2 Copyright (C) 2003-2013 Free Software Foundation, Inc.
3 Contributed by Dorit Naishlos <dorit@il.ibm.com> and
4 Ira Rosen <irar@il.ibm.com>
6 This file is part of GCC.
8 GCC is free software; you can redistribute it and/or modify it under
9 the terms of the GNU General Public License as published by the Free
10 Software Foundation; either version 3, or (at your option) any later
13 GCC is distributed in the hope that it will be useful, but WITHOUT ANY
14 WARRANTY; without even the implied warranty of MERCHANTABILITY or
15 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
18 You should have received a copy of the GNU General Public License
19 along with GCC; see the file COPYING3. If not see
20 <http://www.gnu.org/licenses/>. */
24 #include "coretypes.h"
29 #include "basic-block.h"
30 #include "gimple-pretty-print.h"
32 #include "gimple-ssa.h"
33 #include "tree-phinodes.h"
34 #include "ssa-iterators.h"
35 #include "tree-ssanames.h"
36 #include "tree-ssa-loop-ivopts.h"
37 #include "tree-ssa-loop-manip.h"
38 #include "tree-ssa-loop-niter.h"
39 #include "tree-pass.h"
45 #include "diagnostic-core.h"
46 #include "tree-chrec.h"
47 #include "tree-scalar-evolution.h"
48 #include "tree-vectorizer.h"
51 /* Loop Vectorization Pass.
53 This pass tries to vectorize loops.
55 For example, the vectorizer transforms the following simple loop:
57 short a[N]; short b[N]; short c[N]; int i;
63 as if it was manually vectorized by rewriting the source code into:
65 typedef int __attribute__((mode(V8HI))) v8hi;
66 short a[N]; short b[N]; short c[N]; int i;
67 v8hi *pa = (v8hi*)a, *pb = (v8hi*)b, *pc = (v8hi*)c;
70 for (i=0; i<N/8; i++){
77 The main entry to this pass is vectorize_loops(), in which
78 the vectorizer applies a set of analyses on a given set of loops,
79 followed by the actual vectorization transformation for the loops that
80 had successfully passed the analysis phase.
81 Throughout this pass we make a distinction between two types of
82 data: scalars (which are represented by SSA_NAMES), and memory references
83 ("data-refs"). These two types of data require different handling both
84 during analysis and transformation. The types of data-refs that the
85 vectorizer currently supports are ARRAY_REFS which base is an array DECL
86 (not a pointer), and INDIRECT_REFS through pointers; both array and pointer
87 accesses are required to have a simple (consecutive) access pattern.
91 The driver for the analysis phase is vect_analyze_loop().
92 It applies a set of analyses, some of which rely on the scalar evolution
93 analyzer (scev) developed by Sebastian Pop.
95 During the analysis phase the vectorizer records some information
96 per stmt in a "stmt_vec_info" struct which is attached to each stmt in the
97 loop, as well as general information about the loop as a whole, which is
98 recorded in a "loop_vec_info" struct attached to each loop.
100 Transformation phase:
101 =====================
102 The loop transformation phase scans all the stmts in the loop, and
103 creates a vector stmt (or a sequence of stmts) for each scalar stmt S in
104 the loop that needs to be vectorized. It inserts the vector code sequence
105 just before the scalar stmt S, and records a pointer to the vector code
106 in STMT_VINFO_VEC_STMT (stmt_info) (stmt_info is the stmt_vec_info struct
107 attached to S). This pointer will be used for the vectorization of following
108 stmts which use the def of stmt S. Stmt S is removed if it writes to memory;
109 otherwise, we rely on dead code elimination for removing it.
111 For example, say stmt S1 was vectorized into stmt VS1:
114 S1: b = x[i]; STMT_VINFO_VEC_STMT (stmt_info (S1)) = VS1
117 To vectorize stmt S2, the vectorizer first finds the stmt that defines
118 the operand 'b' (S1), and gets the relevant vector def 'vb' from the
119 vector stmt VS1 pointed to by STMT_VINFO_VEC_STMT (stmt_info (S1)). The
120 resulting sequence would be:
123 S1: b = x[i]; STMT_VINFO_VEC_STMT (stmt_info (S1)) = VS1
125 S2: a = b; STMT_VINFO_VEC_STMT (stmt_info (S2)) = VS2
127 Operands that are not SSA_NAMEs, are data-refs that appear in
128 load/store operations (like 'x[i]' in S1), and are handled differently.
132 Currently the only target specific information that is used is the
133 size of the vector (in bytes) - "TARGET_VECTORIZE_UNITS_PER_SIMD_WORD".
134 Targets that can support different sizes of vectors, for now will need
135 to specify one value for "TARGET_VECTORIZE_UNITS_PER_SIMD_WORD". More
136 flexibility will be added in the future.
138 Since we only vectorize operations which vector form can be
139 expressed using existing tree codes, to verify that an operation is
140 supported, the vectorizer checks the relevant optab at the relevant
141 machine_mode (e.g, optab_handler (add_optab, V8HImode)). If
142 the value found is CODE_FOR_nothing, then there's no target support, and
143 we can't vectorize the stmt.
145 For additional information on this project see:
146 http://gcc.gnu.org/projects/tree-ssa/vectorization.html
149 static void vect_estimate_min_profitable_iters (loop_vec_info, int *, int *);
151 /* Function vect_determine_vectorization_factor
153 Determine the vectorization factor (VF). VF is the number of data elements
154 that are operated upon in parallel in a single iteration of the vectorized
155 loop. For example, when vectorizing a loop that operates on 4byte elements,
156 on a target with vector size (VS) 16byte, the VF is set to 4, since 4
157 elements can fit in a single vector register.
