT_VINFO_IN_PATTERN_P (vinfo_for_stmt (use_stmt)))
1764 loop_use_stmt = use_stmt;
1775 /* We reached a statement with no loop uses. */
1776 if (nloop_uses == 0)
1779 /* This is a loop exit phi, and we haven't reached the reduction phi. */
1780 if (gimple_code (loop_use_stmt) == GIMPLE_PHI)
1783 if (!is_gimple_assign (loop_use_stmt)
1784 || code != gimple_assign_rhs_code (loop_use_stmt)
1785 || !flow_bb_inside_loop_p (loop, gimple_bb (loop_use_stmt)))
1788 /* Insert USE_STMT into reduction chain. */
1789 use_stmt_info = vinfo_for_stmt (loop_use_stmt);
1792 current_stmt_info = vinfo_for_stmt (current_stmt);
1793 GROUP_NEXT_ELEMENT (current_stmt_info) = loop_use_stmt;
1794 GROUP_FIRST_ELEMENT (use_stmt_info)
1795 = GROUP_FIRST_ELEMENT (current_stmt_info);
1798 GROUP_FIRST_ELEMENT (use_stmt_info) = loop_use_stmt;
1800 lhs = gimple_assign_lhs (loop_use_stmt);
1801 current_stmt = loop_use_stmt;
1805 if (!found || loop_use_stmt != phi || size < 2)
1808 /* Swap the operands, if needed, to make the reduction operand be the second
1810 lhs = PHI_RESULT (phi);
1811 next_stmt = GROUP_FIRST_ELEMENT (vinfo_for_stmt (current_stmt));
1814 if (gimple_assign_rhs2 (next_stmt) == lhs)
1816 tree op = gimple_assign_rhs1 (next_stmt);
1817 gimple def_stmt = NULL;
1819 if (TREE_CODE (op) == SSA_NAME)
1820 def_stmt = SSA_NAME_DEF_STMT (op);
1822 /* Check that the other def is either defined in the loop
1823 ("vect_internal_def"), or it's an induction (defined by a
1824 loop-header phi-node). */
1826 && flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))
1827 && (is_gimple_assign (def_stmt)
1828 || is_gimple_call (def_stmt)
1829 || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
1830 == vect_induction_def
1831 || (gimple_code (def_stmt) == GIMPLE_PHI
1832 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
1833 == vect_internal_def
1834 && !is_loop_header_bb_p (gimple_bb (def_stmt)))))
1836 lhs = gimple_assign_lhs (next_stmt);
1837 next_stmt = GROUP_NEXT_ELEMENT (vinfo_for_stmt (next_stmt));
1845 tree op = gimple_assign_rhs2 (next_stmt);
1846 gimple def_stmt = NULL;
1848 if (TREE_CODE (op) == SSA_NAME)
1849 def_stmt = SSA_NAME_DEF_STMT (op);
1851 /* Check that the other def is either defined in the loop
1852 ("vect_internal_def"), or it's an induction (defined by a
1853 loop-header phi-node). */
1855 && flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))
1856 && (is_gimple_assign (def_stmt)
1857 || is_gimple_call (def_stmt)
1858 || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
1859 == vect_induction_def
1860 || (gimple_code (def_stmt) == GIMPLE_PHI
1861 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
1862 == vect_internal_def
1863 && !is_loop_header_bb_p (gimple_bb (def_stmt)))))
1865 if (vect_print_dump_info (REPORT_DETAILS))
1867 fprintf (vect_dump, "swapping oprnds: ");
1868 print_gimple_stmt (vect_dump, next_stmt, 0, TDF_SLIM);
1871 swap_tree_operands (next_stmt,
1872 gimple_assign_rhs1_ptr (next_stmt),
1873 gimple_assign_rhs2_ptr (next_stmt));
1874 mark_symbols_for_renaming (next_stmt);
1880 lhs = gimple_assign_lhs (next_stmt);
1881 next_stmt = GROUP_NEXT_ELEMENT (vinfo_for_stmt (next_stmt));
1884 /* Save the chain for further analysis in SLP detection. */
1885 first = GROUP_FIRST_ELEMENT (vinfo_for_stmt (current_stmt));
1886 VEC_safe_push (gimple, heap, LOOP_VINFO_REDUCTION_CHAINS (loop_info), first);
1887 GROUP_SIZE (vinfo_for_stmt (first)) = size;
1893 /* Function vect_is_simple_reduction_1
1895 (1) Detect a cross-iteration def-use cycle that represents a simple
1896 reduction computation. We look for the following pattern:
1901 a2 = operation (a3, a1)
1904 1. operation is commutative and associative and it is safe to
1905 change the order of the computation (if CHECK_REDUCTION is true)
1906 2. no uses for a2 in the loop (a2 is used out of the loop)
1907 3. no uses of a1 in the loop besides the reduction operation
1908 4. no uses of a1 outside the loop.
1910 Conditions 1,4 are tested here.
1911 Conditions 2,3 are tested in vect_mark_stmts_to_be_vectorized.
1913 (2) Detect a cross-iteration def-use cycle in nested loops, i.e.,
1914 nested cycles, if CHECK_REDUCTION is false.
1916 (3) Detect cycles of phi nodes in outer-loop vectorization, i.e., double
1920 inner loop (def of a3)
1923 If MODIFY is true it tries also to rework the code in-place to enable
1924 detection of more reduction patterns. For the time being we rewrite
1925 "res -= RHS" into "rhs += -RHS" when it seems worthwhile.
1929 vect_is_simple_reduction_1 (loop_vec_info loop_info, gimple phi,
1930 bool check_reduction, bool *double_reduc,
1933 struct loop *loop = (gimple_bb (phi))->loop_father;
1934 struct loop *vect_loop = LOOP_VINFO_LOOP (loop_info);
1935 edge latch_e = loop_latch_edge (loop);
1936 tree loop_arg = PHI_ARG_DEF_FROM_EDGE (phi, latch_e);
1937 gimple def_stmt, def1 = NULL, def2 = NULL;
1938 enum tree_code orig_code, code;
1939 tree op1, op2, op3 = NULL_TREE, op4 = NULL_TREE;
1943 imm_use_iterator imm_iter;
1944 use_operand_p use_p;
1947 *double_reduc = false;
1949 /* If CHECK_REDUCTION is true, we assume inner-most loop vectorization,
1950 otherwise, we assume outer loop vectorization. */
1951 gcc_assert ((check_reduction && loop == vect_loop)
1952 || (!check_reduction && flow_loop_nested_p (vect_loop, loop)));
1954 name = PHI_RESULT (phi);
1956 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, name)
1958 gimple use_stmt = USE_STMT (use_p);
1959 if (is_gimple_debug (use_stmt))
1962 if (!flow_bb_inside_loop_p (loop, gimple_bb (use_stmt)))
1964 if (vect_print_dump_info (REPORT_DETAILS))
1965 fprintf (vect_dump, "intermediate value used outside loop.");
1970 if (vinfo_for_stmt (use_stmt)
1971 && !is_pattern_stmt_p (vinfo_for_stmt (use_stmt)))
1975 if (vect_print_dump_info (REPORT_DETAILS))
1976 fprintf (vect_dump, "reduction used in loop.");
1981 if (TREE_CODE (loop_arg) != SSA_NAME)
1983 if (vect_print_dump_info (REPORT_DETAILS))
1985 fprintf (vect_dump, "reduction: not ssa_name: ");
1986 print_generic_expr (vect_dump, loop_arg, TDF_SLIM);
1991 def_stmt = SSA_NAME_DEF_STMT (loop_arg);
1994 if (vect_print_dump_info (REPORT_DETAILS))
1995 fprintf (vect_dump, "reduction: no def_stmt.");
1999 if (!is_gimple_assign (def_stmt) && gimple_code (def_stmt) != GIMPLE_PHI)
2001 if (vect_print_dump_info (REPORT_DETAILS))
2002 print_gimple_stmt (vect_dump, def_stmt, 0, TDF_SLIM);
2006 if (is_gimple_assign (def_stmt))
2008 name = gimple_assign_lhs (def_stmt);
2013 name = PHI_RESULT (def_stmt);
2018 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, name)
2020 gimple use_stmt = USE_STMT (use_p);
2021 if (is_gimple_debug (use_stmt))
2023 if (flow_bb_inside_loop_p (loop, gimple_bb (use_stmt))
2024 && vinfo_for_stmt (use_stmt)
2025 && !is_pattern_stmt_p (vinfo_for_stmt (use_stmt)))
2029 if (vect_print_dump_info (REPORT_DETAILS))
2030 fprintf (vect_dump, "reduction used in loop.");
2035 /* If DEF_STMT is a phi node itself, we expect it to have a single argument
2036 defined in the inner loop. */
2039 op1 = PHI_ARG_DEF (def_stmt, 0);
2041 if (gimple_phi_num_args (def_stmt) != 1
2042 || TREE_CODE (op1) != SSA_NAME)
2044 if (vect_print_dump_info (REPORT_DETAILS))
2045 fprintf (vect_dump, "unsupported phi node definition.");
2050 def1 = SSA_NAME_DEF_STMT (op1);
2051 if (flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))
2053 && flow_bb_inside_loop_p (loop->inner, gimple_bb (def1))
2054 && is_gimple_assign (def1))
2056 if (vect_print_dump_info (REPORT_DETAILS))
2057 report_vect_op (def_stmt, "detected double reduction: ");
2059 *double_reduc = true;
2066 code = orig_code = gimple_assign_rhs_code (def_stmt);
2068 /* We can handle "res -= x[i]", which is non-associative by
2069 simply rewriting this into "res += -x[i]". Avoid changing
2070 gimple instruction for the first simple tests and only do this
2071 if we're allowed to change code at all. */
2072 if (code == MINUS_EXPR
2074 && (op1 = gimple_assign_rhs1 (def_stmt))
2075 && TREE_CODE (op1) == SSA_NAME
2076 && SSA_NAME_DEF_STMT (op1) == phi)
2080 && (!commutative_tree_code (code) || !associative_tree_code (code)))
2082 if (vect_print_dump_info (REPORT_DETAILS))
2083 report_vect_op (def_stmt, "reduction: not commutative/associative: ");
2087 if (get_gimple_rhs_class (code) != GIMPLE_BINARY_RHS)
2089 if (code != COND_EXPR)
2091 if (vect_print_dump_info (REPORT_DETAILS))
2092 report_vect_op (def_stmt, "reduction: not binary operation: ");
2097 op3 = TREE_OPERAND (gimple_assign_rhs1 (def_stmt), 0);
2098 if (COMPARISON_CLASS_P (op3))
2100 op4 = TREE_OPERAND (op3, 1);
2101 op3 = TREE_OPERAND (op3, 0);
2104 op1 = TREE_OPERAND (gimple_assign_rhs1 (def_stmt), 1);
2105 op2 = TREE_OPERAND (gimple_assign_rhs1 (def_stmt), 2);
2107 if (TREE_CODE (op1) != SSA_NAME && TREE_CODE (op2) != SSA_NAME)
2109 if (vect_print_dump_info (REPORT_DETAILS))
2110 report_vect_op (def_stmt, "reduction: uses not ssa_names: ");
2117 op1 = gimple_assign_rhs1 (def_stmt);
2118 op2 = gimple_assign_rhs2 (def_stmt);
2120 if (TREE_CODE (op1) != SSA_NAME || TREE_CODE (op2) != SSA_NAME)
2122 if (vect_print_dump_info (REPORT_DETAILS))
2123 report_vect_op (def_stmt, "reduction: uses not ssa_names: ");
2129 type = TREE_TYPE (gimple_assign_lhs (def_stmt));
2130 if ((TREE_CODE (op1) == SSA_NAME
2131 && !types_compatible_p (type,TREE_TYPE (op1)))
2132 || (TREE_CODE (op2) == SSA_NAME
2133 && !types_compatible_p (type, TREE_TYPE (op2)))
2134 || (op3 && TREE_CODE (op3) == SSA_NAME
2135 && !types_compatible_p (type, TREE_TYPE (op3)))
2136 || (op4 && TREE_CODE (op4) == SSA_NAME
2137 && !types_compatible_p (type, TREE_TYPE (op4))))
2139 if (vect_print_dump_info (REPORT_DETAILS))
2141 fprintf (vect_dump, "reduction: multiple types: operation type: ");
2142 print_generic_expr (vect_dump, type, TDF_SLIM);
2143 fprintf (vect_dump, ", operands types: ");
2144 print_generic_expr (vect_dump, TREE_TYPE (op1), TDF_SLIM);
2145 fprintf (vect_dump, ",");
2146 print_generic_expr (vect_dump, TREE_TYPE (op2), TDF_SLIM);
2149 fprintf (vect_dump, ",");
2150 print_generic_expr (vect_dump, TREE_TYPE (op3), TDF_SLIM);
2155 fprintf (vect_dump, ",");
2156 print_generic_expr (vect_dump, TREE_TYPE (op4), TDF_SLIM);
2163 /* Check that it's ok to change the order of the computation.