159 We currently support vectorization of loops in which all types operated upon
160 are of the same size. Therefore this function currently sets VF according to
161 the size of the types operated upon, and fails if there are multiple sizes
164 VF is also the factor by which the loop iterations are strip-mined, e.g.:
171 for (i=0; i<N; i+=VF){
172 a[i:VF] = b[i:VF] + c[i:VF];
177 vect_determine_vectorization_factor (loop_vec_info loop_vinfo)
179 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
180 basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
181 int nbbs = loop->num_nodes;
182 gimple_stmt_iterator si;
183 unsigned int vectorization_factor = 0;
188 stmt_vec_info stmt_info;
191 gimple stmt, pattern_stmt = NULL;
192 gimple_seq pattern_def_seq = NULL;
193 gimple_stmt_iterator pattern_def_si = gsi_none ();
194 bool analyze_pattern_stmt = false;
196 if (dump_enabled_p ())
197 dump_printf_loc (MSG_NOTE, vect_location,
198 "=== vect_determine_vectorization_factor ===\n");
200 for (i = 0; i < nbbs; i++)
202 basic_block bb = bbs[i];
204 for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
207 stmt_info = vinfo_for_stmt (phi);
208 if (dump_enabled_p ())
210 dump_printf_loc (MSG_NOTE, vect_location, "==> examining phi: ");
211 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0);
212 dump_printf (MSG_NOTE, "\n");
215 gcc_assert (stmt_info);
217 if (STMT_VINFO_RELEVANT_P (stmt_info))
219 gcc_assert (!STMT_VINFO_VECTYPE (stmt_info));
220 scalar_type = TREE_TYPE (PHI_RESULT (phi));
222 if (dump_enabled_p ())
224 dump_printf_loc (MSG_NOTE, vect_location,
225 "get vectype for scalar type: ");
226 dump_generic_expr (MSG_NOTE, TDF_SLIM, scalar_type);
227 dump_printf (MSG_NOTE, "\n");
230 vectype = get_vectype_for_scalar_type (scalar_type);
233 if (dump_enabled_p ())
235 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
236 "not vectorized: unsupported "
238 dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM,
240 dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
244 STMT_VINFO_VECTYPE (stmt_info) = vectype;
246 if (dump_enabled_p ())
248 dump_printf_loc (MSG_NOTE, vect_location, "vectype: ");
249 dump_generic_expr (MSG_NOTE, TDF_SLIM, vectype);
250 dump_printf (MSG_NOTE, "\n");
253 nunits = TYPE_VECTOR_SUBPARTS (vectype);
254 if (dump_enabled_p ())
255 dump_printf_loc (MSG_NOTE, vect_location, "nunits = %d\n",
258 if (!vectorization_factor
259 || (nunits > vectorization_factor))
260 vectorization_factor = nunits;
264 for (si = gsi_start_bb (bb); !gsi_end_p (si) || analyze_pattern_stmt;)
268 if (analyze_pattern_stmt)
271 stmt = gsi_stmt (si);
273 stmt_info = vinfo_for_stmt (stmt);
275 if (dump_enabled_p ())
277 dump_printf_loc (MSG_NOTE, vect_location,
278 "==> examining statement: ");
279 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, stmt, 0);
280 dump_printf (MSG_NOTE, "\n");
283 gcc_assert (stmt_info);
285 /* Skip stmts which do not need to be vectorized. */
286 if ((!STMT_VINFO_RELEVANT_P (stmt_info)
287 && !STMT_VINFO_LIVE_P (stmt_info))
288 || gimple_clobber_p (stmt))
290 if (STMT_VINFO_IN_PATTERN_P (stmt_info)
291 && (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info))
292 && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt))
293 || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt))))
296 stmt_info = vinfo_for_stmt (pattern_stmt);
297 if (dump_enabled_p ())
299 dump_printf_loc (MSG_NOTE, vect_location,
300 "==> examining pattern statement: ");
301 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, stmt, 0);
302 dump_printf (MSG_NOTE, "\n");
307 if (dump_enabled_p ())
308 dump_printf_loc (MSG_NOTE, vect_location, "skip.\n");
313 else if (STMT_VINFO_IN_PATTERN_P (stmt_info)
314 && (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info))
315 && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt))
316 || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt))))
317 analyze_pattern_stmt = true;
319 /* If a pattern statement has def stmts, analyze them too. */
320 if (is_pattern_stmt_p (stmt_info))
322 if (pattern_def_seq == NULL)
324 pattern_def_seq = STMT_VINFO_PATTERN_DEF_SEQ (stmt_info);
325 pattern_def_si = gsi_start (pattern_def_seq);
327 else if (!gsi_end_p (pattern_def_si))
328 gsi_next (&pattern_def_si);
329 if (pattern_def_seq != NULL)
331 gimple pattern_def_stmt = NULL;
332 stmt_vec_info pattern_def_stmt_info = NULL;
334 while (!gsi_end_p (pattern_def_si))
336 pattern_def_stmt = gsi_stmt (pattern_def_si);
337 pattern_def_stmt_info
338 = vinfo_for_stmt (pattern_def_stmt);
339 if (STMT_VINFO_RELEVANT_P (pattern_def_stmt_info)
340 || STMT_VINFO_LIVE_P (pattern_def_stmt_info))
342 gsi_next (&pattern_def_si);
345 if (!gsi_end_p (pattern_def_si))
347 if (dump_enabled_p ())
349 dump_printf_loc (MSG_NOTE, vect_location,
350 "==> examining pattern def stmt: ");
351 dump_gimple_stmt (MSG_NOTE, TDF_SLIM,
352 pattern_def_stmt, 0);
353 dump_printf (MSG_NOTE, "\n");
356 stmt = pattern_def_stmt;
357 stmt_info = pattern_def_stmt_info;
361 pattern_def_si = gsi_none ();
362 analyze_pattern_stmt = false;
366 analyze_pattern_stmt = false;
369 if (gimple_get_lhs (stmt) == NULL_TREE)
371 if (dump_enabled_p ())
373 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
374 "not vectorized: irregular stmt.");
375 dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt,
377 dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
382 if (VECTOR_MODE_P (TYPE_MODE (gimple_expr_type (stmt))))
384 if (dump_enabled_p ())
386 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
387 "not vectorized: vector stmt in loop:");
388 dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, stmt, 0);
389 dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
394 if (STMT_VINFO_VECTYPE (stmt_info))
396 /* The only case when a vectype had been already set is for stmts
397 that contain a dataref, or for "pattern-stmts" (stmts
398 generated by the vectorizer to represent/replace a certain
400 gcc_assert (STMT_VINFO_DATA_REF (stmt_info)
401 || is_pattern_stmt_p (stmt_info)
402 || !gsi_end_p (pattern_def_si));
403 vectype = STMT_VINFO_VECTYPE (stmt_info);
407 gcc_assert (!STMT_VINFO_DATA_REF (stmt_info));
408 scalar_type = TREE_TYPE (gimple_get_lhs (stmt));
409 if (dump_enabled_p ())
411 dump_printf_loc (MSG_NOTE, vect_location,
412 "get vectype for scalar type: ");
413 dump_generic_expr (MSG_NOTE, TDF_SLIM, scalar_type);
414 dump_printf (MSG_NOTE, "\n");
416 vectype = get_vectype_for_scalar_type (scalar_type);
419 if (dump_enabled_p ())
421 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
422 "not vectorized: unsupported "
424 dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM,
426 dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
431 STMT_VINFO_VECTYPE (stmt_info) = vectype;
433 if (dump_enabled_p ())
435 dump_printf_loc (MSG_NOTE, vect_location, "vectype: ");
436 dump_generic_expr (MSG_NOTE, TDF_SLIM, vectype);
437 dump_printf (MSG_NOTE, "\n");
441 /* The vectorization factor is according to the smallest
442 scalar type (or the largest vector size, but we only
443 support one vector size per loop). */
444 scalar_type = vect_get_smallest_scalar_type (stmt, &dummy,
446 if (dump_enabled_p ())
448 dump_printf_loc (MSG_NOTE, vect_location,
449 "get vectype for scalar type: ");
450 dump_generic_expr (MSG_NOTE, TDF_SLIM, scalar_type);
451 dump_printf (MSG_NOTE, "\n");
453 vf_vectype = get_vectype_for_scalar_type (scalar_type);
456 if (dump_enabled_p ())
458 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
459 "not vectorized: unsupported data-type ");
460 dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM,
462 dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
467 if ((GET_MODE_SIZE (TYPE_MODE (vectype))
468 != GET_MODE_SIZE (TYPE_MODE (vf_vectype))))
470 if (dump_enabled_p ())
472 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
473 "not vectorized: different sized vector "
474 "types in statement, ");
475 dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM,
477 dump_printf (MSG_MISSED_OPTIMIZATION, " and ");
478 dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM,
480 dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
485 if (dump_enabled_p ())
487 dump_printf_loc (MSG_NOTE, vect_location, "vectype: ");
488 dump_generic_expr (MSG_NOTE, TDF_SLIM, vf_vectype);
489 dump_printf (MSG_NOTE, "\n");
492 nunits = TYPE_VECTOR_SUBPARTS (vf_vectype);
493 if (dump_enabled_p ())
494 dump_printf_loc (MSG_NOTE, vect_location, "nunits = %d\n", nunits);
495 if (!vectorization_factor
496 || (nunits > vectorization_factor))
497 vectorization_factor = nunits;
499 if (!analyze_pattern_stmt && gsi_end_p (pattern_def_si))
501 pattern_def_seq = NULL;
507 /* TODO: Analyze cost. Decide if worth while to vectorize. */
508 if (dump_enabled_p ())
509 dump_printf_loc (MSG_NOTE, vect_location, "vectorization factor = %d\n",
510 vectorization_factor);
511 if (vectorization_factor <= 1)
513 if (dump_enabled_p ())
514 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
515 "not vectorized: unsupported data-type\n");
518 LOOP_VINFO_VECT_FACTOR (loop_vinfo) = vectorization_factor;
524 /* Function vect_is_simple_iv_evolution.