2164 Generally, when vectorizing a reduction we change the order of the
2165 computation. This may change the behavior of the program in some
2166 cases, so we need to check that this is ok. One exception is when
2167 vectorizing an outer-loop: the inner-loop is executed sequentially,
2168 and therefore vectorizing reductions in the inner-loop during
2169 outer-loop vectorization is safe. */
2171 /* CHECKME: check for !flag_finite_math_only too? */
2172 if (SCALAR_FLOAT_TYPE_P (type) && !flag_associative_math
2175 /* Changing the order of operations changes the semantics. */
2176 if (vect_print_dump_info (REPORT_DETAILS))
2177 report_vect_op (def_stmt, "reduction: unsafe fp math optimization: ");
2180 else if (INTEGRAL_TYPE_P (type) && TYPE_OVERFLOW_TRAPS (type)
2183 /* Changing the order of operations changes the semantics. */
2184 if (vect_print_dump_info (REPORT_DETAILS))
2185 report_vect_op (def_stmt, "reduction: unsafe int math optimization: ");
2188 else if (SAT_FIXED_POINT_TYPE_P (type) && check_reduction)
2190 /* Changing the order of operations changes the semantics. */
2191 if (vect_print_dump_info (REPORT_DETAILS))
2192 report_vect_op (def_stmt,
2193 "reduction: unsafe fixed-point math optimization: ");
2197 /* If we detected "res -= x[i]" earlier, rewrite it into
2198 "res += -x[i]" now. If this turns out to be useless reassoc
2199 will clean it up again. */
2200 if (orig_code == MINUS_EXPR)
2202 tree rhs = gimple_assign_rhs2 (def_stmt);
2203 tree negrhs = make_ssa_name (SSA_NAME_VAR (rhs), NULL);
2204 gimple negate_stmt = gimple_build_assign_with_ops (NEGATE_EXPR, negrhs,
2206 gimple_stmt_iterator gsi = gsi_for_stmt (def_stmt);
2207 set_vinfo_for_stmt (negate_stmt, new_stmt_vec_info (negate_stmt,
2209 gsi_insert_before (&gsi, negate_stmt, GSI_NEW_STMT);
2210 gimple_assign_set_rhs2 (def_stmt, negrhs);
2211 gimple_assign_set_rhs_code (def_stmt, PLUS_EXPR);
2212 update_stmt (def_stmt);
2215 /* Reduction is safe. We're dealing with one of the following:
2216 1) integer arithmetic and no trapv
2217 2) floating point arithmetic, and special flags permit this optimization
2218 3) nested cycle (i.e., outer loop vectorization). */
2219 if (TREE_CODE (op1) == SSA_NAME)
2220 def1 = SSA_NAME_DEF_STMT (op1);
2222 if (TREE_CODE (op2) == SSA_NAME)
2223 def2 = SSA_NAME_DEF_STMT (op2);
2225 if (code != COND_EXPR
2226 && (!def1 || !def2 || gimple_nop_p (def1) || gimple_nop_p (def2)))
2228 if (vect_print_dump_info (REPORT_DETAILS))
2229 report_vect_op (def_stmt, "reduction: no defs for operands: ");
2233 /* Check that one def is the reduction def, defined by PHI,
2234 the other def is either defined in the loop ("vect_internal_def"),
2235 or it's an induction (defined by a loop-header phi-node). */
2237 if (def2 && def2 == phi
2238 && (code == COND_EXPR
2239 || (def1 && flow_bb_inside_loop_p (loop, gimple_bb (def1))
2240 && (is_gimple_assign (def1)
2241 || is_gimple_call (def1)
2242 || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def1))
2243 == vect_induction_def
2244 || (gimple_code (def1) == GIMPLE_PHI
2245 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def1))
2246 == vect_internal_def
2247 && !is_loop_header_bb_p (gimple_bb (def1)))))))
2249 if (vect_print_dump_info (REPORT_DETAILS))
2250 report_vect_op (def_stmt, "detected reduction: ");
2254 if (def1 && def1 == phi
2255 && (code == COND_EXPR
2256 || (def2 && flow_bb_inside_loop_p (loop, gimple_bb (def2))
2257 && (is_gimple_assign (def2)
2258 || is_gimple_call (def2)
2259 || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def2))
2260 == vect_induction_def
2261 || (gimple_code (def2) == GIMPLE_PHI
2262 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def2))
2263 == vect_internal_def
2264 && !is_loop_header_bb_p (gimple_bb (def2)))))))
2266 if (check_reduction)
2268 /* Swap operands (just for simplicity - so that the rest of the code
2269 can assume that the reduction variable is always the last (second)
2271 if (vect_print_dump_info (REPORT_DETAILS))
2272 report_vect_op (def_stmt,
2273 "detected reduction: need to swap operands: ");
2275 swap_tree_operands (def_stmt, gimple_assign_rhs1_ptr (def_stmt),
2276 gimple_assign_rhs2_ptr (def_stmt));
2280 if (vect_print_dump_info (REPORT_DETAILS))
2281 report_vect_op (def_stmt, "detected reduction: ");
2287 /* Try to find SLP reduction chain. */
2288 if (check_reduction && vect_is_slp_reduction (loop_info, phi, def_stmt))
2290 if (vect_print_dump_info (REPORT_DETAILS))
2291 report_vect_op (def_stmt, "reduction: detected reduction chain: ");
2296 if (vect_print_dump_info (REPORT_DETAILS))
2297 report_vect_op (def_stmt, "reduction: unknown pattern: ");
2302 /* Wrapper around vect_is_simple_reduction_1, that won't modify code
2303 in-place. Arguments as there. */
2306 vect_is_simple_reduction (loop_vec_info loop_info, gimple phi,
2307 bool check_reduction, bool *double_reduc)
2309 return vect_is_simple_reduction_1 (loop_info, phi, check_reduction,
2310 double_reduc, false);
2313 /* Wrapper around vect_is_simple_reduction_1, which will modify code
2314 in-place if it enables detection of more reductions. Arguments
2318 vect_force_simple_reduction (loop_vec_info loop_info, gimple phi,
2319 bool check_reduction, bool *double_reduc)
2321 return vect_is_simple_reduction_1 (loop_info, phi, check_reduction,
2322 double_reduc, true);
2325 /* Calculate the cost of one scalar iteration of the loop. */
2327 vect_get_single_scalar_iteraion_cost (loop_vec_info loop_vinfo)
2329 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
2330 basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
2331 int nbbs = loop->num_nodes, factor, scalar_single_iter_cost = 0;
2332 int innerloop_iters, i, stmt_cost;
2334 /* Count statements in scalar loop. Using this as scalar cost for a single
2337 TODO: Add outer loop support.
2339 TODO: Consider assigning different costs to different scalar
2343 innerloop_iters = 1;
2345 innerloop_iters = 50; /* FIXME */
2347 for (i = 0; i < nbbs; i++)
2349 gimple_stmt_iterator si;
2350 basic_block bb = bbs[i];
2352 if (bb->loop_father == loop->inner)
2353 factor = innerloop_iters;
2357 for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
2359 gimple stmt = gsi_stmt (si);
2360 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
2362 if (!is_gimple_assign (stmt) && !is_gimple_call (stmt))
2365 /* Skip stmts that are not vectorized inside the loop. */
2367 && !STMT_VINFO_RELEVANT_P (stmt_info)
2368 && (!STMT_VINFO_LIVE_P (stmt_info)
2369 || STMT_VINFO_DEF_TYPE (stmt_info) != vect_reduction_def))
2372 if (STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt)))
2374 if (DR_IS_READ (STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt))))
2375 stmt_cost = vect_get_cost (scalar_load);
2377 stmt_cost = vect_get_cost (scalar_store);
2380 stmt_cost = vect_get_cost (scalar_stmt);
2382 scalar_single_iter_cost += stmt_cost * factor;
2385 return scalar_single_iter_cost;
2388 /* Calculate cost of peeling the loop PEEL_ITERS_PROLOGUE times. */
2390 vect_get_known_peeling_cost (loop_vec_info loop_vinfo, int peel_iters_prologue,
2391 int *peel_iters_epilogue,
2392 int scalar_single_iter_cost)
2394 int peel_guard_costs = 0;
2395 int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
2397 if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
2399 *peel_iters_epilogue = vf/2;
2400 if (vect_print_dump_info (REPORT_COST))
2401 fprintf (vect_dump, "cost model: "
2402 "epilogue peel iters set to vf/2 because "
2403 "loop iterations are unknown .");
2405 /* If peeled iterations are known but number of scalar loop
2406 iterations are unknown, count a taken branch per peeled loop. */
2407 peel_guard_costs = 2 * vect_get_cost (cond_branch_taken);
2411 int niters = LOOP_VINFO_INT_NITERS (loop_vinfo);
2412 peel_iters_prologue = niters < peel_iters_prologue ?
2413 niters : peel_iters_prologue;
2414 *peel_iters_epilogue = (niters - peel_iters_prologue) % vf;
2415 /* If we need to peel for gaps, but no peeling is required, we have to
2416 peel VF iterations. */
2417 if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo) && !*peel_iters_epilogue)
2418 *peel_iters_epilogue = vf;
2421 return (peel_iters_prologue * scalar_single_iter_cost)
2422 + (*peel_iters_epilogue * scalar_single_iter_cost)
2426 /* Function vect_estimate_min_profitable_iters
2428 Return the number of iterations required for the vector version of the
2429 loop to be profitable relative to the cost of the scalar version of the
2432 TODO: Take profile info into account before making vectorization
2433 decisions, if available. */
2436 vect_estimate_min_profitable_iters (loop_vec_info loop_vinfo)
2439 int min_profitable_iters;
2440 int peel_iters_prologue;
2441 int peel_iters_epilogue;
2442 int vec_inside_cost = 0;
2443 int vec_outside_cost = 0;
2444 int scalar_single_iter_cost = 0;
2445 int scalar_outside_cost = 0;
2446 int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
2447 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
2448 basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
2449 int nbbs = loop->num_nodes;
2450 int npeel = LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo);
2451 int peel_guard_costs = 0;
2452 int innerloop_iters = 0, factor;
2453 VEC (slp_instance, heap) *slp_instances;
2454 slp_instance instance;
2456 /* Cost model disabled. */
2457 if (!flag_vect_cost_model)
2459 if (vect_print_dump_info (REPORT_COST))
2460 fprintf (vect_dump, "cost model disabled.");
2464 /* Requires loop versioning tests to handle misalignment. */
2465 if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo))
2467 /* FIXME: Make cost depend on complexity of individual check. */
2469 VEC_length (gimple, LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo));
2470 if (vect_print_dump_info (REPORT_COST))
2471 fprintf (vect_dump, "cost model: Adding cost of checks for loop "
2472 "versioning to treat misalignment.\n");
2475 /* Requires loop versioning with alias checks. */
2476 if (LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
2478 /* FIXME: Make cost depend on complexity of individual check. */
2480 VEC_length (ddr_p, LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo));
2481 if (vect_print_dump_info (REPORT_COST))
2482 fprintf (vect_dump, "cost model: Adding cost of checks for loop "
2483 "versioning aliasing.\n");
2486 if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)
2487 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
2488 vec_outside_cost += vect_get_cost (cond_branch_taken);
2490 /* Count statements in scalar loop. Using this as scalar cost for a single
2493 TODO: Add outer loop support.
2495 TODO: Consider assigning different costs to different scalar
2500 innerloop_iters = 50; /* FIXME */
2502 for (i = 0; i < nbbs; i++)
2504 gimple_stmt_iterator si;
2505 basic_block bb = bbs[i];
2507 if (bb->loop_father == loop->inner)
2508 factor = innerloop_iters;
2512 for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
2514 gimple stmt = gsi_stmt (si);
2515 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
2516 /* Skip stmts that are not vectorized inside the loop. */
2517 if (!STMT_VINFO_RELEVANT_P (stmt_info)
2518 && (!STMT_VINFO_LIVE_P (stmt_info)
2519 || STMT_VINFO_DEF_TYPE (stmt_info) != vect_reduction_def))
2521 vec_inside_cost += STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info) * factor;
2522 /* FIXME: for stmts in the inner-loop in outer-loop vectorization,
2523 some of the "outside" costs are generated inside the outer-loop. */
2524 vec_outside_cost += STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info);
2528 scalar_single_iter_cost = vect_get_single_scalar_iteraion_cost (loop_vinfo);
2530 /* Add additional cost for the peeled instructions in prologue and epilogue
2533 FORNOW: If we don't know the value of peel_iters for prologue or epilogue
2534 at compile-time - we assume it's vf/2 (the worst would be vf-1).
2536 TODO: Build an expression that represents peel_iters for prologue and
2537 epilogue to be used in a run-time test. */
2541 peel_iters_prologue = vf/2;
2542 if (vect_print_dump_info (REPORT_COST))
2543 fprintf (vect_dump, "cost model: "
2544 "prologue peel iters set to vf/2.");
2546 /* If peeling for alignment is unknown, loop bound of main loop becomes
2548 peel_iters_epilogue = vf/2;
2549 if (vect_print_dump_info (REPORT_COST))
2550 fprintf (vect_dump, "cost model: "
2551 "epilogue peel iters set to vf/2 because "
2552 "peeling for alignment is unknown .");
2554 /* If peeled iterations are unknown, count a taken branch and a not taken
2555 branch per peeled loop. Even if scalar loop iterations are known,
2556 vector iterations are not known since peeled prologue iterations are
2557 not known. Hence guards remain the same. */
2558 peel_guard_costs += 2 * (vect_get_cost (cond_branch_taken)
2559 + vect_get_cost (cond_branch_not_taken));
2560 vec_outside_cost += (peel_iters_prologue * scalar_single_iter_cost)
2561 + (peel_iters_epilogue * scalar_single_iter_cost)
2566 peel_iters_prologue = npeel;
2567 vec_outside_cost += vect_get_known_peeling_cost (loop_vinfo,
2568 peel_iters_prologue, &peel_iters_epilogue,
2569 scalar_single_iter_cost);
2572 /* FORNOW: The scalar outside cost is incremented in one of the
2575 1. The vectorizer checks for alignment and aliasing and generates
2576 a condition that allows dynamic vectorization. A cost model
2577 check is ANDED with the versioning condition. Hence scalar code
2578 path now has the added cost of the versioning check.
2580 if (cost > th & versioning_check)
2583 Hence run-time scalar is incremented by not-taken branch cost.
2585 2. The vectorizer then checks if a prologue is required. If the
2586 cost model check was not done before during versioning, it has to
2587 be done before the prologue check.
2590 prologue = scalar_iters
2595 if (prologue == num_iters)
2598 Hence the run-time scalar cost is incremented by a taken branch,
2599 plus a not-taken branch, plus a taken branch cost.
2601 3. The vectorizer then checks if an epilogue is required. If the
2602 cost model check was not done before during prologue check, it
2603 has to be done with the epilogue check.
2609 if (prologue == num_iters)
2612 if ((cost <= th) | (scalar_iters-prologue-epilogue == 0))
2615 Hence the run-time scalar cost should be incremented by 2 taken
2618 TODO: The back end may reorder the BBS's differently and reverse
2619 conditions/branch directions. Change the estimates below to
2620 something more reasonable. */
2622 /* If the number of iterations is known and we do not do versioning, we can
2623 decide whether to vectorize at compile time. Hence the scalar version
2624 do not carry cost model guard costs. */
2625 if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
2626 || LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)
2627 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
2629 /* Cost model check occurs at versioning. */
2630 if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)
2631 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
2632 scalar_outside_cost += vect_get_cost (cond_branch_not_taken);
2635 /* Cost model check occurs at prologue generation. */
2636 if (LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo) < 0)
2637 scalar_outside_cost += 2 * vect_get_cost (cond_branch_taken)
2638 + vect_get_cost (cond_branch_not_taken);
2639 /* Cost model check occurs at epilogue generation. */
2641 scalar_outside_cost += 2 * vect_get_cost (cond_branch_taken);
2645 /* Add SLP costs. */
2646 slp_instances = LOOP_VINFO_SLP_INSTANCES (loop_vinfo);
2647 FOR_EACH_VEC_ELT (slp_instance, slp_instances, i, instance)
2649 vec_outside_cost += SLP_INSTANCE_OUTSIDE_OF_LOOP_COST (instance);
2650 vec_inside_cost += SLP_INSTANCE_INSIDE_OF_LOOP_COST (instance);
2653 /* Calculate number of iterations required to make the vector version
2654 profitable, relative to the loop bodies only. The following condition
2656 SIC * niters + SOC > VIC * ((niters-PL_ITERS-EP_ITERS)/VF) + VOC
2658 SIC = scalar iteration cost, VIC = vector iteration cost,
2659 VOC = vector outside cost, VF = vectorization factor,
2660 PL_ITERS = prologue iterations, EP_ITERS= epilogue iterations
2661 SOC = scalar outside cost for run time cost model check. */
2663 if ((scalar_single_iter_cost * vf) > vec_inside_cost)
2665 if (vec_outside_cost <= 0)
2666 min_profitable_iters = 1;
2669 min_profitable_iters = ((vec_outside_cost - scalar_outside_cost) * vf
2670 - vec_inside_cost * peel_iters_prologue
2671 - vec_inside_cost * peel_iters_epilogue)
2672 / ((scalar_single_iter_cost * vf)
2675 if ((scalar_single_iter_cost * vf * min_profitable_iters)
2676 <= ((vec_inside_cost * min_profitable_iters)
2677 + ((vec_outside_cost - scalar_outside_cost) * vf)))
2678 min_profitable_iters++;
2681 /* vector version will never be profitable. */
2684 if (vect_print_dump_info (REPORT_COST))
2685 fprintf (vect_dump, "cost model: the vector iteration cost = %d "
2686 "divided by the scalar iteration cost = %d "
2687 "is greater or equal to the vectorization factor = %d.",
2688 vec_inside_cost, scalar_single_iter_cost, vf);
2692 if (vect_print_dump_info (REPORT_COST))
2694 fprintf (vect_dump, "Cost model analysis: \n");
2695 fprintf (vect_dump, " Vector inside of loop cost: %d\n",
2697 fprintf (vect_dump, " Vector outside of loop cost: %d\n",
2699 fprintf (vect_dump, " Scalar iteration cost: %d\n",
2700 scalar_single_iter_cost);
2701 fprintf (vect_dump, " Scalar outside cost: %d\n", scalar_outside_cost);
2702 fprintf (vect_dump, " prologue iterations: %d\n",
2703 peel_iters_prologue);
2704 fprintf (vect_dump, " epilogue iterations: %d\n",
2705 peel_iters_epilogue);
2706 fprintf (vect_dump, " Calculated minimum iters for profitability: %d\n",
2707 min_profitable_iters);
2710 min_profitable_iters =
2711 min_profitable_iters < vf ? vf : min_profitable_iters;
2713 /* Because the condition we create is:
2714 if (niters <= min_profitable_iters)
2715 then skip the vectorized loop. */
2716 min_profitable_iters--;
2718 if (vect_print_dump_info (REPORT_COST))
2719 fprintf (vect_dump, " Profitability threshold = %d\n",
2720 min_profitable_iters);
2722 return min_profitable_iters;
2726 /* TODO: Close dependency between vect_model_*_cost and vectorizable_*
2727 functions. Design better to avoid maintenance issues. */
2729 /* Function vect_model_reduction_cost.
2731 Models cost for a reduction operation, including the vector ops
2732 generated within the strip-mine loop, the initial definition before
2733 the loop, and the epilogue code that must be generated. */
2736 vect_model_reduction_cost (stmt_vec_info stmt_info, enum tree_code reduc_code,
2740 enum tree_code code;
2743 gimple stmt, orig_stmt;
2745 enum machine_mode mode;
2746 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
2747 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
2750 /* Cost of reduction op inside loop. */
2751 STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info)
2752 += ncopies * vect_get_cost (vector_stmt);
2754 stmt = STMT_VINFO_STMT (stmt_info);
2756 switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt)))
2758 case GIMPLE_SINGLE_RHS:
2759 gcc_assert (TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt)) == ternary_op);
2760 reduction_op = TREE_OPERAND (gimple_assign_rhs1 (stmt), 2);
2762 case GIMPLE_UNARY_RHS:
2763 reduction_op = gimple_assign_rhs1 (stmt);
2765 case GIMPLE_BINARY_RHS:
2766 reduction_op = gimple_assign_rhs2 (stmt);
2768 case GIMPLE_TERNARY_RHS:
2769 reduction_op = gimple_assign_rhs3 (stmt);
2775 vectype = get_vectype_for_scalar_type (TREE_TYPE (reduction_op));
2778 if (vect_print_dump_info (REPORT_COST))
2780 fprintf (vect_dump, "unsupported data-type ");
2781 print_generic_expr (vect_dump, TREE_TYPE (reduction_op), TDF_SLIM);
2786 mode = TYPE_MODE (vectype);
2787 orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);
2790 orig_stmt = STMT_VINFO_STMT (stmt_info);
2792 code = gimple_assign_rhs_code (orig_stmt);
2794 /* Add in cost for initial definition. */
2795 outer_cost += vect_get_cost (scalar_to_vec);
2797 /* Determine cost of epilogue code.
2799 We have a reduction operator that will reduce the vector in one statement.
2800 Also requires scalar extract. */
2802 if (!nested_in_vect_loop_p (loop, orig_stmt))
2804 if (reduc_code != ERROR_MARK)
2805 outer_cost += vect_get_cost (vector_stmt)
2806 + vect_get_cost (vec_to_scalar);
2809 int vec_size_in_bits = tree_low_cst (TYPE_SIZE (vectype), 1);
2811 TYPE_SIZE (TREE_TYPE (gimple_assign_lhs (orig_stmt)));
2812 int element_bitsize = tree_low_cst (bitsize, 1);
2813 int nelements = vec_size_in_bits / element_bitsize;
2815 optab = optab_for_tree_code (code, vectype, optab_default);
2817 /* We have a whole vector shift available. */
2818 if (VECTOR_MODE_P (mode)
2819 && optab_handler (optab, mode) != CODE_FOR_nothing
2820 && optab_handler (vec_shr_optab, mode) != CODE_FOR_nothing)
2821 /* Final reduction via vector shifts and the reduction operator. Also
2822 requires scalar extract. */
2823 outer_cost += ((exact_log2(nelements) * 2)
2824 * vect_get_cost (vector_stmt)
2825 + vect_get_cost (vec_to_scalar));
2827 /* Use extracts and reduction op for final reduction. For N elements,
2828 we have N extracts and N-1 reduction ops. */
2829 outer_cost += ((nelements + nelements - 1)
2830 * vect_get_cost (vector_stmt));
2834 STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info) = outer_cost;
2836 if (vect_print_dump_info (REPORT_COST))
2837 fprintf (vect_dump, "vect_model_reduction_cost: inside_cost = %d, "
2838 "outside_cost = %d .", STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info),
2839 STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info));
2845 /* Function vect_model_induction_cost.
2847 Models cost for induction operations. */
2850 vect_model_induction_cost (stmt_vec_info stmt_info, int ncopies)
2852 /* loop cost for vec_loop. */
2853 STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info)
2854 = ncopies * vect_get_cost (vector_stmt);
2855 /* prologue cost for vec_init and vec_step. */
2856 STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info)
2857 = 2 * vect_get_cost (scalar_to_vec);
2859 if (vect_print_dump_info (REPORT_COST))
2860 fprintf (vect_dump, "vect_model_induction_cost: inside_cost = %d, "
2861 "outside_cost = %d .", STMT_VINFO_INSIDE_OF_LOOP_COST (stmt_info),
2862 STMT_VINFO_OUTSIDE_OF_LOOP_COST (stmt_info));
2866 /* Function get_initial_def_for_induction
2869 STMT - a stmt that performs an induction operation in the loop.
2870 IV_PHI - the initial value of the induction variable
2873 Return a vector variable, initialized with the first VF values of
2874 the induction variable. E.g., for an iv with IV_PHI='X' and
2875 evolution S, for a vector of 4 units, we want to return:
2876 [X, X + S, X + 2*S, X + 3*S]. */
2879 get_initial_def_for_induction (gimple iv_phi)
2881 stmt_vec_info stmt_vinfo = vinfo_for_stmt (iv_phi);
2882 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo);
2883 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
2887 edge pe = loop_preheader_edge (loop);
2888 struct loop *iv_loop;
2890 tree vec, vec_init, vec_step, t;
2894 gimple init_stmt, induction_phi, new_stmt;
2895 tree induc_def, vec_def, vec_dest;
2896 tree init_expr, step_expr;
2897 int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
2902 stmt_vec_info phi_info = vinfo_for_stmt (iv_phi);
2903 bool nested_in_vect_loop = false;
2904 gimple_seq stmts = NULL;
2905 imm_use_iterator imm_iter;
2906 use_operand_p use_p;
2910 gimple_stmt_iterator si;
2911 basic_block bb = gimple_bb (iv_phi);
2915 /* Is phi in an inner-loop, while vectorizing an enclosing outer-loop? */
2916 if (nested_in_vect_loop_p (loop, iv_phi))
2918 nested_in_vect_loop = true;
2919 iv_loop = loop->inner;
2923 gcc_assert (iv_loop == (gimple_bb (iv_phi))->loop_father);
2925 latch_e = loop_latch_edge (iv_loop);
2926 loop_arg = PHI_ARG_DEF_FROM_EDGE (iv_phi, latch_e);
2928 access_fn = analyze_scalar_evolution (iv_loop, PHI_RESULT (iv_phi));
2929 gcc_assert (access_fn);
2930 STRIP_NOPS (access_fn);
2931 ok = vect_is_simple_iv_evolution (iv_loop->num, access_fn,
2932 &init_expr, &step_expr);
2934 pe = loop_preheader_edge (iv_loop);
2936 scalar_type = TREE_TYPE (init_expr);
2937 vectype = get_vectype_for_scalar_type (scalar_type);
2938 resvectype = get_vectype_for_scalar_type (TREE_TYPE (PHI_RESULT (iv_phi)));
2939 gcc_assert (vectype);
2940 nunits = TYPE_VECTOR_SUBPARTS (vectype);
2941 ncopies = vf / nunits;
2943 gcc_assert (phi_info);
2944 gcc_assert (ncopies >= 1);
2946 /* Find the first insertion point in the BB. */
2947 si = gsi_after_labels (bb);
2949 /* Create the vector that holds the initial_value of the induction. */
2950 if (nested_in_vect_loop)
2952 /* iv_loop is nested in the loop to be vectorized. init_expr had already
2953 been created during vectorization of previous stmts. We obtain it
2954 from the STMT_VINFO_VEC_STMT of the defining stmt. */
2955 tree iv_def = PHI_ARG_DEF_FROM_EDGE (iv_phi,
2956 loop_preheader_edge (iv_loop));
2957 vec_init = vect_get_vec_def_for_operand (iv_def, iv_phi, NULL);
2961 /* iv_loop is the loop to be vectorized. Create:
2962 vec_init = [X, X+S, X+2*S, X+3*S] (S = step_expr, X = init_expr) */
2963 new_var = vect_get_new_vect_var (scalar_type, vect_scalar_var, "var_");
2964 add_referenced_var (new_var);
2966 new_name = force_gimple_operand (init_expr, &stmts, false, new_var);
2969 new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts);
2970 gcc_assert (!new_bb);
2974 t = tree_cons (NULL_TREE, new_name, t);
2975 for (i = 1; i < nunits; i++)
2977 /* Create: new_name_i = new_name + step_expr */
2978 enum tree_code code = POINTER_TYPE_P (scalar_type)
2979 ? POINTER_PLUS_EXPR : PLUS_EXPR;
2980 init_stmt = gimple_build_assign_with_ops (code, new_var,
2981 new_name, step_expr);
2982 new_name = make_ssa_name (new_var, init_stmt);
2983 gimple_assign_set_lhs (init_stmt, new_name);
2985 new_bb = gsi_insert_on_edge_immediate (pe, init_stmt);
2986 gcc_assert (!new_bb);
2988 if (vect_print_dump_info (REPORT_DETAILS))
2990 fprintf (vect_dump, "created new init_stmt: ");
2991 print_gimple_stmt (vect_dump, init_stmt, 0, TDF_SLIM);
2993 t = tree_cons (NULL_TREE, new_name, t);
2995 /* Create a vector from [new_name_0, new_name_1, ..., new_name_nunits-1] */
2996 vec = build_constructor_from_list (vectype, nreverse (t));
2997 vec_init = vect_init_vector (iv_phi, vec, vectype, NULL);
3001 /* Create the vector that holds the step of the induction. */
3002 if (nested_in_vect_loop)
3003 /* iv_loop is nested in the loop to be vectorized. Generate:
3004 vec_step = [S, S, S, S] */
3005 new_name = step_expr;
3008 /* iv_loop is the loop to be vectorized. Generate:
3009 vec_step = [VF*S, VF*S, VF*S, VF*S] */
3010 expr = build_int_cst (TREE_TYPE (step_expr), vf);
3011 new_name = fold_build2 (MULT_EXPR, TREE_TYPE (step_expr),
3015 t = unshare_expr (new_name);
3016 gcc_assert (CONSTANT_CLASS_P (new_name));
3017 stepvectype = get_vectype_for_scalar_type (TREE_TYPE (new_name));
3018 gcc_assert (stepvectype);
3019 vec = build_vector_from_val (stepvectype, t);
3020 vec_step = vect_init_vector (iv_phi, vec, stepvectype, NULL);
3023 /* Create the following def-use cycle:
3028 vec_iv = PHI <vec_init, vec_loop>
3032 vec_loop = vec_iv + vec_step; */
3034 /* Create the induction-phi that defines the induction-operand. */
3035 vec_dest = vect_get_new_vect_var (vectype, vect_simple_var, "vec_iv_");
3036 add_referenced_var (vec_dest);
3037 induction_phi = create_phi_node (vec_dest, iv_loop->header);
3038 set_vinfo_for_stmt (induction_phi,
3039 new_stmt_vec_info (induction_phi, loop_vinfo, NULL));
3040 induc_def = PHI_RESULT (induction_phi);
3042 /* Create the iv update inside the loop */
3043 new_stmt = gimple_build_assign_with_ops (PLUS_EXPR, vec_dest,
3044 induc_def, vec_step);
3045 vec_def = make_ssa_name (vec_dest, new_stmt);
3046 gimple_assign_set_lhs (new_stmt, vec_def);
3047 gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
3048 set_vinfo_for_stmt (new_stmt, new_stmt_vec_info (new_stmt, loop_vinfo,
3051 /* Set the arguments of the phi node: */
3052 add_phi_arg (induction_phi, vec_init, pe, UNKNOWN_LOCATION);
3053 add_phi_arg (induction_phi, vec_def, loop_latch_edge (iv_loop),
3057 /* In case that vectorization factor (VF) is bigger than the number
3058 of elements that we can fit in a vectype (nunits), we have to generate
3059 more than one vector stmt - i.e - we need to "unroll" the
3060 vector stmt by a factor VF/nunits. For more details see documentation
3061 in vectorizable_operation. */
3065 stmt_vec_info prev_stmt_vinfo;
3066 /* FORNOW. This restriction should be relaxed. */
3067 gcc_assert (!nested_in_vect_loop);
3069 /* Create the vector that holds the step of the induction. */
3070 expr = build_int_cst (TREE_TYPE (step_expr), nunits);
3071 new_name = fold_build2 (MULT_EXPR, TREE_TYPE (step_expr),
3073 t = unshare_expr (new_name);
3074 gcc_assert (CONSTANT_CLASS_P (new_name));
3075 vec = build_vector_from_val (stepvectype, t);
3076 vec_step = vect_init_vector (iv_phi, vec, stepvectype, NULL);
3078 vec_def = induc_def;
3079 prev_stmt_vinfo = vinfo_for_stmt (induction_phi);
3080 for (i = 1; i < ncopies; i++)
3082 /* vec_i = vec_prev + vec_step */
3083 new_stmt = gimple_build_assign_with_ops (PLUS_EXPR, vec_dest,
3085 vec_def = make_ssa_name (vec_dest, new_stmt);
3086 gimple_assign_set_lhs (new_stmt, vec_def);
3088 gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
3089 if (!useless_type_conversion_p (resvectype, vectype))
3091 new_stmt = gimple_build_assign_with_ops
3093 vect_get_new_vect_var (resvectype, vect_simple_var,
3095 build1 (VIEW_CONVERT_EXPR, resvectype,
3096 gimple_assign_lhs (new_stmt)), NULL_TREE);
3097 gimple_assign_set_lhs (new_stmt,
3099 (gimple_assign_lhs (new_stmt), new_stmt));
3100 gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
3102 set_vinfo_for_stmt (new_stmt,
3103 new_stmt_vec_info (new_stmt, loop_vinfo, NULL));
3104 STMT_VINFO_RELATED_STMT (prev_stmt_vinfo) = new_stmt;
3105 prev_stmt_vinfo = vinfo_for_stmt (new_stmt);
3109 if (nested_in_vect_loop)
3111 /* Find the loop-closed exit-phi of the induction, and record
3112 the final vector of induction results: */
3114 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, loop_arg)
3116 if (!flow_bb_inside_loop_p (iv_loop, gimple_bb (USE_STMT (use_p))))
3118 exit_phi = USE_STMT (use_p);
3124 stmt_vec_info stmt_vinfo = vinfo_for_stmt (exit_phi);
3125 /* FORNOW. Currently not supporting the case that an inner-loop induction
3126 is not used in the outer-loop (i.e. only outside the outer-loop). */
3127 gcc_assert (STMT_VINFO_RELEVANT_P (stmt_vinfo)
3128 && !STMT_VINFO_LIVE_P (stmt_vinfo));
3130 STMT_VINFO_VEC_STMT (stmt_vinfo) = new_stmt;
3131 if (vect_print_dump_info (REPORT_DETAILS))
3133 fprintf (vect_dump, "vector of inductions after inner-loop:");
3134 print_gimple_stmt (vect_dump, new_stmt, 0, TDF_SLIM);
3140 if (vect_print_dump_info (REPORT_DETAILS))
3142 fprintf (vect_dump, "transform induction: created def-use cycle: ");
3143 print_gimple_stmt (vect_dump, induction_phi, 0, TDF_SLIM);
3144 fprintf (vect_dump, "\n");
3145 print_gimple_stmt (vect_dump, SSA_NAME_DEF_STMT (vec_def), 0, TDF_SLIM);
3148 STMT_VINFO_VEC_STMT (phi_info) = induction_phi;
3149 if (!useless_type_conversion_p (resvectype, vectype))
3151 new_stmt = gimple_build_assign_with_ops
3153 vect_get_new_vect_var (resvectype, vect_simple_var, "vec_iv_"),
3154 build1 (VIEW_CONVERT_EXPR, resvectype, induc_def), NULL_TREE);
3155 induc_def = make_ssa_name (gimple_assign_lhs (new_stmt), new_stmt);
3156 gimple_assign_set_lhs (new_stmt, induc_def);
3157 si = gsi_start_bb (bb);
3158 gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
3159 set_vinfo_for_stmt (new_stmt,
3160 new_stmt_vec_info (new_stmt, loop_vinfo, NULL));
3161 STMT_VINFO_RELATED_STMT (vinfo_for_stmt (new_stmt))
3162 = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (induction_phi));