526 FORNOW: A simple evolution of an induction variables in the loop is
527 considered a polynomial evolution. */
530 vect_is_simple_iv_evolution (unsigned loop_nb, tree access_fn, tree * init,
535 tree evolution_part = evolution_part_in_loop_num (access_fn, loop_nb);
538 /* When there is no evolution in this loop, the evolution function
540 if (evolution_part == NULL_TREE)
543 /* When the evolution is a polynomial of degree >= 2
544 the evolution function is not "simple". */
545 if (tree_is_chrec (evolution_part))
548 step_expr = evolution_part;
549 init_expr = unshare_expr (initial_condition_in_loop_num (access_fn, loop_nb));
551 if (dump_enabled_p ())
553 dump_printf_loc (MSG_NOTE, vect_location, "step: ");
554 dump_generic_expr (MSG_NOTE, TDF_SLIM, step_expr);
555 dump_printf (MSG_NOTE, ", init: ");
556 dump_generic_expr (MSG_NOTE, TDF_SLIM, init_expr);
557 dump_printf (MSG_NOTE, "\n");
563 if (TREE_CODE (step_expr) != INTEGER_CST
564 && (TREE_CODE (step_expr) != SSA_NAME
565 || ((bb = gimple_bb (SSA_NAME_DEF_STMT (step_expr)))
566 && flow_bb_inside_loop_p (get_loop (cfun, loop_nb), bb))
567 || (!INTEGRAL_TYPE_P (TREE_TYPE (step_expr))
568 && (!SCALAR_FLOAT_TYPE_P (TREE_TYPE (step_expr))
569 || !flag_associative_math)))
570 && (TREE_CODE (step_expr) != REAL_CST
571 || !flag_associative_math))
573 if (dump_enabled_p ())
574 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
582 /* Function vect_analyze_scalar_cycles_1.
584 Examine the cross iteration def-use cycles of scalar variables
585 in LOOP. LOOP_VINFO represents the loop that is now being
586 considered for vectorization (can be LOOP, or an outer-loop
590 vect_analyze_scalar_cycles_1 (loop_vec_info loop_vinfo, struct loop *loop)
592 basic_block bb = loop->header;
594 stack_vec<gimple, 64> worklist;
595 gimple_stmt_iterator gsi;
598 if (dump_enabled_p ())
599 dump_printf_loc (MSG_NOTE, vect_location,
600 "=== vect_analyze_scalar_cycles ===\n");
602 /* First - identify all inductions. Reduction detection assumes that all the
603 inductions have been identified, therefore, this order must not be
605 for (gsi = gsi_start_phis (bb); !gsi_end_p (gsi); gsi_next (&gsi))
607 gimple phi = gsi_stmt (gsi);
608 tree access_fn = NULL;
609 tree def = PHI_RESULT (phi);
610 stmt_vec_info stmt_vinfo = vinfo_for_stmt (phi);
612 if (dump_enabled_p ())
614 dump_printf_loc (MSG_NOTE, vect_location, "Analyze phi: ");
615 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0);
616 dump_printf (MSG_NOTE, "\n");
619 /* Skip virtual phi's. The data dependences that are associated with
620 virtual defs/uses (i.e., memory accesses) are analyzed elsewhere. */
621 if (virtual_operand_p (def))
624 STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_unknown_def_type;
626 /* Analyze the evolution function. */
627 access_fn = analyze_scalar_evolution (loop, def);
630 STRIP_NOPS (access_fn);
631 if (dump_enabled_p ())
633 dump_printf_loc (MSG_NOTE, vect_location,
634 "Access function of PHI: ");
635 dump_generic_expr (MSG_NOTE, TDF_SLIM, access_fn);
636 dump_printf (MSG_NOTE, "\n");
638 STMT_VINFO_LOOP_PHI_EVOLUTION_PART (stmt_vinfo)
639 = evolution_part_in_loop_num (access_fn, loop->num);
643 || !vect_is_simple_iv_evolution (loop->num, access_fn, &init, &step)
644 || (LOOP_VINFO_LOOP (loop_vinfo) != loop
645 && TREE_CODE (step) != INTEGER_CST))
647 worklist.safe_push (phi);
651 gcc_assert (STMT_VINFO_LOOP_PHI_EVOLUTION_PART (stmt_vinfo) != NULL_TREE);
653 if (dump_enabled_p ())
654 dump_printf_loc (MSG_NOTE, vect_location, "Detected induction.\n");
655 STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_induction_def;
659 /* Second - identify all reductions and nested cycles. */
660 while (worklist.length () > 0)
662 gimple phi = worklist.pop ();
663 tree def = PHI_RESULT (phi);
664 stmt_vec_info stmt_vinfo = vinfo_for_stmt (phi);
668 if (dump_enabled_p ())
670 dump_printf_loc (MSG_NOTE, vect_location, "Analyze phi: ");
671 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0);
672 dump_printf (MSG_NOTE, "\n");
675 gcc_assert (!virtual_operand_p (def)
676 && STMT_VINFO_DEF_TYPE (stmt_vinfo) == vect_unknown_def_type);
678 nested_cycle = (loop != LOOP_VINFO_LOOP (loop_vinfo));
679 reduc_stmt = vect_force_simple_reduction (loop_vinfo, phi, !nested_cycle,
685 if (dump_enabled_p ())
686 dump_printf_loc (MSG_NOTE, vect_location,
687 "Detected double reduction.\n");
689 STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_double_reduction_def;
690 STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) =
691 vect_double_reduction_def;
697 if (dump_enabled_p ())
698 dump_printf_loc (MSG_NOTE, vect_location,
699 "Detected vectorizable nested cycle.\n");
701 STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_nested_cycle;
702 STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) =
707 if (dump_enabled_p ())
708 dump_printf_loc (MSG_NOTE, vect_location,
709 "Detected reduction.\n");
711 STMT_VINFO_DEF_TYPE (stmt_vinfo) = vect_reduction_def;
712 STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt)) =
714 /* Store the reduction cycles for possible vectorization in
716 LOOP_VINFO_REDUCTIONS (loop_vinfo).safe_push (reduc_stmt);
721 if (dump_enabled_p ())
722 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
723 "Unknown def-use cycle pattern.\n");
728 /* Function vect_analyze_scalar_cycles.
730 Examine the cross iteration def-use cycles of scalar variables, by
731 analyzing the loop-header PHIs of scalar variables. Classify each
732 cycle as one of the following: invariant, induction, reduction, unknown.
733 We do that for the loop represented by LOOP_VINFO, and also to its
734 inner-loop, if exists.
735 Examples for scalar cycles:
750 vect_analyze_scalar_cycles (loop_vec_info loop_vinfo)
752 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
754 vect_analyze_scalar_cycles_1 (loop_vinfo, loop);
756 /* When vectorizing an outer-loop, the inner-loop is executed sequentially.
757 Reductions in such inner-loop therefore have different properties than
758 the reductions in the nest that gets vectorized:
759 1. When vectorized, they are executed in the same order as in the original
760 scalar loop, so we can't change the order of computation when
762 2. FIXME: Inner-loop reductions can be used in the inner-loop, so the
763 current checks are too strict. */
766 vect_analyze_scalar_cycles_1 (loop_vinfo, loop->inner);
769 /* Function vect_get_loop_niters.
771 Determine how many iterations the loop is executed.
772 If an expression that represents the number of iterations
773 can be constructed, place it in NUMBER_OF_ITERATIONS.
774 Return the loop exit condition. */
777 vect_get_loop_niters (struct loop *loop, tree *number_of_iterations)
781 if (dump_enabled_p ())
782 dump_printf_loc (MSG_NOTE, vect_location,
783 "=== get_loop_niters ===\n");
784 niters = number_of_exit_cond_executions (loop);
786 if (niters != NULL_TREE
787 && niters != chrec_dont_know)
789 *number_of_iterations = niters;
791 if (dump_enabled_p ())
793 dump_printf_loc (MSG_NOTE, vect_location, "==> get_loop_niters:");
794 dump_generic_expr (MSG_NOTE, TDF_SLIM, *number_of_iterations);
795 dump_printf (MSG_NOTE, "\n");
799 return get_loop_exit_condition (loop);
803 /* Function bb_in_loop_p
805 Used as predicate for dfs order traversal of the loop bbs. */
808 bb_in_loop_p (const_basic_block bb, const void *data)
810 const struct loop *const loop = (const struct loop *)data;
811 if (flow_bb_inside_loop_p (loop, bb))
817 /* Function new_loop_vec_info.
819 Create and initialize a new loop_vec_info struct for LOOP, as well as
820 stmt_vec_info structs for all the stmts in LOOP. */
823 new_loop_vec_info (struct loop *loop)
827 gimple_stmt_iterator si;
828 unsigned int i, nbbs;
830 res = (loop_vec_info) xcalloc (1, sizeof (struct _loop_vec_info));
831 LOOP_VINFO_LOOP (res) = loop;
833 bbs = get_loop_body (loop);
835 /* Create/Update stmt_info for all stmts in the loop. */
836 for (i = 0; i < loop->num_nodes; i++)
838 basic_block bb = bbs[i];
840 /* BBs in a nested inner-loop will have been already processed (because
841 we will have called vect_analyze_loop_form for any nested inner-loop).
842 Therefore, for stmts in an inner-loop we just want to update the
843 STMT_VINFO_LOOP_VINFO field of their stmt_info to point to the new
844 loop_info of the outer-loop we are currently considering to vectorize
845 (instead of the loop_info of the inner-loop).
846 For stmts in other BBs we need to create a stmt_info from scratch. */
847 if (bb->loop_father != loop)
850 gcc_assert (loop->inner && bb->loop_father == loop->inner);
851 for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
853 gimple phi = gsi_stmt (si);
854 stmt_vec_info stmt_info = vinfo_for_stmt (phi);
855 loop_vec_info inner_loop_vinfo =
856 STMT_VINFO_LOOP_VINFO (stmt_info);
857 gcc_assert (loop->inner == LOOP_VINFO_LOOP (inner_loop_vinfo));
858 STMT_VINFO_LOOP_VINFO (stmt_info) = res;
860 for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
862 gimple stmt = gsi_stmt (si);
863 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
864 loop_vec_info inner_loop_vinfo =
865 STMT_VINFO_LOOP_VINFO (stmt_info);
866 gcc_assert (loop->inner == LOOP_VINFO_LOOP (inner_loop_vinfo));
867 STMT_VINFO_LOOP_VINFO (stmt_info) = res;
872 /* bb in current nest. */
873 for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
875 gimple phi = gsi_stmt (si);
876 gimple_set_uid (phi, 0);
877 set_vinfo_for_stmt (phi, new_stmt_vec_info (phi, res, NULL));
880 for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
882 gimple stmt = gsi_stmt (si);
883 gimple_set_uid (stmt, 0);
884 set_vinfo_for_stmt (stmt, new_stmt_vec_info (stmt, res, NULL));
889 /* CHECKME: We want to visit all BBs before their successors (except for
890 latch blocks, for which this assertion wouldn't hold). In the simple
891 case of the loop forms we allow, a dfs order of the BBs would the same
892 as reversed postorder traversal, so we are safe. */
895 bbs = XCNEWVEC (basic_block, loop->num_nodes);
896 nbbs = dfs_enumerate_from (loop->header, 0, bb_in_loop_p,
897 bbs, loop->num_nodes, loop);
898 gcc_assert (nbbs == loop->num_nodes);
900 LOOP_VINFO_BBS (res) = bbs;
901 LOOP_VINFO_NITERS (res) = NULL;
902 LOOP_VINFO_NITERS_UNCHANGED (res) = NULL;
903 LOOP_VINFO_COST_MODEL_MIN_ITERS (res) = 0;
904 LOOP_VINFO_VECTORIZABLE_P (res) = 0;
905 LOOP_PEELING_FOR_ALIGNMENT (res) = 0;
906 LOOP_VINFO_VECT_FACTOR (res) = 0;
907 LOOP_VINFO_LOOP_NEST (res).create (3);
908 LOOP_VINFO_DATAREFS (res).create (10);
909 LOOP_VINFO_DDRS (res).create (10 * 10);
910 LOOP_VINFO_UNALIGNED_DR (res) = NULL;
911 LOOP_VINFO_MAY_MISALIGN_STMTS (res).create (
912 PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIGNMENT_CHECKS));
913 LOOP_VINFO_MAY_ALIAS_DDRS (res).create (
914 PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIAS_CHECKS));
915 LOOP_VINFO_GROUPED_STORES (res).create (10);
916 LOOP_VINFO_REDUCTIONS (res).create (10);
917 LOOP_VINFO_REDUCTION_CHAINS (res).create (10);
918 LOOP_VINFO_SLP_INSTANCES (res).create (10);
919 LOOP_VINFO_SLP_UNROLLING_FACTOR (res) = 1;
920 LOOP_VINFO_TARGET_COST_DATA (res) = init_cost (loop);
921 LOOP_VINFO_PEELING_FOR_GAPS (res) = false;
922 LOOP_VINFO_OPERANDS_SWAPPED (res) = false;
928 /* Function destroy_loop_vec_info.
930 Free LOOP_VINFO struct, as well as all the stmt_vec_info structs of all the
931 stmts in the loop. */
934 destroy_loop_vec_info (loop_vec_info loop_vinfo, bool clean_stmts)
939 gimple_stmt_iterator si;
941 vec<slp_instance> slp_instances;
942 slp_instance instance;
948 loop = LOOP_VINFO_LOOP (loop_vinfo);
950 bbs = LOOP_VINFO_BBS (loop_vinfo);
951 nbbs = clean_stmts ? loop->num_nodes : 0;
952 swapped = LOOP_VINFO_OPERANDS_SWAPPED (loop_vinfo);
954 for (j = 0; j < nbbs; j++)
956 basic_block bb = bbs[j];
957 for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
958 free_stmt_vec_info (gsi_stmt (si));
960 for (si = gsi_start_bb (bb); !gsi_end_p (si); )
962 gimple stmt = gsi_stmt (si);
964 /* We may have broken canonical form by moving a constant
965 into RHS1 of a commutative op. Fix such occurrences. */
966 if (swapped && is_gimple_assign (stmt))
968 enum tree_code code = gimple_assign_rhs_code (stmt);
970 if ((code == PLUS_EXPR
971 || code == POINTER_PLUS_EXPR
972 || code == MULT_EXPR)
973 && CONSTANT_CLASS_P (gimple_assign_rhs1 (stmt)))
974 swap_ssa_operands (stmt,
975 gimple_assign_rhs1_ptr (stmt),
976 gimple_assign_rhs2_ptr (stmt));
979 /* Free stmt_vec_info. */
980 free_stmt_vec_info (stmt);
985 free (LOOP_VINFO_BBS (loop_vinfo));
986 vect_destroy_datarefs (loop_vinfo, NULL);
987 free_dependence_relations (LOOP_VINFO_DDRS (loop_vinfo));
988 LOOP_VINFO_LOOP_NEST (loop_vinfo).release ();
989 LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo).release ();
990 LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo).release ();
991 slp_instances = LOOP_VINFO_SLP_INSTANCES (loop_vinfo);
992 FOR_EACH_VEC_ELT (slp_instances, j, instance)
993 vect_free_slp_instance (instance);
995 LOOP_VINFO_SLP_INSTANCES (loop_vinfo).release ();
996 LOOP_VINFO_GROUPED_STORES (loop_vinfo).release ();
997 LOOP_VINFO_REDUCTIONS (loop_vinfo).release ();
998 LOOP_VINFO_REDUCTION_CHAINS (loop_vinfo).release ();
1000 if (LOOP_VINFO_PEELING_HTAB (loop_vinfo).is_created ())
1001 LOOP_VINFO_PEELING_HTAB (loop_vinfo).dispose ();
1003 destroy_cost_data (LOOP_VINFO_TARGET_COST_DATA (loop_vinfo));
1010 /* Function vect_analyze_loop_1.