3169 /* Function get_initial_def_for_reduction
3172 STMT - a stmt that performs a reduction operation in the loop.
3173 INIT_VAL - the initial value of the reduction variable
3176 ADJUSTMENT_DEF - a tree that holds a value to be added to the final result
3177 of the reduction (used for adjusting the epilog - see below).
3178 Return a vector variable, initialized according to the operation that STMT
3179 performs. This vector will be used as the initial value of the
3180 vector of partial results.
3182 Option1 (adjust in epilog): Initialize the vector as follows:
3183 add/bit or/xor: [0,0,...,0,0]
3184 mult/bit and: [1,1,...,1,1]
3185 min/max/cond_expr: [init_val,init_val,..,init_val,init_val]
3186 and when necessary (e.g. add/mult case) let the caller know
3187 that it needs to adjust the result by init_val.
3189 Option2: Initialize the vector as follows:
3190 add/bit or/xor: [init_val,0,0,...,0]
3191 mult/bit and: [init_val,1,1,...,1]
3192 min/max/cond_expr: [init_val,init_val,...,init_val]
3193 and no adjustments are needed.
3195 For example, for the following code:
3201 STMT is 's = s + a[i]', and the reduction variable is 's'.
3202 For a vector of 4 units, we want to return either [0,0,0,init_val],
3203 or [0,0,0,0] and let the caller know that it needs to adjust
3204 the result at the end by 'init_val'.
3206 FORNOW, we are using the 'adjust in epilog' scheme, because this way the
3207 initialization vector is simpler (same element in all entries), if
3208 ADJUSTMENT_DEF is not NULL, and Option2 otherwise.
3210 A cost model should help decide between these two schemes. */
3213 get_initial_def_for_reduction (gimple stmt, tree init_val,
3214 tree *adjustment_def)
3216 stmt_vec_info stmt_vinfo = vinfo_for_stmt (stmt);
3217 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo);
3218 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
3219 tree scalar_type = TREE_TYPE (init_val);
3220 tree vectype = get_vectype_for_scalar_type (scalar_type);
3222 enum tree_code code = gimple_assign_rhs_code (stmt);
3227 bool nested_in_vect_loop = false;
3229 REAL_VALUE_TYPE real_init_val = dconst0;
3230 int int_init_val = 0;
3231 gimple def_stmt = NULL;
3233 gcc_assert (vectype);
3234 nunits = TYPE_VECTOR_SUBPARTS (vectype);
3236 gcc_assert (POINTER_TYPE_P (scalar_type) || INTEGRAL_TYPE_P (scalar_type)
3237 || SCALAR_FLOAT_TYPE_P (scalar_type));
3239 if (nested_in_vect_loop_p (loop, stmt))
3240 nested_in_vect_loop = true;
3242 gcc_assert (loop == (gimple_bb (stmt))->loop_father);
3244 /* In case of double reduction we only create a vector variable to be put
3245 in the reduction phi node. The actual statement creation is done in
3246 vect_create_epilog_for_reduction. */
3247 if (adjustment_def && nested_in_vect_loop
3248 && TREE_CODE (init_val) == SSA_NAME
3249 && (def_stmt = SSA_NAME_DEF_STMT (init_val))
3250 && gimple_code (def_stmt) == GIMPLE_PHI
3251 && flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))
3252 && vinfo_for_stmt (def_stmt)
3253 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
3254 == vect_double_reduction_def)
3256 *adjustment_def = NULL;
3257 return vect_create_destination_var (init_val, vectype);
3260 if (TREE_CONSTANT (init_val))
3262 if (SCALAR_FLOAT_TYPE_P (scalar_type))
3263 init_value = build_real (scalar_type, TREE_REAL_CST (init_val));
3265 init_value = build_int_cst (scalar_type, TREE_INT_CST_LOW (init_val));
3268 init_value = init_val;
3272 case WIDEN_SUM_EXPR:
3280 /* ADJUSMENT_DEF is NULL when called from
3281 vect_create_epilog_for_reduction to vectorize double reduction. */
3284 if (nested_in_vect_loop)
3285 *adjustment_def = vect_get_vec_def_for_operand (init_val, stmt,
3288 *adjustment_def = init_val;
3291 if (code == MULT_EXPR)
3293 real_init_val = dconst1;
3297 if (code == BIT_AND_EXPR)
3300 if (SCALAR_FLOAT_TYPE_P (scalar_type))
3301 def_for_init = build_real (scalar_type, real_init_val);
3303 def_for_init = build_int_cst (scalar_type, int_init_val);
3305 /* Create a vector of '0' or '1' except the first element. */
3306 for (i = nunits - 2; i >= 0; --i)
3307 t = tree_cons (NULL_TREE, def_for_init, t);
3309 /* Option1: the first element is '0' or '1' as well. */
3312 t = tree_cons (NULL_TREE, def_for_init, t);
3313 init_def = build_vector (vectype, t);
3317 /* Option2: the first element is INIT_VAL. */
3318 t = tree_cons (NULL_TREE, init_value, t);
3319 if (TREE_CONSTANT (init_val))
3320 init_def = build_vector (vectype, t);
3322 init_def = build_constructor_from_list (vectype, t);
3331 *adjustment_def = NULL_TREE;
3332 init_def = vect_get_vec_def_for_operand (init_val, stmt, NULL);
3336 init_def = build_vector_from_val (vectype, init_value);
3347 /* Function vect_create_epilog_for_reduction
3349 Create code at the loop-epilog to finalize the result of a reduction
3352 VECT_DEFS is list of vector of partial results, i.e., the lhs's of vector
3353 reduction statements.
3354 STMT is the scalar reduction stmt that is being vectorized.
3355 NCOPIES is > 1 in case the vectorization factor (VF) is bigger than the
3356 number of elements that we can fit in a vectype (nunits). In this case
3357 we have to generate more than one vector stmt - i.e - we need to "unroll"
3358 the vector stmt by a factor VF/nunits. For more details see documentation
3359 in vectorizable_operation.
3360 REDUC_CODE is the tree-code for the epilog reduction.
3361 REDUCTION_PHIS is a list of the phi-nodes that carry the reduction
3363 REDUC_INDEX is the index of the operand in the right hand side of the
3364 statement that is defined by REDUCTION_PHI.
3365 DOUBLE_REDUC is TRUE if double reduction phi nodes should be handled.
3366 SLP_NODE is an SLP node containing a group of reduction statements. The
3367 first one in this group is STMT.
3370 1. Creates the reduction def-use cycles: sets the arguments for
3372 The loop-entry argument is the vectorized initial-value of the reduction.
3373 The loop-latch argument is taken from VECT_DEFS - the vector of partial
3375 2. "Reduces" each vector of partial results VECT_DEFS into a single result,
3376 by applying the operation specified by REDUC_CODE if available, or by
3377 other means (whole-vector shifts or a scalar loop).
3378 The function also creates a new phi node at the loop exit to preserve
3379 loop-closed form, as illustrated below.
3381 The flow at the entry to this function:
3384 vec_def = phi <null, null> # REDUCTION_PHI
3385 VECT_DEF = vector_stmt # vectorized form of STMT
3386 s_loop = scalar_stmt # (scalar) STMT
3388 s_out0 = phi <s_loop> # (scalar) EXIT_PHI
3392 The above is transformed by this function into:
3395 vec_def = phi <vec_init, VECT_DEF> # REDUCTION_PHI
3396 VECT_DEF = vector_stmt # vectorized form of STMT
3397 s_loop = scalar_stmt # (scalar) STMT
3399 s_out0 = phi <s_loop> # (scalar) EXIT_PHI
3400 v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
3401 v_out2 = reduce <v_out1>
3402 s_out3 = extract_field <v_out2, 0>
3403 s_out4 = adjust_result <s_out3>
3409 vect_create_epilog_for_reduction (VEC (tree, heap) *vect_defs, gimple stmt,
3410 int ncopies, enum tree_code reduc_code,
3411 VEC (gimple, heap) *reduction_phis,
3412 int reduc_index, bool double_reduc,
3415 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
3416 stmt_vec_info prev_phi_info;
3418 enum machine_mode mode;
3419 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
3420 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo), *outer_loop = NULL;
3421 basic_block exit_bb;
3424 gimple new_phi = NULL, phi;
3425 gimple_stmt_iterator exit_gsi;
3427 tree new_temp = NULL_TREE, new_dest, new_name, new_scalar_dest;
3428 gimple epilog_stmt = NULL;
3429 enum tree_code code = gimple_assign_rhs_code (stmt);
3431 tree bitsize, bitpos;
3432 tree adjustment_def = NULL;
3433 tree vec_initial_def = NULL;
3434 tree reduction_op, expr, def;
3435 tree orig_name, scalar_result;
3436 imm_use_iterator imm_iter, phi_imm_iter;
3437 use_operand_p use_p, phi_use_p;
3438 bool extract_scalar_result = false;
3439 gimple use_stmt, orig_stmt, reduction_phi = NULL;
3440 bool nested_in_vect_loop = false;
3441 VEC (gimple, heap) *new_phis = NULL;
3442 enum vect_def_type dt = vect_unknown_def_type;
3444 VEC (tree, heap) *scalar_results = NULL;
3445 unsigned int group_size = 1, k, ratio;
3446 VEC (tree, heap) *vec_initial_defs = NULL;
3447 VEC (gimple, heap) *phis;
3448 bool slp_reduc = false;
3449 tree new_phi_result;
3452 group_size = VEC_length (gimple, SLP_TREE_SCALAR_STMTS (slp_node));
3454 if (nested_in_vect_loop_p (loop, stmt))
3458 nested_in_vect_loop = true;
3459 gcc_assert (!slp_node);
3462 switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt)))
3464 case GIMPLE_SINGLE_RHS:
3465 gcc_assert (TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt))
3467 reduction_op = TREE_OPERAND (gimple_assign_rhs1 (stmt), reduc_index);
3469 case GIMPLE_UNARY_RHS:
3470 reduction_op = gimple_assign_rhs1 (stmt);
3472 case GIMPLE_BINARY_RHS:
3473 reduction_op = reduc_index ?
3474 gimple_assign_rhs2 (stmt) : gimple_assign_rhs1 (stmt);
3476 case GIMPLE_TERNARY_RHS:
3477 reduction_op = gimple_op (stmt, reduc_index + 1);
3483 vectype = get_vectype_for_scalar_type (TREE_TYPE (reduction_op));
3484 gcc_assert (vectype);
3485 mode = TYPE_MODE (vectype);
3487 /* 1. Create the reduction def-use cycle:
3488 Set the arguments of REDUCTION_PHIS, i.e., transform
3491 vec_def = phi <null, null> # REDUCTION_PHI
3492 VECT_DEF = vector_stmt # vectorized form of STMT
3498 vec_def = phi <vec_init, VECT_DEF> # REDUCTION_PHI
3499 VECT_DEF = vector_stmt # vectorized form of STMT
3502 (in case of SLP, do it for all the phis). */
3504 /* Get the loop-entry arguments. */
3506 vect_get_slp_defs (reduction_op, NULL_TREE, slp_node, &vec_initial_defs,
3510 vec_initial_defs = VEC_alloc (tree, heap, 1);
3511 /* For the case of reduction, vect_get_vec_def_for_operand returns
3512 the scalar def before the loop, that defines the initial value
3513 of the reduction variable. */
3514 vec_initial_def = vect_get_vec_def_for_operand (reduction_op, stmt,
3516 VEC_quick_push (tree, vec_initial_defs, vec_initial_def);
3519 /* Set phi nodes arguments. */
3520 FOR_EACH_VEC_ELT (gimple, reduction_phis, i, phi)
3522 tree vec_init_def = VEC_index (tree, vec_initial_defs, i);
3523 tree def = VEC_index (tree, vect_defs, i);
3524 for (j = 0; j < ncopies; j++)
3526 /* Set the loop-entry arg of the reduction-phi. */
3527 add_phi_arg (phi, vec_init_def, loop_preheader_edge (loop),
3530 /* Set the loop-latch arg for the reduction-phi. */
3532 def = vect_get_vec_def_for_stmt_copy (vect_unknown_def_type, def);
3534 add_phi_arg (phi, def, loop_latch_edge (loop), UNKNOWN_LOCATION);
3536 if (vect_print_dump_info (REPORT_DETAILS))
3538 fprintf (vect_dump, "transform reduction: created def-use"
3540 print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
3541 fprintf (vect_dump, "\n");
3542 print_gimple_stmt (vect_dump, SSA_NAME_DEF_STMT (def), 0,
3546 phi = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi));
3550 VEC_free (tree, heap, vec_initial_defs);
3552 /* 2. Create epilog code.