1012 Apply a set of analyses on LOOP, and create a loop_vec_info struct
1013 for it. The different analyses will record information in the
1014 loop_vec_info struct. This is a subset of the analyses applied in
1015 vect_analyze_loop, to be applied on an inner-loop nested in the loop
1016 that is now considered for (outer-loop) vectorization. */
1018 static loop_vec_info
1019 vect_analyze_loop_1 (struct loop *loop)
1021 loop_vec_info loop_vinfo;
1023 if (dump_enabled_p ())
1024 dump_printf_loc (MSG_NOTE, vect_location,
1025 "===== analyze_loop_nest_1 =====\n");
1027 /* Check the CFG characteristics of the loop (nesting, entry/exit, etc. */
1029 loop_vinfo = vect_analyze_loop_form (loop);
1032 if (dump_enabled_p ())
1033 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1034 "bad inner-loop form.\n");
1042 /* Function vect_analyze_loop_form.
1044 Verify that certain CFG restrictions hold, including:
1045 - the loop has a pre-header
1046 - the loop has a single entry and exit
1047 - the loop exit condition is simple enough, and the number of iterations
1048 can be analyzed (a countable loop). */
1051 vect_analyze_loop_form (struct loop *loop)
1053 loop_vec_info loop_vinfo;
1055 tree number_of_iterations = NULL;
1056 loop_vec_info inner_loop_vinfo = NULL;
1058 if (dump_enabled_p ())
1059 dump_printf_loc (MSG_NOTE, vect_location,
1060 "=== vect_analyze_loop_form ===\n");
1062 /* Different restrictions apply when we are considering an inner-most loop,
1063 vs. an outer (nested) loop.
1064 (FORNOW. May want to relax some of these restrictions in the future). */
1068 /* Inner-most loop. We currently require that the number of BBs is
1069 exactly 2 (the header and latch). Vectorizable inner-most loops
1080 if (loop->num_nodes != 2)
1082 if (dump_enabled_p ())
1083 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1084 "not vectorized: control flow in loop.\n");
1088 if (empty_block_p (loop->header))
1090 if (dump_enabled_p ())
1091 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1092 "not vectorized: empty loop.\n");
1098 struct loop *innerloop = loop->inner;
1101 /* Nested loop. We currently require that the loop is doubly-nested,
1102 contains a single inner loop, and the number of BBs is exactly 5.
1103 Vectorizable outer-loops look like this:
1115 The inner-loop has the properties expected of inner-most loops
1116 as described above. */
1118 if ((loop->inner)->inner || (loop->inner)->next)
1120 if (dump_enabled_p ())
1121 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1122 "not vectorized: multiple nested loops.\n");
1126 /* Analyze the inner-loop. */
1127 inner_loop_vinfo = vect_analyze_loop_1 (loop->inner);
1128 if (!inner_loop_vinfo)
1130 if (dump_enabled_p ())
1131 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1132 "not vectorized: Bad inner loop.\n");
1136 if (!expr_invariant_in_loop_p (loop,
1137 LOOP_VINFO_NITERS (inner_loop_vinfo)))
1139 if (dump_enabled_p ())
1140 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1141 "not vectorized: inner-loop count not"
1143 destroy_loop_vec_info (inner_loop_vinfo, true);
1147 if (loop->num_nodes != 5)
1149 if (dump_enabled_p ())
1150 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1151 "not vectorized: control flow in loop.\n");
1152 destroy_loop_vec_info (inner_loop_vinfo, true);
1156 gcc_assert (EDGE_COUNT (innerloop->header->preds) == 2);
1157 entryedge = EDGE_PRED (innerloop->header, 0);
1158 if (EDGE_PRED (innerloop->header, 0)->src == innerloop->latch)
1159 entryedge = EDGE_PRED (innerloop->header, 1);
1161 if (entryedge->src != loop->header
1162 || !single_exit (innerloop)
1163 || single_exit (innerloop)->dest != EDGE_PRED (loop->latch, 0)->src)
1165 if (dump_enabled_p ())
1166 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1167 "not vectorized: unsupported outerloop form.\n");
1168 destroy_loop_vec_info (inner_loop_vinfo, true);
1172 if (dump_enabled_p ())
1173 dump_printf_loc (MSG_NOTE, vect_location,
1174 "Considering outer-loop vectorization.\n");
1177 if (!single_exit (loop)
1178 || EDGE_COUNT (loop->header->preds) != 2)
1180 if (dump_enabled_p ())
1182 if (!single_exit (loop))
1183 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1184 "not vectorized: multiple exits.\n");
1185 else if (EDGE_COUNT (loop->header->preds) != 2)
1186 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1187 "not vectorized: too many incoming edges.\n");
1189 if (inner_loop_vinfo)
1190 destroy_loop_vec_info (inner_loop_vinfo, true);
1194 /* We assume that the loop exit condition is at the end of the loop. i.e,
1195 that the loop is represented as a do-while (with a proper if-guard
1196 before the loop if needed), where the loop header contains all the
1197 executable statements, and the latch is empty. */
1198 if (!empty_block_p (loop->latch)
1199 || !gimple_seq_empty_p (phi_nodes (loop->latch)))
1201 if (dump_enabled_p ())
1202 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1203 "not vectorized: latch block not empty.\n");
1204 if (inner_loop_vinfo)
1205 destroy_loop_vec_info (inner_loop_vinfo, true);
1209 /* Make sure there exists a single-predecessor exit bb: */
1210 if (!single_pred_p (single_exit (loop)->dest))
1212 edge e = single_exit (loop);
1213 if (!(e->flags & EDGE_ABNORMAL))
1215 split_loop_exit_edge (e);
1216 if (dump_enabled_p ())
1217 dump_printf (MSG_NOTE, "split exit edge.\n");
1221 if (dump_enabled_p ())
1222 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1223 "not vectorized: abnormal loop exit edge.\n");
1224 if (inner_loop_vinfo)
1225 destroy_loop_vec_info (inner_loop_vinfo, true);
1230 loop_cond = vect_get_loop_niters (loop, &number_of_iterations);
1233 if (dump_enabled_p ())
1234 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1235 "not vectorized: complicated exit condition.\n");
1236 if (inner_loop_vinfo)
1237 destroy_loop_vec_info (inner_loop_vinfo, true);
1241 if (!number_of_iterations)
1243 if (dump_enabled_p ())
1244 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1245 "not vectorized: number of iterations cannot be "
1247 if (inner_loop_vinfo)
1248 destroy_loop_vec_info (inner_loop_vinfo, true);
1252 if (chrec_contains_undetermined (number_of_iterations))
1254 if (dump_enabled_p ())
1255 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1256 "Infinite number of iterations.\n");
1257 if (inner_loop_vinfo)
1258 destroy_loop_vec_info (inner_loop_vinfo, true);
1262 if (!NITERS_KNOWN_P (number_of_iterations))
1264 if (dump_enabled_p ())
1266 dump_printf_loc (MSG_NOTE, vect_location,
1267 "Symbolic number of iterations is ");
1268 dump_generic_expr (MSG_NOTE, TDF_DETAILS, number_of_iterations);
1269 dump_printf (MSG_NOTE, "\n");
1272 else if (TREE_INT_CST_LOW (number_of_iterations) == 0)
1274 if (dump_enabled_p ())
1275 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1276 "not vectorized: number of iterations = 0.\n");
1277 if (inner_loop_vinfo)
1278 destroy_loop_vec_info (inner_loop_vinfo, true);
1282 loop_vinfo = new_loop_vec_info (loop);
1283 LOOP_VINFO_NITERS (loop_vinfo) = number_of_iterations;
1284 LOOP_VINFO_NITERS_UNCHANGED (loop_vinfo) = number_of_iterations;
1286 STMT_VINFO_TYPE (vinfo_for_stmt (loop_cond)) = loop_exit_ctrl_vec_info_type;
1288 /* CHECKME: May want to keep it around it in the future. */
1289 if (inner_loop_vinfo)
1290 destroy_loop_vec_info (inner_loop_vinfo, false);
1292 gcc_assert (!loop->aux);
1293 loop->aux = loop_vinfo;
1298 /* Function vect_analyze_loop_operations.
1300 Scan the loop stmts and make sure they are all vectorizable. */
1303 vect_analyze_loop_operations (loop_vec_info loop_vinfo, bool slp)
1305 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
1306 basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
1307 int nbbs = loop->num_nodes;
1308 gimple_stmt_iterator si;
1309 unsigned int vectorization_factor = 0;
1312 stmt_vec_info stmt_info;
1313 bool need_to_vectorize = false;
1314 int min_profitable_iters;
1315 int min_scalar_loop_bound;
1317 bool only_slp_in_loop = true, ok;
1318 HOST_WIDE_INT max_niter;
1319 HOST_WIDE_INT estimated_niter;
1320 int min_profitable_estimate;
1322 if (dump_enabled_p ())
1323 dump_printf_loc (MSG_NOTE, vect_location,
1324 "=== vect_analyze_loop_operations ===\n");
1326 gcc_assert (LOOP_VINFO_VECT_FACTOR (loop_vinfo));
1327 vectorization_factor = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
1330 /* If all the stmts in the loop can be SLPed, we perform only SLP, and
1331 vectorization factor of the loop is the unrolling factor required by
1332 the SLP instances. If that unrolling factor is 1, we say, that we
1333 perform pure SLP on loop - cross iteration parallelism is not
1335 for (i = 0; i < nbbs; i++)
1337 basic_block bb = bbs[i];
1338 for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
1340 gimple stmt = gsi_stmt (si);
1341 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
1342 gcc_assert (stmt_info);
1343 if ((STMT_VINFO_RELEVANT_P (stmt_info)
1344 || VECTORIZABLE_CYCLE_DEF (STMT_VINFO_DEF_TYPE (stmt_info)))
1345 && !PURE_SLP_STMT (stmt_info))
1346 /* STMT needs both SLP and loop-based vectorization. */
1347 only_slp_in_loop = false;
1351 if (only_slp_in_loop)
1352 vectorization_factor = LOOP_VINFO_SLP_UNROLLING_FACTOR (loop_vinfo);
1354 vectorization_factor = least_common_multiple (vectorization_factor,
1355 LOOP_VINFO_SLP_UNROLLING_FACTOR (loop_vinfo));
1357 LOOP_VINFO_VECT_FACTOR (loop_vinfo) = vectorization_factor;
1358 if (dump_enabled_p ())
1359 dump_printf_loc (MSG_NOTE, vect_location,
1360 "Updating vectorization factor to %d\n",
1361 vectorization_factor);
1364 for (i = 0; i < nbbs; i++)
1366 basic_block bb = bbs[i];
1368 for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
1370 phi = gsi_stmt (si);
1373 stmt_info = vinfo_for_stmt (phi);
1374 if (dump_enabled_p ())
1376 dump_printf_loc (MSG_NOTE, vect_location, "examining phi: ");
1377 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0);
1378 dump_printf (MSG_NOTE, "\n");
1381 /* Inner-loop loop-closed exit phi in outer-loop vectorization
1382 (i.e., a phi in the tail of the outer-loop). */
1383 if (! is_loop_header_bb_p (bb))
1385 /* FORNOW: we currently don't support the case that these phis
1386 are not used in the outerloop (unless it is double reduction,
1387 i.e., this phi is vect_reduction_def), cause this case
1388 requires to actually do something here. */
1389 if ((!STMT_VINFO_RELEVANT_P (stmt_info)
1390 || STMT_VINFO_LIVE_P (stmt_info))
1391 && STMT_VINFO_DEF_TYPE (stmt_info)
1392 != vect_double_reduction_def)
1394 if (dump_enabled_p ())
1395 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1396 "Unsupported loop-closed phi in "
1401 /* If PHI is used in the outer loop, we check that its operand
1402 is defined in the inner loop. */
1403 if (STMT_VINFO_RELEVANT_P (stmt_info))
1408 if (gimple_phi_num_args (phi) != 1)
1411 phi_op = PHI_ARG_DEF (phi, 0);
1412 if (TREE_CODE (phi_op) != SSA_NAME)
1415 op_def_stmt = SSA_NAME_DEF_STMT (phi_op);
1416 if (gimple_nop_p (op_def_stmt)
1417 || !flow_bb_inside_loop_p (loop, gimple_bb (op_def_stmt))
1418 || !vinfo_for_stmt (op_def_stmt))
1421 if (STMT_VINFO_RELEVANT (vinfo_for_stmt (op_def_stmt))
1422 != vect_used_in_outer
1423 && STMT_VINFO_RELEVANT (vinfo_for_stmt (op_def_stmt))
1424 != vect_used_in_outer_by_reduction)
1431 gcc_assert (stmt_info);
1433 if (STMT_VINFO_LIVE_P (stmt_info))
1435 /* FORNOW: not yet supported. */
1436 if (dump_enabled_p ())
1437 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1438 "not vectorized: value used after loop.\n");
1442 if (STMT_VINFO_RELEVANT (stmt_info) == vect_used_in_scope
1443 && STMT_VINFO_DEF_TYPE (stmt_info) != vect_induction_def)
1445 /* A scalar-dependence cycle that we don't support. */
1446 if (dump_enabled_p ())
1447 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1448 "not vectorized: scalar dependence cycle.\n");
1452 if (STMT_VINFO_RELEVANT_P (stmt_info))
1454 need_to_vectorize = true;
1455 if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def)
1456 ok = vectorizable_induction (phi, NULL, NULL);
1461 if (dump_enabled_p ())
1463 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1464 "not vectorized: relevant phi not "
1466 dump_gimple_stmt (MSG_MISSED_OPTIMIZATION, TDF_SLIM, phi, 0);
1467 dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
1473 for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
1475 gimple stmt = gsi_stmt (si);
1476 if (!gimple_clobber_p (stmt)
1477 && !vect_analyze_stmt (stmt, &need_to_vectorize, NULL))
1482 /* All operations in the loop are either irrelevant (deal with loop
1483 control, or dead), or only used outside the loop and can be moved
1484 out of the loop (e.g. invariants, inductions). The loop can be
1485 optimized away by scalar optimizations. We're better off not
1486 touching this loop. */
1487 if (!need_to_vectorize)
1489 if (dump_enabled_p ())
1490 dump_printf_loc (MSG_NOTE, vect_location,
1491 "All the computation can be taken out of the loop.\n");
1492 if (dump_enabled_p ())
1493 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1494 "not vectorized: redundant loop. no profit to "
1499 if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo) && dump_enabled_p ())
1500 dump_printf_loc (MSG_NOTE, vect_location,
1501 "vectorization_factor = %d, niters = "
1502 HOST_WIDE_INT_PRINT_DEC "\n", vectorization_factor,
1503 LOOP_VINFO_INT_NITERS (loop_vinfo));
1505 if ((LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
1506 && (LOOP_VINFO_INT_NITERS (loop_vinfo) < vectorization_factor))
1507 || ((max_niter = max_stmt_executions_int (loop)) != -1
1508 && (unsigned HOST_WIDE_INT) max_niter < vectorization_factor))
1510 if (dump_enabled_p ())
1511 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1512 "not vectorized: iteration count too small.\n");
1513 if (dump_enabled_p ())
1514 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1515 "not vectorized: iteration count smaller than "
1516 "vectorization factor.\n");
1520 /* Analyze cost. Decide if worth while to vectorize. */
1522 /* Once VF is set, SLP costs should be updated since the number of created
1523 vector stmts depends on VF. */
1524 vect_update_slp_costs_according_to_vf (loop_vinfo);