3553 The reduction epilog code operates across the elements of the vector
3554 of partial results computed by the vectorized loop.
3555 The reduction epilog code consists of:
3557 step 1: compute the scalar result in a vector (v_out2)
3558 step 2: extract the scalar result (s_out3) from the vector (v_out2)
3559 step 3: adjust the scalar result (s_out3) if needed.
3561 Step 1 can be accomplished using one the following three schemes:
3562 (scheme 1) using reduc_code, if available.
3563 (scheme 2) using whole-vector shifts, if available.
3564 (scheme 3) using a scalar loop. In this case steps 1+2 above are
3567 The overall epilog code looks like this:
3569 s_out0 = phi <s_loop> # original EXIT_PHI
3570 v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
3571 v_out2 = reduce <v_out1> # step 1
3572 s_out3 = extract_field <v_out2, 0> # step 2
3573 s_out4 = adjust_result <s_out3> # step 3
3575 (step 3 is optional, and steps 1 and 2 may be combined).
3576 Lastly, the uses of s_out0 are replaced by s_out4. */
3579 /* 2.1 Create new loop-exit-phis to preserve loop-closed form:
3580 v_out1 = phi <VECT_DEF>
3581 Store them in NEW_PHIS. */
3583 exit_bb = single_exit (loop)->dest;
3584 prev_phi_info = NULL;
3585 new_phis = VEC_alloc (gimple, heap, VEC_length (tree, vect_defs));
3586 FOR_EACH_VEC_ELT (tree, vect_defs, i, def)
3588 for (j = 0; j < ncopies; j++)
3590 phi = create_phi_node (SSA_NAME_VAR (def), exit_bb);
3591 set_vinfo_for_stmt (phi, new_stmt_vec_info (phi, loop_vinfo, NULL));
3593 VEC_quick_push (gimple, new_phis, phi);
3596 def = vect_get_vec_def_for_stmt_copy (dt, def);
3597 STMT_VINFO_RELATED_STMT (prev_phi_info) = phi;
3600 SET_PHI_ARG_DEF (phi, single_exit (loop)->dest_idx, def);
3601 prev_phi_info = vinfo_for_stmt (phi);
3605 /* The epilogue is created for the outer-loop, i.e., for the loop being
3610 exit_bb = single_exit (loop)->dest;
3613 exit_gsi = gsi_after_labels (exit_bb);
3615 /* 2.2 Get the relevant tree-code to use in the epilog for schemes 2,3
3616 (i.e. when reduc_code is not available) and in the final adjustment
3617 code (if needed). Also get the original scalar reduction variable as
3618 defined in the loop. In case STMT is a "pattern-stmt" (i.e. - it
3619 represents a reduction pattern), the tree-code and scalar-def are
3620 taken from the original stmt that the pattern-stmt (STMT) replaces.
3621 Otherwise (it is a regular reduction) - the tree-code and scalar-def
3622 are taken from STMT. */
3624 orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);
3627 /* Regular reduction */
3632 /* Reduction pattern */
3633 stmt_vec_info stmt_vinfo = vinfo_for_stmt (orig_stmt);
3634 gcc_assert (STMT_VINFO_IN_PATTERN_P (stmt_vinfo));
3635 gcc_assert (STMT_VINFO_RELATED_STMT (stmt_vinfo) == stmt);
3638 code = gimple_assign_rhs_code (orig_stmt);
3639 /* For MINUS_EXPR the initial vector is [init_val,0,...,0], therefore,
3640 partial results are added and not subtracted. */
3641 if (code == MINUS_EXPR)
3644 scalar_dest = gimple_assign_lhs (orig_stmt);
3645 scalar_type = TREE_TYPE (scalar_dest);
3646 scalar_results = VEC_alloc (tree, heap, group_size);
3647 new_scalar_dest = vect_create_destination_var (scalar_dest, NULL);
3648 bitsize = TYPE_SIZE (scalar_type);
3650 /* In case this is a reduction in an inner-loop while vectorizing an outer
3651 loop - we don't need to extract a single scalar result at the end of the
3652 inner-loop (unless it is double reduction, i.e., the use of reduction is
3653 outside the outer-loop). The final vector of partial results will be used
3654 in the vectorized outer-loop, or reduced to a scalar result at the end of
3656 if (nested_in_vect_loop && !double_reduc)
3657 goto vect_finalize_reduction;
3659 /* SLP reduction without reduction chain, e.g.,
3663 b2 = operation (b1) */
3664 slp_reduc = (slp_node && !GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)));
3666 /* In case of reduction chain, e.g.,
3669 a3 = operation (a2),
3671 we may end up with more than one vector result. Here we reduce them to
3673 if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)))
3675 tree first_vect = PHI_RESULT (VEC_index (gimple, new_phis, 0));
3678 vec_dest = vect_create_destination_var (scalar_dest, vectype);
3679 for (k = 1; k < VEC_length (gimple, new_phis); k++)
3681 gimple next_phi = VEC_index (gimple, new_phis, k);
3682 tree second_vect = PHI_RESULT (next_phi);
3683 gimple new_vec_stmt;
3685 tmp = build2 (code, vectype, first_vect, second_vect);
3686 new_vec_stmt = gimple_build_assign (vec_dest, tmp);
3687 first_vect = make_ssa_name (vec_dest, new_vec_stmt);
3688 gimple_assign_set_lhs (new_vec_stmt, first_vect);
3689 gsi_insert_before (&exit_gsi, new_vec_stmt, GSI_SAME_STMT);
3692 new_phi_result = first_vect;
3695 new_phi_result = PHI_RESULT (VEC_index (gimple, new_phis, 0));
3697 /* 2.3 Create the reduction code, using one of the three schemes described
3698 above. In SLP we simply need to extract all the elements from the
3699 vector (without reducing them), so we use scalar shifts. */
3700 if (reduc_code != ERROR_MARK && !slp_reduc)
3704 /*** Case 1: Create:
3705 v_out2 = reduc_expr <v_out1> */
3707 if (vect_print_dump_info (REPORT_DETAILS))
3708 fprintf (vect_dump, "Reduce using direct vector reduction.");
3710 vec_dest = vect_create_destination_var (scalar_dest, vectype);
3711 tmp = build1 (reduc_code, vectype, new_phi_result);
3712 epilog_stmt = gimple_build_assign (vec_dest, tmp);
3713 new_temp = make_ssa_name (vec_dest, epilog_stmt);
3714 gimple_assign_set_lhs (epilog_stmt, new_temp);
3715 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
3717 extract_scalar_result = true;
3721 enum tree_code shift_code = ERROR_MARK;
3722 bool have_whole_vector_shift = true;
3724 int element_bitsize = tree_low_cst (bitsize, 1);
3725 int vec_size_in_bits = tree_low_cst (TYPE_SIZE (vectype), 1);
3728 if (optab_handler (vec_shr_optab, mode) != CODE_FOR_nothing)
3729 shift_code = VEC_RSHIFT_EXPR;
3731 have_whole_vector_shift = false;
3733 /* Regardless of whether we have a whole vector shift, if we're
3734 emulating the operation via tree-vect-generic, we don't want
3735 to use it. Only the first round of the reduction is likely
3736 to still be profitable via emulation. */
3737 /* ??? It might be better to emit a reduction tree code here, so that
3738 tree-vect-generic can expand the first round via bit tricks. */
3739 if (!VECTOR_MODE_P (mode))
3740 have_whole_vector_shift = false;
3743 optab optab = optab_for_tree_code (code, vectype, optab_default);
3744 if (optab_handler (optab, mode) == CODE_FOR_nothing)
3745 have_whole_vector_shift = false;
3748 if (have_whole_vector_shift && !slp_reduc)
3750 /*** Case 2: Create:
3751 for (offset = VS/2; offset >= element_size; offset/=2)
3753 Create: va' = vec_shift <va, offset>
3754 Create: va = vop <va, va'>
3757 if (vect_print_dump_info (REPORT_DETAILS))
3758 fprintf (vect_dump, "Reduce using vector shifts");
3760 vec_dest = vect_create_destination_var (scalar_dest, vectype);
3761 new_temp = new_phi_result;
3762 for (bit_offset = vec_size_in_bits/2;
3763 bit_offset >= element_bitsize;
3766 tree bitpos = size_int (bit_offset);
3768 epilog_stmt = gimple_build_assign_with_ops (shift_code,
3769 vec_dest, new_temp, bitpos);
3770 new_name = make_ssa_name (vec_dest, epilog_stmt);
3771 gimple_assign_set_lhs (epilog_stmt, new_name);
3772 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
3774 epilog_stmt = gimple_build_assign_with_ops (code, vec_dest,
3775 new_name, new_temp);
3776 new_temp = make_ssa_name (vec_dest, epilog_stmt);
3777 gimple_assign_set_lhs (epilog_stmt, new_temp);
3778 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
3781 extract_scalar_result = true;
3787 /*** Case 3: Create:
3788 s = extract_field <v_out2, 0>
3789 for (offset = element_size;
3790 offset < vector_size;
3791 offset += element_size;)
3793 Create: s' = extract_field <v_out2, offset>
3794 Create: s = op <s, s'> // For non SLP cases
3797 if (vect_print_dump_info (REPORT_DETAILS))
3798 fprintf (vect_dump, "Reduce using scalar code. ");
3800 vec_size_in_bits = tree_low_cst (TYPE_SIZE (vectype), 1);
3801 FOR_EACH_VEC_ELT (gimple, new_phis, i, new_phi)
3803 vec_temp = PHI_RESULT (new_phi);
3804 rhs = build3 (BIT_FIELD_REF, scalar_type, vec_temp, bitsize,
3806 epilog_stmt = gimple_build_assign (new_scalar_dest, rhs);
3807 new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
3808 gimple_assign_set_lhs (epilog_stmt, new_temp);
3809 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
3811 /* In SLP we don't need to apply reduction operation, so we just
3812 collect s' values in SCALAR_RESULTS. */
3814 VEC_safe_push (tree, heap, scalar_results, new_temp);
3816 for (bit_offset = element_bitsize;
3817 bit_offset < vec_size_in_bits;
3818 bit_offset += element_bitsize)
3820 tree bitpos = bitsize_int (bit_offset);
3821 tree rhs = build3 (BIT_FIELD_REF, scalar_type, vec_temp,
3824 epilog_stmt = gimple_build_assign (new_scalar_dest, rhs);
3825 new_name = make_ssa_name (new_scalar_dest, epilog_stmt);
3826 gimple_assign_set_lhs (epilog_stmt, new_name);
3827 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
3831 /* In SLP we don't need to apply reduction operation, so
3832 we just collect s' values in SCALAR_RESULTS. */
3833 new_temp = new_name;
3834 VEC_safe_push (tree, heap, scalar_results, new_name);
3838 epilog_stmt = gimple_build_assign_with_ops (code,
3839 new_scalar_dest, new_name, new_temp);
3840 new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
3841 gimple_assign_set_lhs (epilog_stmt, new_temp);
3842 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
3847 /* The only case where we need to reduce scalar results in SLP, is
3848 unrolling. If the size of SCALAR_RESULTS is greater than
3849 GROUP_SIZE, we reduce them combining elements modulo
3853 tree res, first_res, new_res;
3856 /* Reduce multiple scalar results in case of SLP unrolling. */
3857 for (j = group_size; VEC_iterate (tree, scalar_results, j, res);
3860 first_res = VEC_index (tree, scalar_results, j % group_size);
3861 new_stmt = gimple_build_assign_with_ops (code,
3862 new_scalar_dest, first_res, res);
3863 new_res = make_ssa_name (new_scalar_dest, new_stmt);
3864 gimple_assign_set_lhs (new_stmt, new_res);
3865 gsi_insert_before (&exit_gsi, new_stmt, GSI_SAME_STMT);
3866 VEC_replace (tree, scalar_results, j % group_size, new_res);
3870 /* Not SLP - we have one scalar to keep in SCALAR_RESULTS. */
3871 VEC_safe_push (tree, heap, scalar_results, new_temp);
3873 extract_scalar_result = false;
3877 /* 2.4 Extract the final scalar result. Create:
3878 s_out3 = extract_field <v_out2, bitpos> */
3880 if (extract_scalar_result)
3884 if (vect_print_dump_info (REPORT_DETAILS))
3885 fprintf (vect_dump, "extract scalar result");
3887 if (BYTES_BIG_ENDIAN)
3888 bitpos = size_binop (MULT_EXPR,
3889 bitsize_int (TYPE_VECTOR_SUBPARTS (vectype) - 1),
3890 TYPE_SIZE (scalar_type));
3892 bitpos = bitsize_zero_node;
3894 rhs = build3 (BIT_FIELD_REF, scalar_type, new_temp, bitsize, bitpos);
3895 epilog_stmt = gimple_build_assign (new_scalar_dest, rhs);
3896 new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
3897 gimple_assign_set_lhs (epilog_stmt, new_temp);
3898 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
3899 VEC_safe_push (tree, heap, scalar_results, new_temp);
3902 vect_finalize_reduction:
3907 /* 2.5 Adjust the final result by the initial value of the reduction
3908 variable. (When such adjustment is not needed, then
3909 'adjustment_def' is zero). For example, if code is PLUS we create:
3910 new_temp = loop_exit_def + adjustment_def */
3914 gcc_assert (!slp_reduc);
3915 if (nested_in_vect_loop)
3917 new_phi = VEC_index (gimple, new_phis, 0);
3918 gcc_assert (TREE_CODE (TREE_TYPE (adjustment_def)) == VECTOR_TYPE);
3919 expr = build2 (code, vectype, PHI_RESULT (new_phi), adjustment_def);
3920 new_dest = vect_create_destination_var (scalar_dest, vectype);
3924 new_temp = VEC_index (tree, scalar_results, 0);
3925 gcc_assert (TREE_CODE (TREE_TYPE (adjustment_def)) != VECTOR_TYPE);
3926 expr = build2 (code, scalar_type, new_temp, adjustment_def);
3927 new_dest = vect_create_destination_var (scalar_dest, scalar_type);
3930 epilog_stmt = gimple_build_assign (new_dest, expr);
3931 new_temp = make_ssa_name (new_dest, epilog_stmt);
3932 gimple_assign_set_lhs (epilog_stmt, new_temp);
3933 SSA_NAME_DEF_STMT (new_temp) = epilog_stmt;
3934 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
3935 if (nested_in_vect_loop)
3937 set_vinfo_for_stmt (epilog_stmt,
3938 new_stmt_vec_info (epilog_stmt, loop_vinfo,
3940 STMT_VINFO_RELATED_STMT (vinfo_for_stmt (epilog_stmt)) =
3941 STMT_VINFO_RELATED_STMT (vinfo_for_stmt (new_phi));
3944 VEC_quick_push (tree, scalar_results, new_temp);
3946 VEC_replace (tree, scalar_results, 0, new_temp);
3949 VEC_replace (tree, scalar_results, 0, new_temp);
3951 VEC_replace (gimple, new_phis, 0, epilog_stmt);
3954 /* 2.6 Handle the loop-exit phis. Replace the uses of scalar loop-exit
3955 phis with new adjusted scalar results, i.e., replace use <s_out0>
3960 s_out0 = phi <s_loop> # (scalar) EXIT_PHI
3961 v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
3962 v_out2 = reduce <v_out1>
3963 s_out3 = extract_field <v_out2, 0>
3964 s_out4 = adjust_result <s_out3>
3971 s_out0 = phi <s_loop> # (scalar) EXIT_PHI
3972 v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
3973 v_out2 = reduce <v_out1>
3974 s_out3 = extract_field <v_out2, 0>
3975 s_out4 = adjust_result <s_out3>
3980 /* In SLP reduction chain we reduce vector results into one vector if
3981 necessary, hence we set here GROUP_SIZE to 1. SCALAR_DEST is the LHS of
3982 the last stmt in the reduction chain, since we are looking for the loop
3984 if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)))
3986 scalar_dest = gimple_assign_lhs (VEC_index (gimple,
3987 SLP_TREE_SCALAR_STMTS (slp_node),
3992 /* In SLP we may have several statements in NEW_PHIS and REDUCTION_PHIS (in
3993 case that GROUP_SIZE is greater than vectorization factor). Therefore, we
3994 need to match SCALAR_RESULTS with corresponding statements. The first
3995 (GROUP_SIZE / number of new vector stmts) scalar results correspond to
3996 the first vector stmt, etc.