1526 vect_estimate_min_profitable_iters (loop_vinfo, &min_profitable_iters,
1527 &min_profitable_estimate);
1528 LOOP_VINFO_COST_MODEL_MIN_ITERS (loop_vinfo) = min_profitable_iters;
1530 if (min_profitable_iters < 0)
1532 if (dump_enabled_p ())
1533 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1534 "not vectorized: vectorization not profitable.\n");
1535 if (dump_enabled_p ())
1536 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1537 "not vectorized: vector version will never be "
1542 min_scalar_loop_bound = ((PARAM_VALUE (PARAM_MIN_VECT_LOOP_BOUND)
1543 * vectorization_factor) - 1);
1546 /* Use the cost model only if it is more conservative than user specified
1549 th = (unsigned) min_scalar_loop_bound;
1550 if (min_profitable_iters
1551 && (!min_scalar_loop_bound
1552 || min_profitable_iters > min_scalar_loop_bound))
1553 th = (unsigned) min_profitable_iters;
1555 if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
1556 && LOOP_VINFO_INT_NITERS (loop_vinfo) <= th)
1558 if (dump_enabled_p ())
1559 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1560 "not vectorized: vectorization not profitable.\n");
1561 if (dump_enabled_p ())
1562 dump_printf_loc (MSG_NOTE, vect_location,
1563 "not vectorized: iteration count smaller than user "
1564 "specified loop bound parameter or minimum profitable "
1565 "iterations (whichever is more conservative).\n");
1569 if ((estimated_niter = estimated_stmt_executions_int (loop)) != -1
1570 && ((unsigned HOST_WIDE_INT) estimated_niter
1571 <= MAX (th, (unsigned)min_profitable_estimate)))
1573 if (dump_enabled_p ())
1574 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1575 "not vectorized: estimated iteration count too "
1577 if (dump_enabled_p ())
1578 dump_printf_loc (MSG_NOTE, vect_location,
1579 "not vectorized: estimated iteration count smaller "
1580 "than specified loop bound parameter or minimum "
1581 "profitable iterations (whichever is more "
1582 "conservative).\n");
1586 if (LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo)
1587 || ((int) tree_ctz (LOOP_VINFO_NITERS (loop_vinfo))
1588 < exact_log2 (vectorization_factor)))
1590 if (dump_enabled_p ())
1591 dump_printf_loc (MSG_NOTE, vect_location, "epilog loop required.\n");
1592 if (!vect_can_advance_ivs_p (loop_vinfo))
1594 if (dump_enabled_p ())
1595 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1596 "not vectorized: can't create epilog loop 1.\n");
1599 if (!slpeel_can_duplicate_loop_p (loop, single_exit (loop)))
1601 if (dump_enabled_p ())
1602 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1603 "not vectorized: can't create epilog loop 2.\n");
1612 /* Function vect_analyze_loop_2.
1614 Apply a set of analyses on LOOP, and create a loop_vec_info struct
1615 for it. The different analyses will record information in the
1616 loop_vec_info struct. */
1618 vect_analyze_loop_2 (loop_vec_info loop_vinfo)
1620 bool ok, slp = false;
1621 int max_vf = MAX_VECTORIZATION_FACTOR;
1624 /* Find all data references in the loop (which correspond to vdefs/vuses)
1625 and analyze their evolution in the loop. Also adjust the minimal
1626 vectorization factor according to the loads and stores.
1628 FORNOW: Handle only simple, array references, which
1629 alignment can be forced, and aligned pointer-references. */
1631 ok = vect_analyze_data_refs (loop_vinfo, NULL, &min_vf);
1634 if (dump_enabled_p ())
1635 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1636 "bad data references.\n");
1640 /* Analyze the access patterns of the data-refs in the loop (consecutive,
1641 complex, etc.). FORNOW: Only handle consecutive access pattern. */
1643 ok = vect_analyze_data_ref_accesses (loop_vinfo, NULL);
1646 if (dump_enabled_p ())
1647 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1648 "bad data access.\n");
1652 /* Classify all cross-iteration scalar data-flow cycles.
1653 Cross-iteration cycles caused by virtual phis are analyzed separately. */
1655 vect_analyze_scalar_cycles (loop_vinfo);
1657 vect_pattern_recog (loop_vinfo, NULL);
1659 /* Data-flow analysis to detect stmts that do not need to be vectorized. */
1661 ok = vect_mark_stmts_to_be_vectorized (loop_vinfo);
1664 if (dump_enabled_p ())
1665 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1666 "unexpected pattern.\n");
1670 /* Analyze data dependences between the data-refs in the loop
1671 and adjust the maximum vectorization factor according to
1673 FORNOW: fail at the first data dependence that we encounter. */
1675 ok = vect_analyze_data_ref_dependences (loop_vinfo, &max_vf);
1679 if (dump_enabled_p ())
1680 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1681 "bad data dependence.\n");
1685 ok = vect_determine_vectorization_factor (loop_vinfo);
1688 if (dump_enabled_p ())
1689 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1690 "can't determine vectorization factor.\n");
1693 if (max_vf < LOOP_VINFO_VECT_FACTOR (loop_vinfo))
1695 if (dump_enabled_p ())
1696 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1697 "bad data dependence.\n");
1701 /* Analyze the alignment of the data-refs in the loop.
1702 Fail if a data reference is found that cannot be vectorized. */
1704 ok = vect_analyze_data_refs_alignment (loop_vinfo, NULL);
1707 if (dump_enabled_p ())
1708 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1709 "bad data alignment.\n");
1713 /* Prune the list of ddrs to be tested at run-time by versioning for alias.
1714 It is important to call pruning after vect_analyze_data_ref_accesses,
1715 since we use grouping information gathered by interleaving analysis. */
1716 ok = vect_prune_runtime_alias_test_list (loop_vinfo);
1719 if (dump_enabled_p ())
1720 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1721 "too long list of versioning for alias "
1722 "run-time tests.\n");
1726 /* This pass will decide on using loop versioning and/or loop peeling in
1727 order to enhance the alignment of data references in the loop. */
1729 ok = vect_enhance_data_refs_alignment (loop_vinfo);
1732 if (dump_enabled_p ())
1733 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1734 "bad data alignment.\n");
1738 /* Check the SLP opportunities in the loop, analyze and build SLP trees. */
1739 ok = vect_analyze_slp (loop_vinfo, NULL);
1742 /* Decide which possible SLP instances to SLP. */
1743 slp = vect_make_slp_decision (loop_vinfo);
1745 /* Find stmts that need to be both vectorized and SLPed. */
1746 vect_detect_hybrid_slp (loop_vinfo);
1751 /* Scan all the operations in the loop and make sure they are
1754 ok = vect_analyze_loop_operations (loop_vinfo, slp);
1757 if (dump_enabled_p ())
1758 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1759 "bad operation or unsupported loop bound.\n");
1766 /* Function vect_analyze_loop.