3997 (RATIO is equal to (GROUP_SIZE / number of new vector stmts)). */
3998 if (group_size > VEC_length (gimple, new_phis))
4000 ratio = group_size / VEC_length (gimple, new_phis);
4001 gcc_assert (!(group_size % VEC_length (gimple, new_phis)));
4006 for (k = 0; k < group_size; k++)
4010 epilog_stmt = VEC_index (gimple, new_phis, k / ratio);
4011 reduction_phi = VEC_index (gimple, reduction_phis, k / ratio);
4016 gimple current_stmt = VEC_index (gimple,
4017 SLP_TREE_SCALAR_STMTS (slp_node), k);
4019 orig_stmt = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (current_stmt));
4020 /* SLP statements can't participate in patterns. */
4021 gcc_assert (!orig_stmt);
4022 scalar_dest = gimple_assign_lhs (current_stmt);
4025 phis = VEC_alloc (gimple, heap, 3);
4026 /* Find the loop-closed-use at the loop exit of the original scalar
4027 result. (The reduction result is expected to have two immediate uses -
4028 one at the latch block, and one at the loop exit). */
4029 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, scalar_dest)
4030 if (!flow_bb_inside_loop_p (loop, gimple_bb (USE_STMT (use_p))))
4031 VEC_safe_push (gimple, heap, phis, USE_STMT (use_p));
4033 /* We expect to have found an exit_phi because of loop-closed-ssa
4035 gcc_assert (!VEC_empty (gimple, phis));
4037 FOR_EACH_VEC_ELT (gimple, phis, i, exit_phi)
4041 stmt_vec_info exit_phi_vinfo = vinfo_for_stmt (exit_phi);
4044 /* FORNOW. Currently not supporting the case that an inner-loop
4045 reduction is not used in the outer-loop (but only outside the
4046 outer-loop), unless it is double reduction. */
4047 gcc_assert ((STMT_VINFO_RELEVANT_P (exit_phi_vinfo)
4048 && !STMT_VINFO_LIVE_P (exit_phi_vinfo))
4051 STMT_VINFO_VEC_STMT (exit_phi_vinfo) = epilog_stmt;
4053 || STMT_VINFO_DEF_TYPE (exit_phi_vinfo)
4054 != vect_double_reduction_def)
4057 /* Handle double reduction:
4059 stmt1: s1 = phi <s0, s2> - double reduction phi (outer loop)
4060 stmt2: s3 = phi <s1, s4> - (regular) reduc phi (inner loop)
4061 stmt3: s4 = use (s3) - (regular) reduc stmt (inner loop)
4062 stmt4: s2 = phi <s4> - double reduction stmt (outer loop)
4064 At that point the regular reduction (stmt2 and stmt3) is
4065 already vectorized, as well as the exit phi node, stmt4.
4066 Here we vectorize the phi node of double reduction, stmt1, and
4067 update all relevant statements. */
4069 /* Go through all the uses of s2 to find double reduction phi
4070 node, i.e., stmt1 above. */
4071 orig_name = PHI_RESULT (exit_phi);
4072 FOR_EACH_IMM_USE_STMT (use_stmt, imm_iter, orig_name)
4074 stmt_vec_info use_stmt_vinfo = vinfo_for_stmt (use_stmt);
4075 stmt_vec_info new_phi_vinfo;
4076 tree vect_phi_init, preheader_arg, vect_phi_res, init_def;
4077 basic_block bb = gimple_bb (use_stmt);
4080 /* Check that USE_STMT is really double reduction phi
4082 if (gimple_code (use_stmt) != GIMPLE_PHI
4083 || gimple_phi_num_args (use_stmt) != 2
4085 || STMT_VINFO_DEF_TYPE (use_stmt_vinfo)
4086 != vect_double_reduction_def
4087 || bb->loop_father != outer_loop)
4090 /* Create vector phi node for double reduction:
4091 vs1 = phi <vs0, vs2>
4092 vs1 was created previously in this function by a call to
4093 vect_get_vec_def_for_operand and is stored in
4095 vs2 is defined by EPILOG_STMT, the vectorized EXIT_PHI;
4096 vs0 is created here. */
4098 /* Create vector phi node. */
4099 vect_phi = create_phi_node (vec_initial_def, bb);
4100 new_phi_vinfo = new_stmt_vec_info (vect_phi,
4101 loop_vec_info_for_loop (outer_loop), NULL);
4102 set_vinfo_for_stmt (vect_phi, new_phi_vinfo);
4104 /* Create vs0 - initial def of the double reduction phi. */
4105 preheader_arg = PHI_ARG_DEF_FROM_EDGE (use_stmt,
4106 loop_preheader_edge (outer_loop));
4107 init_def = get_initial_def_for_reduction (stmt,
4108 preheader_arg, NULL);
4109 vect_phi_init = vect_init_vector (use_stmt, init_def,
4112 /* Update phi node arguments with vs0 and vs2. */
4113 add_phi_arg (vect_phi, vect_phi_init,
4114 loop_preheader_edge (outer_loop),
4116 add_phi_arg (vect_phi, PHI_RESULT (epilog_stmt),
4117 loop_latch_edge (outer_loop), UNKNOWN_LOCATION);
4118 if (vect_print_dump_info (REPORT_DETAILS))
4120 fprintf (vect_dump, "created double reduction phi "
4122 print_gimple_stmt (vect_dump, vect_phi, 0, TDF_SLIM);
4125 vect_phi_res = PHI_RESULT (vect_phi);
4127 /* Replace the use, i.e., set the correct vs1 in the regular
4128 reduction phi node. FORNOW, NCOPIES is always 1, so the
4129 loop is redundant. */
4130 use = reduction_phi;
4131 for (j = 0; j < ncopies; j++)
4133 edge pr_edge = loop_preheader_edge (loop);
4134 SET_PHI_ARG_DEF (use, pr_edge->dest_idx, vect_phi_res);
4135 use = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (use));
4141 VEC_free (gimple, heap, phis);
4142 if (nested_in_vect_loop)
4150 phis = VEC_alloc (gimple, heap, 3);
4151 /* Find the loop-closed-use at the loop exit of the original scalar
4152 result. (The reduction result is expected to have two immediate uses,
4153 one at the latch block, and one at the loop exit). For double
4154 reductions we are looking for exit phis of the outer loop. */
4155 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, scalar_dest)
4157 if (!flow_bb_inside_loop_p (loop, gimple_bb (USE_STMT (use_p))))
4158 VEC_safe_push (gimple, heap, phis, USE_STMT (use_p));
4161 if (double_reduc && gimple_code (USE_STMT (use_p)) == GIMPLE_PHI)
4163 tree phi_res = PHI_RESULT (USE_STMT (use_p));
4165 FOR_EACH_IMM_USE_FAST (phi_use_p, phi_imm_iter, phi_res)
4167 if (!flow_bb_inside_loop_p (loop,
4168 gimple_bb (USE_STMT (phi_use_p))))
4169 VEC_safe_push (gimple, heap, phis,
4170 USE_STMT (phi_use_p));
4176 FOR_EACH_VEC_ELT (gimple, phis, i, exit_phi)
4178 /* Replace the uses: */
4179 orig_name = PHI_RESULT (exit_phi);
4180 scalar_result = VEC_index (tree, scalar_results, k);
4181 FOR_EACH_IMM_USE_STMT (use_stmt, imm_iter, orig_name)
4182 FOR_EACH_IMM_USE_ON_STMT (use_p, imm_iter)
4183 SET_USE (use_p, scalar_result);
4186 VEC_free (gimple, heap, phis);
4189 VEC_free (tree, heap, scalar_results);
4190 VEC_free (gimple, heap, new_phis);
4194 /* Function vectorizable_reduction.
4196 Check if STMT performs a reduction operation that can be vectorized.
4197 If VEC_STMT is also passed, vectorize the STMT: create a vectorized
4198 stmt to replace it, put it in VEC_STMT, and insert it at GSI.
4199 Return FALSE if not a vectorizable STMT, TRUE otherwise.
4201 This function also handles reduction idioms (patterns) that have been
4202 recognized in advance during vect_pattern_recog. In this case, STMT may be
4204 X = pattern_expr (arg0, arg1, ..., X)
4205 and it's STMT_VINFO_RELATED_STMT points to the last stmt in the original
4206 sequence that had been detected and replaced by the pattern-stmt (STMT).
4208 In some cases of reduction patterns, the type of the reduction variable X is
4209 different than the type of the other arguments of STMT.
4210 In such cases, the vectype that is used when transforming STMT into a vector
4211 stmt is different than the vectype that is used to determine the
4212 vectorization factor, because it consists of a different number of elements
4213 than the actual number of elements that are being operated upon in parallel.
4215 For example, consider an accumulation of shorts into an int accumulator.
4216 On some targets it's possible to vectorize this pattern operating on 8
4217 shorts at a time (hence, the vectype for purposes of determining the
4218 vectorization factor should be V8HI); on the other hand, the vectype that
4219 is used to create the vector form is actually V4SI (the type of the result).
4221 Upon entry to this function, STMT_VINFO_VECTYPE records the vectype that
4222 indicates what is the actual level of parallelism (V8HI in the example), so
4223 that the right vectorization factor would be derived. This vectype
4224 corresponds to the type of arguments to the reduction stmt, and should *NOT*
4225 be used to create the vectorized stmt. The right vectype for the vectorized
4226 stmt is obtained from the type of the result X:
4227 get_vectype_for_scalar_type (TREE_TYPE (X))
4229 This means that, contrary to "regular" reductions (or "regular" stmts in
4230 general), the following equation:
4231 STMT_VINFO_VECTYPE == get_vectype_for_scalar_type (TREE_TYPE (X))
4232 does *NOT* necessarily hold for reduction patterns. */
4235 vectorizable_reduction (gimple stmt, gimple_stmt_iterator *gsi,
4236 gimple *vec_stmt, slp_tree slp_node)
4240 tree loop_vec_def0 = NULL_TREE, loop_vec_def1 = NULL_TREE;
4241 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
4242 tree vectype_out = STMT_VINFO_VECTYPE (stmt_info);
4243 tree vectype_in = NULL_TREE;
4244 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
4245 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
4246 enum tree_code code, orig_code, epilog_reduc_code;
4247 enum machine_mode vec_mode;
4249 optab optab, reduc_optab;
4250 tree new_temp = NULL_TREE;
4253 enum vect_def_type dt;
4254 gimple new_phi = NULL;
4258 stmt_vec_info orig_stmt_info;
4259 tree expr = NULL_TREE;
4263 stmt_vec_info prev_stmt_info, prev_phi_info;
4264 bool single_defuse_cycle = false;
4265 tree reduc_def = NULL_TREE;
4266 gimple new_stmt = NULL;
4269 bool nested_cycle = false, found_nested_cycle_def = false;
4270 gimple reduc_def_stmt = NULL;
4271 /* The default is that the reduction variable is the last in statement. */
4272 int reduc_index = 2;
4273 bool double_reduc = false, dummy;
4275 struct loop * def_stmt_loop, *outer_loop = NULL;
4277 gimple def_arg_stmt;
4278 VEC (tree, heap) *vec_oprnds0 = NULL, *vec_oprnds1 = NULL, *vect_defs = NULL;
4279 VEC (gimple, heap) *phis = NULL;
4281 tree def0, def1, tem;
4283 /* In case of reduction chain we switch to the first stmt in the chain, but
4284 we don't update STMT_INFO, since only the last stmt is marked as reduction
4285 and has reduction properties. */
4286 if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)))
4287 stmt = GROUP_FIRST_ELEMENT (stmt_info);
4289 if (nested_in_vect_loop_p (loop, stmt))
4293 nested_cycle = true;
4296 /* 1. Is vectorizable reduction? */
4297 /* Not supportable if the reduction variable is used in the loop, unless
4298 it's a reduction chain. */
4299 if (STMT_VINFO_RELEVANT (stmt_info) > vect_used_in_outer
4300 && !GROUP_FIRST_ELEMENT (stmt_info))
4303 /* Reductions that are not used even in an enclosing outer-loop,
4304 are expected to be "live" (used out of the loop). */
4305 if (STMT_VINFO_RELEVANT (stmt_info) == vect_unused_in_scope
4306 && !STMT_VINFO_LIVE_P (stmt_info))
4309 /* Make sure it was already recognized as a reduction computation. */
4310 if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_reduction_def
4311 && STMT_VINFO_DEF_TYPE (stmt_info) != vect_nested_cycle)
4314 /* 2. Has this been recognized as a reduction pattern?
4316 Check if STMT represents a pattern that has been recognized
4317 in earlier analysis stages. For stmts that represent a pattern,
4318 the STMT_VINFO_RELATED_STMT field records the last stmt in
4319 the original sequence that constitutes the pattern. */
4321 orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);
4324 orig_stmt_info = vinfo_for_stmt (orig_stmt);
4325 gcc_assert (STMT_VINFO_RELATED_STMT (orig_stmt_info) == stmt);
4326 gcc_assert (STMT_VINFO_IN_PATTERN_P (orig_stmt_info));
4327 gcc_assert (!STMT_VINFO_IN_PATTERN_P (stmt_info));
4330 /* 3. Check the operands of the operation. The first operands are defined
4331 inside the loop body. The last operand is the reduction variable,
4332 which is defined by the loop-header-phi. */
4334 gcc_assert (is_gimple_assign (stmt));
4337 switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt)))
4339 case GIMPLE_SINGLE_RHS:
4340 op_type = TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt));
4341 if (op_type == ternary_op)
4343 tree rhs = gimple_assign_rhs1 (stmt);
4344 ops[0] = TREE_OPERAND (rhs, 0);
4345 ops[1] = TREE_OPERAND (rhs, 1);
4346 ops[2] = TREE_OPERAND (rhs, 2);
4347 code = TREE_CODE (rhs);
4353 case GIMPLE_BINARY_RHS:
4354 code = gimple_assign_rhs_code (stmt);
4355 op_type = TREE_CODE_LENGTH (code);
4356 gcc_assert (op_type == binary_op);
4357 ops[0] = gimple_assign_rhs1 (stmt);
4358 ops[1] = gimple_assign_rhs2 (stmt);
4361 case GIMPLE_TERNARY_RHS:
4362 code = gimple_assign_rhs_code (stmt);
4363 op_type = TREE_CODE_LENGTH (code);
4364 gcc_assert (op_type == ternary_op);
4365 ops[0] = gimple_assign_rhs1 (stmt);
4366 ops[1] = gimple_assign_rhs2 (stmt);
4367 ops[2] = gimple_assign_rhs3 (stmt);
4370 case GIMPLE_UNARY_RHS:
4377 scalar_dest = gimple_assign_lhs (stmt);
4378 scalar_type = TREE_TYPE (scalar_dest);
4379 if (!POINTER_TYPE_P (scalar_type) && !INTEGRAL_TYPE_P (scalar_type)
4380 && !SCALAR_FLOAT_TYPE_P (scalar_type))
4383 /* All uses but the last are expected to be defined in the loop.
4384 The last use is the reduction variable. In case of nested cycle this
4385 assumption is not true: we use reduc_index to record the index of the
4386 reduction variable. */
4387 for (i = 0; i < op_type-1; i++)
4389 /* The condition of COND_EXPR is checked in vectorizable_condition(). */
4390 if (i == 0 && code == COND_EXPR)
4393 is_simple_use = vect_is_simple_use_1 (ops[i], loop_vinfo, NULL,
4394 &def_stmt, &def, &dt, &tem);
4397 gcc_assert (is_simple_use);
4399 if (dt != vect_internal_def
4400 && dt != vect_external_def
4401 && dt != vect_constant_def
4402 && dt != vect_induction_def
4403 && !(dt == vect_nested_cycle && nested_cycle))
4406 if (dt == vect_nested_cycle)
4408 found_nested_cycle_def = true;
4409 reduc_def_stmt = def_stmt;
4414 is_simple_use = vect_is_simple_use_1 (ops[i], loop_vinfo, NULL, &def_stmt,
4418 gcc_assert (is_simple_use);
4419 gcc_assert (dt == vect_reduction_def
4420 || dt == vect_nested_cycle
4421 || ((dt == vect_internal_def || dt == vect_external_def
4422 || dt == vect_constant_def || dt == vect_induction_def)
4423 && nested_cycle && found_nested_cycle_def));
4424 if (!found_nested_cycle_def)
4425 reduc_def_stmt = def_stmt;
4427 gcc_assert (gimple_code (reduc_def_stmt) == GIMPLE_PHI);
4429 gcc_assert (orig_stmt == vect_is_simple_reduction (loop_vinfo,
4435 gimple tmp = vect_is_simple_reduction (loop_vinfo, reduc_def_stmt,
4436 !nested_cycle, &dummy);
4437 /* We changed STMT to be the first stmt in reduction chain, hence we
4438 check that in this case the first element in the chain is STMT. */
4439 gcc_assert (stmt == tmp
4440 || GROUP_FIRST_ELEMENT (vinfo_for_stmt (tmp)) == stmt);
4443 if (STMT_VINFO_LIVE_P (vinfo_for_stmt (reduc_def_stmt)))
4446 if (slp_node || PURE_SLP_STMT (stmt_info))
4449 ncopies = (LOOP_VINFO_VECT_FACTOR (loop_vinfo)
4450 / TYPE_VECTOR_SUBPARTS (vectype_in));
4452 gcc_assert (ncopies >= 1);
4454 vec_mode = TYPE_MODE (vectype_in);
4456 if (code == COND_EXPR)
4458 if (!vectorizable_condition (stmt, gsi, NULL, ops[reduc_index], 0))
4460 if (vect_print_dump_info (REPORT_DETAILS))
4461 fprintf (vect_dump, "unsupported condition in reduction");
4468 /* 4. Supportable by target? */
4470 /* 4.1. check support for the operation in the loop */
4471 optab = optab_for_tree_code (code, vectype_in, optab_default);
4474 if (vect_print_dump_info (REPORT_DETAILS))
4475 fprintf (vect_dump, "no optab.");
4480 if (optab_handler (optab, vec_mode) == CODE_FOR_nothing)
4482 if (vect_print_dump_info (REPORT_DETAILS))
4483 fprintf (vect_dump, "op not supported by target.");
4485 if (GET_MODE_SIZE (vec_mode) != UNITS_PER_WORD
4486 || LOOP_VINFO_VECT_FACTOR (loop_vinfo)
4487 < vect_min_worthwhile_factor (code))
4490 if (vect_print_dump_info (REPORT_DETAILS))
4491 fprintf (vect_dump, "proceeding using word mode.");
4494 /* Worthwhile without SIMD support? */
4495 if (!VECTOR_MODE_P (TYPE_MODE (vectype_in))
4496 && LOOP_VINFO_VECT_FACTOR (loop_vinfo)
4497 < vect_min_worthwhile_factor (code))
4499 if (vect_print_dump_info (REPORT_DETAILS))
4500 fprintf (vect_dump, "not worthwhile without SIMD support.");
4506 /* 4.2. Check support for the epilog operation.
4508 If STMT represents a reduction pattern, then the type of the
4509 reduction variable may be different than the type of the rest
4510 of the arguments. For example, consider the case of accumulation
4511 of shorts into an int accumulator; The original code:
4512 S1: int_a = (int) short_a;
4513 orig_stmt-> S2: int_acc = plus <int_a ,int_acc>;
4516 STMT: int_acc = widen_sum <short_a, int_acc>
4519 1. The tree-code that is used to create the vector operation in the
4520 epilog code (that reduces the partial results) is not the
4521 tree-code of STMT, but is rather the tree-code of the original
4522 stmt from the pattern that STMT is replacing. I.e, in the example
4523 above we want to use 'widen_sum' in the loop, but 'plus' in the
4525 2. The type (mode) we use to check available target support
4526 for the vector operation to be created in the *epilog*, is
4527 determined by the type of the reduction variable (in the example
4528 above we'd check this: optab_handler (plus_optab, vect_int_mode])).
4529 However the type (mode) we use to check available target support
4530 for the vector operation to be created *inside the loop*, is
4531 determined by the type of the other arguments to STMT (in the
4532 example we'd check this: optab_handler (widen_sum_optab,
4535 This is contrary to "regular" reductions, in which the types of all
4536 the arguments are the same as the type of the reduction variable.
4537 For "regular" reductions we can therefore use the same vector type
4538 (and also the same tree-code) when generating the epilog code and
4539 when generating the code inside the loop. */
4543 /* This is a reduction pattern: get the vectype from the type of the
4544 reduction variable, and get the tree-code from orig_stmt. */
4545 orig_code = gimple_assign_rhs_code (orig_stmt);
4546 gcc_assert (vectype_out);
4547 vec_mode = TYPE_MODE (vectype_out);
4551 /* Regular reduction: use the same vectype and tree-code as used for
4552 the vector code inside the loop can be used for the epilog code. */
4558 def_bb = gimple_bb (reduc_def_stmt);
4559 def_stmt_loop = def_bb->loop_father;
4560 def_arg = PHI_ARG_DEF_FROM_EDGE (reduc_def_stmt,
4561 loop_preheader_edge (def_stmt_loop));
4562 if (TREE_CODE (def_arg) == SSA_NAME
4563 && (def_arg_stmt = SSA_NAME_DEF_STMT (def_arg))
4564 && gimple_code (def_arg_stmt) == GIMPLE_PHI
4565 && flow_bb_inside_loop_p (outer_loop, gimple_bb (def_arg_stmt))
4566 && vinfo_for_stmt (def_arg_stmt)
4567 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_arg_stmt))
4568 == vect_double_reduction_def)
4569 double_reduc = true;
4572 epilog_reduc_code = ERROR_MARK;
4573 if (reduction_code_for_scalar_code (orig_code, &epilog_reduc_code))
4575 reduc_optab = optab_for_tree_code (epilog_reduc_code, vectype_out,
4579 if (vect_print_dump_info (REPORT_DETAILS))
4580 fprintf (vect_dump, "no optab for reduction.");
4582 epilog_reduc_code = ERROR_MARK;
4586 && optab_handler (reduc_optab, vec_mode) == CODE_FOR_nothing)
4588 if (vect_print_dump_info (REPORT_DETAILS))
4589 fprintf (vect_dump, "reduc op not supported by target.");
4591 epilog_reduc_code = ERROR_MARK;
4596 if (!nested_cycle || double_reduc)
4598 if (vect_print_dump_info (REPORT_DETAILS))
4599 fprintf (vect_dump, "no reduc code for scalar code.");
4605 if (double_reduc && ncopies > 1)
4607 if (vect_print_dump_info (REPORT_DETAILS))
4608 fprintf (vect_dump, "multiple types in double reduction");
4613 /* In case of widenning multiplication by a constant, we update the type
4614 of the constant to be the type of the other operand. We check that the
4615 constant fits the type in the pattern recognition pass. */
4616 if (code == DOT_PROD_EXPR
4617 && !types_compatible_p (TREE_TYPE (ops[0]), TREE_TYPE (ops[1])))
4619 if (TREE_CODE (ops[0]) == INTEGER_CST)
4620 ops[0] = fold_convert (TREE_TYPE (ops[1]), ops[0]);
4621 else if (TREE_CODE (ops[1]) == INTEGER_CST)
4622 ops[1] = fold_convert (TREE_TYPE (ops[0]), ops[1]);
4625 if (vect_print_dump_info (REPORT_DETAILS))
4626 fprintf (vect_dump, "invalid types in dot-prod");
4632 if (!vec_stmt) /* transformation not required. */
4634 if (!vect_model_reduction_cost (stmt_info, epilog_reduc_code, ncopies))
4636 STMT_VINFO_TYPE (stmt_info) = reduc_vec_info_type;
4642 if (vect_print_dump_info (REPORT_DETAILS))
4643 fprintf (vect_dump, "transform reduction.");
4645 /* FORNOW: Multiple types are not supported for condition. */
4646 if (code == COND_EXPR)
4647 gcc_assert (ncopies == 1);
4649 /* Create the destination vector */
4650 vec_dest = vect_create_destination_var (scalar_dest, vectype_out);
4652 /* In case the vectorization factor (VF) is bigger than the number
4653 of elements that we can fit in a vectype (nunits), we have to generate
4654 more than one vector stmt - i.e - we need to "unroll" the
4655 vector stmt by a factor VF/nunits. For more details see documentation
4656 in vectorizable_operation. */
4658 /* If the reduction is used in an outer loop we need to generate
4659 VF intermediate results, like so (e.g. for ncopies=2):
4664 (i.e. we generate VF results in 2 registers).
4665 In this case we have a separate def-use cycle for each copy, and therefore
4666 for each copy we get the vector def for the reduction variable from the
4667 respective phi node created for this copy.
4669 Otherwise (the reduction is unused in the loop nest), we can combine
4670 together intermediate results, like so (e.g. for ncopies=2):
4674 (i.e. we generate VF/2 results in a single register).
4675 In this case for each copy we get the vector def for the reduction variable
4676 from the vectorized reduction operation generated in the previous iteration.
4679 if (STMT_VINFO_RELEVANT (stmt_info) == vect_unused_in_scope)
4681 single_defuse_cycle = true;
4685 epilog_copies = ncopies;
4687 prev_stmt_info = NULL;
4688 prev_phi_info = NULL;
4691 vec_num = SLP_TREE_NUMBER_OF_VEC_STMTS (slp_node);
4692 gcc_assert (TYPE_VECTOR_SUBPARTS (vectype_out)
4693 == TYPE_VECTOR_SUBPARTS (vectype_in));
4698 vec_oprnds0 = VEC_alloc (tree, heap, 1);
4699 if (op_type == ternary_op)
4700 vec_oprnds1 = VEC_alloc (tree, heap, 1);
4703 phis = VEC_alloc (gimple, heap, vec_num);
4704 vect_defs = VEC_alloc (tree, heap, vec_num);
4706 VEC_quick_push (tree, vect_defs, NULL_TREE);
4708 for (j = 0; j < ncopies; j++)
4710 if (j == 0 || !single_defuse_cycle)
4712 for (i = 0; i < vec_num; i++)
4714 /* Create the reduction-phi that defines the reduction
4716 new_phi = create_phi_node (vec_dest, loop->header);
4717 set_vinfo_for_stmt (new_phi,
4718 new_stmt_vec_info (new_phi, loop_vinfo,
4720 if (j == 0 || slp_node)
4721 VEC_quick_push (gimple, phis, new_phi);
4725 if (code == COND_EXPR)
4727 gcc_assert (!slp_node);
4728 vectorizable_condition (stmt, gsi, vec_stmt,
4729 PHI_RESULT (VEC_index (gimple, phis, 0)),
4731 /* Multiple types are not supported for condition. */
4738 tree op0, op1 = NULL_TREE;
4740 op0 = ops[!reduc_index];
4741 if (op_type == ternary_op)
4743 if (reduc_index == 0)
4750 vect_get_slp_defs (op0, op1, slp_node, &vec_oprnds0, &vec_oprnds1,
4754 loop_vec_def0 = vect_get_vec_def_for_operand (ops[!reduc_index],
4756 VEC_quick_push (tree, vec_oprnds0, loop_vec_def0);
4757 if (op_type == ternary_op)
4759 loop_vec_def1 = vect_get_vec_def_for_operand (op1, stmt,
4761 VEC_quick_push (tree, vec_oprnds1, loop_vec_def1);
4769 enum vect_def_type dt = vect_unknown_def_type; /* Dummy */
4770 loop_vec_def0 = vect_get_vec_def_for_stmt_copy (dt, loop_vec_def0);
4771 VEC_replace (tree, vec_oprnds0, 0, loop_vec_def0);
4772 if (op_type == ternary_op)
4774 loop_vec_def1 = vect_get_vec_def_for_stmt_copy (dt,
4776 VEC_replace (tree, vec_oprnds1, 0, loop_vec_def1);
4780 if (single_defuse_cycle)
4781 reduc_def = gimple_assign_lhs (new_stmt);
4783 STMT_VINFO_RELATED_STMT (prev_phi_info) = new_phi;
4786 FOR_EACH_VEC_ELT (tree, vec_oprnds0, i, def0)
4789 reduc_def = PHI_RESULT (VEC_index (gimple, phis, i));
4792 if (!single_defuse_cycle || j == 0)
4793 reduc_def = PHI_RESULT (new_phi);
4796 def1 = ((op_type == ternary_op)
4797 ? VEC_index (tree, vec_oprnds1, i) : NULL);
4798 if (op_type == binary_op)
4800 if (reduc_index == 0)
4801 expr = build2 (code, vectype_out, reduc_def, def0);
4803 expr = build2 (code, vectype_out, def0, reduc_def);
4807 if (reduc_index == 0)
4808 expr = build3 (code, vectype_out, reduc_def, def0, def1);
4811 if (reduc_index == 1)
4812 expr = build3 (code, vectype_out, def0, reduc_def, def1);
4814 expr = build3 (code, vectype_out, def0, def1, reduc_def);
4818 new_stmt = gimple_build_assign (vec_dest, expr);
4819 new_temp = make_ssa_name (vec_dest, new_stmt);
4820 gimple_assign_set_lhs (new_stmt, new_temp);
4821 vect_finish_stmt_generation (stmt, new_stmt, gsi);
4825 VEC_quick_push (gimple, SLP_TREE_VEC_STMTS (slp_node), new_stmt);
4826 VEC_quick_push (tree, vect_defs, new_temp);
4829 VEC_replace (tree, vect_defs, 0, new_temp);
4836 STMT_VINFO_VEC_STMT (stmt_info) = *vec_stmt = new_stmt;
4838 STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;
4840 prev_stmt_info = vinfo_for_stmt (new_stmt);
4841 prev_phi_info = vinfo_for_stmt (new_phi);
4844 /* Finalize the reduction-phi (set its arguments) and create the
4845 epilog reduction code. */
4846 if ((!single_defuse_cycle || code == COND_EXPR) && !slp_node)
4848 new_temp = gimple_assign_lhs (*vec_stmt);
4849 VEC_replace (tree, vect_defs, 0, new_temp);
4852 vect_create_epilog_for_reduction (vect_defs, stmt, epilog_copies,
4853 epilog_reduc_code, phis, reduc_index,
4854 double_reduc, slp_node);
4856 VEC_free (gimple, heap, phis);
4857 VEC_free (tree, heap, vec_oprnds0);
4859 VEC_free (tree, heap, vec_oprnds1);
4864 /* Function vect_min_worthwhile_factor.
4866 For a loop where we could vectorize the operation indicated by CODE,
4867 return the minimum vectorization factor that makes it worthwhile
4868 to use generic vectors. */
4870 vect_min_worthwhile_factor (enum tree_code code)
4891 /* Function vectorizable_induction
4893 Check if PHI performs an induction computation that can be vectorized.
4894 If VEC_STMT is also passed, vectorize the induction PHI: create a vectorized
4895 phi to replace it, put it in VEC_STMT, and add it to the same basic block.
4896 Return FALSE if not a vectorizable STMT, TRUE otherwise. */
4899 vectorizable_induction (gimple phi, gimple_stmt_iterator *gsi ATTRIBUTE_UNUSED,
4902 stmt_vec_info stmt_info = vinfo_for_stmt (phi);
4903 tree vectype = STMT_VINFO_VECTYPE (stmt_info);
4904 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
4905 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
4906 int nunits = TYPE_VECTOR_SUBPARTS (vectype);
4907 int ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits;
4910 gcc_assert (ncopies >= 1);
4911 /* FORNOW. This restriction should be relaxed. */
4912 if (nested_in_vect_loop_p (loop, phi) && ncopies > 1)
4914 if (vect_print_dump_info (REPORT_DETAILS))
4915 fprintf (vect_dump, "multiple types in nested loop.");
4919 if (!STMT_VINFO_RELEVANT_P (stmt_info))
4922 /* FORNOW: SLP not supported. */
4923 if (STMT_SLP_TYPE (stmt_info))
4926 gcc_assert (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def);
4928 if (gimple_code (phi) != GIMPLE_PHI)
4931 if (!vec_stmt) /* transformation not required. */
4933 STMT_VINFO_TYPE (stmt_info) = induc_vec_info_type;
4934 if (vect_print_dump_info (REPORT_DETAILS))
4935 fprintf (vect_dump, "=== vectorizable_induction ===");
4936 vect_model_induction_cost (stmt_info, ncopies);
4942 if (vect_print_dump_info (REPORT_DETAILS))
4943 fprintf (vect_dump, "transform induction phi.");
4945 vec_def = get_initial_def_for_induction (phi);
4946 *vec_stmt = SSA_NAME_DEF_STMT (vec_def);
4950 /* Function vectorizable_live_operation.
4952 STMT computes a value that is used outside the loop. Check if
4953 it can be supported. */
4956 vectorizable_live_operation (gimple stmt,
4957 gimple_stmt_iterator *gsi ATTRIBUTE_UNUSED,
4958 gimple *vec_stmt ATTRIBUTE_UNUSED)
4960 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
4961 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
4962 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
4968 enum vect_def_type dt;
4969 enum tree_code code;
4970 enum gimple_rhs_class rhs_class;
4972 gcc_assert (STMT_VINFO_LIVE_P (stmt_info));
4974 if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_reduction_def)
4977 if (!is_gimple_assign (stmt))
4980 if (TREE_CODE (gimple_assign_lhs (stmt)) != SSA_NAME)
4983 /* FORNOW. CHECKME. */
4984 if (nested_in_vect_loop_p (loop, stmt))
4987 code = gimple_assign_rhs_code (stmt);
4988 op_type = TREE_CODE_LENGTH (code);
4989 rhs_class = get_gimple_rhs_class (code);
4990 gcc_assert (rhs_class != GIMPLE_UNARY_RHS || op_type == unary_op);
4991 gcc_assert (rhs_class != GIMPLE_BINARY_RHS || op_type == binary_op);
4993 /* FORNOW: support only if all uses are invariant. This means
4994 that the scalar operations can remain in place, unvectorized.
4995 The original last scalar value that they compute will be used. */
4997 for (i = 0; i < op_type; i++)
4999 if (rhs_class == GIMPLE_SINGLE_RHS)
5000 op = TREE_OPERAND (gimple_op (stmt, 1), i);
5002 op = gimple_op (stmt, i + 1);
5004 && !vect_is_simple_use (op, loop_vinfo, NULL, &def_stmt, &def, &dt))
5006 if (vect_print_dump_info (REPORT_DETAILS))
5007 fprintf (vect_dump, "use not simple.");
5011 if (dt != vect_external_def && dt != vect_constant_def)
5015 /* No transformation is required for the cases we currently support. */
5019 /* Kill any debug uses outside LOOP of SSA names defined in STMT. */
5022 vect_loop_kill_debug_uses (struct loop *loop, gimple stmt)
5024 ssa_op_iter op_iter;
5025 imm_use_iterator imm_iter;
5026 def_operand_p def_p;
5029 FOR_EACH_PHI_OR_STMT_DEF (def_p, stmt, op_iter, SSA_OP_DEF)
5031 FOR_EACH_IMM_USE_STMT (ustmt, imm_iter, DEF_FROM_PTR (def_p))
5035 if (!is_gimple_debug (ustmt))
5038 bb = gimple_bb (ustmt);
5040 if (!flow_bb_inside_loop_p (loop, bb))
5042 if (gimple_debug_bind_p (ustmt))
5044 if (vect_print_dump_info (REPORT_DETAILS))
5045 fprintf (vect_dump, "killing debug use");
5047 gimple_debug_bind_reset_value (ustmt);
5048 update_stmt (ustmt);
5057 /* Function vect_transform_loop.
5059 The analysis phase has determined that the loop is vectorizable.
5060 Vectorize the loop - created vectorized stmts to replace the scalar
5061 stmts in the loop, and update the loop exit condition. */
5064 vect_transform_loop (loop_vec_info loop_vinfo)
5066 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
5067 basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
5068 int nbbs = loop->num_nodes;
5069 gimple_stmt_iterator si;
5072 int vectorization_factor = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
5074 bool slp_scheduled = false;
5075 unsigned int nunits;
5076 tree cond_expr = NULL_TREE;
5077 gimple_seq cond_expr_stmt_list = NULL;
5078 bool do_peeling_for_loop_bound;
5079 gimple stmt, pattern_stmt;
5080 bool transform_pattern_stmt = false;
5082 if (vect_print_dump_info (REPORT_DETAILS))
5083 fprintf (vect_dump, "=== vec_transform_loop ===");
5085 /* Peel the loop if there are data refs with unknown alignment.
5086 Only one data ref with unknown store is allowed. */
5088 if (LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo))
5089 vect_do_peeling_for_alignment (loop_vinfo);
5091 do_peeling_for_loop_bound
5092 = (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
5093 || (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
5094 && LOOP_VINFO_INT_NITERS (loop_vinfo) % vectorization_factor != 0)
5095 || LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo));
5097 if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)
5098 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
5099 vect_loop_versioning (loop_vinfo,
5100 !do_peeling_for_loop_bound,
5101 &cond_expr, &cond_expr_stmt_list);
5103 /* If the loop has a symbolic number of iterations 'n' (i.e. it's not a
5104 compile time constant), or it is a constant that doesn't divide by the
5105 vectorization factor, then an epilog loop needs to be created.
5106 We therefore duplicate the loop: the original loop will be vectorized,
5107 and will compute the first (n/VF) iterations. The second copy of the loop
5108 will remain scalar and will compute the remaining (n%VF) iterations.
5109 (VF is the vectorization factor). */
5111 if (do_peeling_for_loop_bound)
5112 vect_do_peeling_for_loop_bound (loop_vinfo, &ratio,
5113 cond_expr, cond_expr_stmt_list);
5115 ratio = build_int_cst (TREE_TYPE (LOOP_VINFO_NITERS (loop_vinfo)),
5116 LOOP_VINFO_INT_NITERS (loop_vinfo) / vectorization_factor);
5118 /* 1) Make sure the loop header has exactly two entries
5119 2) Make sure we have a preheader basic block. */
5121 gcc_assert (EDGE_COUNT (loop->header->preds) == 2);
5123 split_edge (loop_preheader_edge (loop));
5125 /* FORNOW: the vectorizer supports only loops which body consist
5126 of one basic block (header + empty latch). When the vectorizer will
5127 support more involved loop forms, the order by which the BBs are
5128 traversed need to be reconsidered. */
5130 for (i = 0; i < nbbs; i++)
5132 basic_block bb = bbs[i];
5133 stmt_vec_info stmt_info;
5136 for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
5138 phi = gsi_stmt (si);
5139 if (vect_print_dump_info (REPORT_DETAILS))
5141 fprintf (vect_dump, "------>vectorizing phi: ");
5142 print_gimple_stmt (vect_dump, phi, 0, TDF_SLIM);
5144 stmt_info = vinfo_for_stmt (phi);
5148 if (MAY_HAVE_DEBUG_STMTS && !STMT_VINFO_LIVE_P (stmt_info))
5149 vect_loop_kill_debug_uses (loop, phi);
5151 if (!STMT_VINFO_RELEVANT_P (stmt_info)
5152 && !STMT_VINFO_LIVE_P (stmt_info))
5155 if ((TYPE_VECTOR_SUBPARTS (STMT_VINFO_VECTYPE (stmt_info))
5156 != (unsigned HOST_WIDE_INT) vectorization_factor)
5157 && vect_print_dump_info (REPORT_DETAILS))
5158 fprintf (vect_dump, "multiple-types.");
5160 if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def)
5162 if (vect_print_dump_info (REPORT_DETAILS))
5163 fprintf (vect_dump, "transform phi.");
5164 vect_transform_stmt (phi, NULL, NULL, NULL, NULL);
5168 pattern_stmt = NULL;
5169 for (si = gsi_start_bb (bb); !gsi_end_p (si) || transform_pattern_stmt;)
5173 if (transform_pattern_stmt)
5175 stmt = pattern_stmt;
5176 transform_pattern_stmt = false;
5179 stmt = gsi_stmt (si);
5181 if (vect_print_dump_info (REPORT_DETAILS))
5183 fprintf (vect_dump, "------>vectorizing statement: ");
5184 print_gimple_stmt (vect_dump, stmt, 0, TDF_SLIM);
5187 stmt_info = vinfo_for_stmt (stmt);
5189 /* vector stmts created in the outer-loop during vectorization of
5190 stmts in an inner-loop may not have a stmt_info, and do not
5191 need to be vectorized. */
5198 if (MAY_HAVE_DEBUG_STMTS && !STMT_VINFO_LIVE_P (stmt_info))
5199 vect_loop_kill_debug_uses (loop, stmt);
5201 if (!STMT_VINFO_RELEVANT_P (stmt_info)
5202 && !STMT_VINFO_LIVE_P (stmt_info))
5204 if (STMT_VINFO_IN_PATTERN_P (stmt_info)
5205 && (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info))
5206 && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt))
5207 || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt))))
5209 stmt = pattern_stmt;
5210 stmt_info = vinfo_for_stmt (stmt);
5218 else if (STMT_VINFO_IN_PATTERN_P (stmt_info)
5219 && (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info))
5220 && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt))
5221 || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt))))
5222 transform_pattern_stmt = true;
5224 gcc_assert (STMT_VINFO_VECTYPE (stmt_info));
5225 nunits = (unsigned int) TYPE_VECTOR_SUBPARTS (
5226 STMT_VINFO_VECTYPE (stmt_info));
5227 if (!STMT_SLP_TYPE (stmt_info)
5228 && nunits != (unsigned int) vectorization_factor
5229 && vect_print_dump_info (REPORT_DETAILS))
5230 /* For SLP VF is set according to unrolling factor, and not to
5231 vector size, hence for SLP this print is not valid. */
5232 fprintf (vect_dump, "multiple-types.");
5234 /* SLP. Schedule all the SLP instances when the first SLP stmt is
5236 if (STMT_SLP_TYPE (stmt_info))
5240 slp_scheduled = true;
5242 if (vect_print_dump_info (REPORT_DETAILS))
5243 fprintf (vect_dump, "=== scheduling SLP instances ===");
5245 vect_schedule_slp (loop_vinfo, NULL);
5248 /* Hybrid SLP stmts must be vectorized in addition to SLP. */
5249 if (!vinfo_for_stmt (stmt) || PURE_SLP_STMT (stmt_info))
5251 if (!transform_pattern_stmt)
5257 /* -------- vectorize statement ------------ */
5258 if (vect_print_dump_info (REPORT_DETAILS))
5259 fprintf (vect_dump, "transform statement.");
5261 strided_store = false;
5262 is_store = vect_transform_stmt (stmt, &si, &strided_store, NULL, NULL);
5265 if (STMT_VINFO_STRIDED_ACCESS (stmt_info))
5267 /* Interleaving. If IS_STORE is TRUE, the vectorization of the
5268 interleaving chain was completed - free all the stores in
5270 vect_remove_stores (GROUP_FIRST_ELEMENT (stmt_info));
5271 gsi_remove (&si, true);
5276 /* Free the attached stmt_vec_info and remove the stmt. */
5277 free_stmt_vec_info (stmt);
5278 gsi_remove (&si, true);
5283 if (!transform_pattern_stmt)
5288 slpeel_make_loop_iterate_ntimes (loop, ratio);
5290 /* The memory tags and pointers in vectorized statements need to
5291 have their SSA forms updated. FIXME, why can't this be delayed
5292 until all the loops have been transformed? */
5293 update_ssa (TODO_update_ssa);
5295 if (vect_print_dump_info (REPORT_VECTORIZED_LOCATIONS))
5296 fprintf (vect_dump, "LOOP VECTORIZED.");
5297 if (loop->inner && vect_print_dump_info (REPORT_VECTORIZED_LOCATIONS))
5298 fprintf (vect_dump, "OUTER LOOP VECTORIZED.");