1768 Apply a set of analyses on LOOP, and create a loop_vec_info struct
1769 for it. The different analyses will record information in the
1770 loop_vec_info struct. */
1772 vect_analyze_loop (struct loop *loop)
1774 loop_vec_info loop_vinfo;
1775 unsigned int vector_sizes;
1777 /* Autodetect first vector size we try. */
1778 current_vector_size = 0;
1779 vector_sizes = targetm.vectorize.autovectorize_vector_sizes ();
1781 if (dump_enabled_p ())
1782 dump_printf_loc (MSG_NOTE, vect_location,
1783 "===== analyze_loop_nest =====\n");
1785 if (loop_outer (loop)
1786 && loop_vec_info_for_loop (loop_outer (loop))
1787 && LOOP_VINFO_VECTORIZABLE_P (loop_vec_info_for_loop (loop_outer (loop))))
1789 if (dump_enabled_p ())
1790 dump_printf_loc (MSG_NOTE, vect_location,
1791 "outer-loop already vectorized.\n");
1797 /* Check the CFG characteristics of the loop (nesting, entry/exit). */
1798 loop_vinfo = vect_analyze_loop_form (loop);
1801 if (dump_enabled_p ())
1802 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
1803 "bad loop form.\n");
1807 if (vect_analyze_loop_2 (loop_vinfo))
1809 LOOP_VINFO_VECTORIZABLE_P (loop_vinfo) = 1;
1814 destroy_loop_vec_info (loop_vinfo, true);
1816 vector_sizes &= ~current_vector_size;
1817 if (vector_sizes == 0
1818 || current_vector_size == 0)
1821 /* Try the next biggest vector size. */
1822 current_vector_size = 1 << floor_log2 (vector_sizes);
1823 if (dump_enabled_p ())
1824 dump_printf_loc (MSG_NOTE, vect_location,
1825 "***** Re-trying analysis with "
1826 "vector size %d\n", current_vector_size);
1831 /* Function reduction_code_for_scalar_code
1834 CODE - tree_code of a reduction operations.
1837 REDUC_CODE - the corresponding tree-code to be used to reduce the
1838 vector of partial results into a single scalar result (which
1839 will also reside in a vector) or ERROR_MARK if the operation is
1840 a supported reduction operation, but does not have such tree-code.
1842 Return FALSE if CODE currently cannot be vectorized as reduction. */
1845 reduction_code_for_scalar_code (enum tree_code code,
1846 enum tree_code *reduc_code)
1851 *reduc_code = REDUC_MAX_EXPR;
1855 *reduc_code = REDUC_MIN_EXPR;
1859 *reduc_code = REDUC_PLUS_EXPR;
1867 *reduc_code = ERROR_MARK;
1876 /* Error reporting helper for vect_is_simple_reduction below. GIMPLE statement
1877 STMT is printed with a message MSG. */
1880 report_vect_op (int msg_type, gimple stmt, const char *msg)
1882 dump_printf_loc (msg_type, vect_location, "%s", msg);
1883 dump_gimple_stmt (msg_type, TDF_SLIM, stmt, 0);
1884 dump_printf (msg_type, "\n");
1888 /* Detect SLP reduction of the form:
1898 PHI is the reduction phi node (#a1 = phi <a5, a0> above)
1899 FIRST_STMT is the first reduction stmt in the chain
1900 (a2 = operation (a1)).
1902 Return TRUE if a reduction chain was detected. */
1905 vect_is_slp_reduction (loop_vec_info loop_info, gimple phi, gimple first_stmt)
1907 struct loop *loop = (gimple_bb (phi))->loop_father;
1908 struct loop *vect_loop = LOOP_VINFO_LOOP (loop_info);
1909 enum tree_code code;
1910 gimple current_stmt = NULL, loop_use_stmt = NULL, first, next_stmt;
1911 stmt_vec_info use_stmt_info, current_stmt_info;
1913 imm_use_iterator imm_iter;
1914 use_operand_p use_p;
1915 int nloop_uses, size = 0, n_out_of_loop_uses;
1918 if (loop != vect_loop)
1921 lhs = PHI_RESULT (phi);
1922 code = gimple_assign_rhs_code (first_stmt);
1926 n_out_of_loop_uses = 0;
1927 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, lhs)
1929 gimple use_stmt = USE_STMT (use_p);
1930 if (is_gimple_debug (use_stmt))
1933 use_stmt = USE_STMT (use_p);
1935 /* Check if we got back to the reduction phi. */
1936 if (use_stmt == phi)
1938 loop_use_stmt = use_stmt;
1943 if (flow_bb_inside_loop_p (loop, gimple_bb (use_stmt)))
1945 if (vinfo_for_stmt (use_stmt)
1946 && !STMT_VINFO_IN_PATTERN_P (vinfo_for_stmt (use_stmt)))
1948 loop_use_stmt = use_stmt;
1953 n_out_of_loop_uses++;
1955 /* There are can be either a single use in the loop or two uses in
1957 if (nloop_uses > 1 || (n_out_of_loop_uses && nloop_uses))
1964 /* We reached a statement with no loop uses. */
1965 if (nloop_uses == 0)
1968 /* This is a loop exit phi, and we haven't reached the reduction phi. */
1969 if (gimple_code (loop_use_stmt) == GIMPLE_PHI)
1972 if (!is_gimple_assign (loop_use_stmt)
1973 || code != gimple_assign_rhs_code (loop_use_stmt)
1974 || !flow_bb_inside_loop_p (loop, gimple_bb (loop_use_stmt)))
1977 /* Insert USE_STMT into reduction chain. */
1978 use_stmt_info = vinfo_for_stmt (loop_use_stmt);
1981 current_stmt_info = vinfo_for_stmt (current_stmt);
1982 GROUP_NEXT_ELEMENT (current_stmt_info) = loop_use_stmt;
1983 GROUP_FIRST_ELEMENT (use_stmt_info)
1984 = GROUP_FIRST_ELEMENT (current_stmt_info);
1987 GROUP_FIRST_ELEMENT (use_stmt_info) = loop_use_stmt;
1989 lhs = gimple_assign_lhs (loop_use_stmt);
1990 current_stmt = loop_use_stmt;
1994 if (!found || loop_use_stmt != phi || size < 2)
1997 /* Swap the operands, if needed, to make the reduction operand be the second
1999 lhs = PHI_RESULT (phi);
2000 next_stmt = GROUP_FIRST_ELEMENT (vinfo_for_stmt (current_stmt));
2003 if (gimple_assign_rhs2 (next_stmt) == lhs)
2005 tree op = gimple_assign_rhs1 (next_stmt);
2006 gimple def_stmt = NULL;
2008 if (TREE_CODE (op) == SSA_NAME)
2009 def_stmt = SSA_NAME_DEF_STMT (op);
2011 /* Check that the other def is either defined in the loop
2012 ("vect_internal_def"), or it's an induction (defined by a
2013 loop-header phi-node). */
2015 && gimple_bb (def_stmt)
2016 && flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))
2017 && (is_gimple_assign (def_stmt)
2018 || is_gimple_call (def_stmt)
2019 || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
2020 == vect_induction_def
2021 || (gimple_code (def_stmt) == GIMPLE_PHI
2022 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
2023 == vect_internal_def
2024 && !is_loop_header_bb_p (gimple_bb (def_stmt)))))
2026 lhs = gimple_assign_lhs (next_stmt);
2027 next_stmt = GROUP_NEXT_ELEMENT (vinfo_for_stmt (next_stmt));
2035 tree op = gimple_assign_rhs2 (next_stmt);
2036 gimple def_stmt = NULL;
2038 if (TREE_CODE (op) == SSA_NAME)
2039 def_stmt = SSA_NAME_DEF_STMT (op);
2041 /* Check that the other def is either defined in the loop
2042 ("vect_internal_def"), or it's an induction (defined by a
2043 loop-header phi-node). */
2045 && gimple_bb (def_stmt)
2046 && flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))
2047 && (is_gimple_assign (def_stmt)
2048 || is_gimple_call (def_stmt)
2049 || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
2050 == vect_induction_def
2051 || (gimple_code (def_stmt) == GIMPLE_PHI
2052 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
2053 == vect_internal_def
2054 && !is_loop_header_bb_p (gimple_bb (def_stmt)))))
2056 if (dump_enabled_p ())
2058 dump_printf_loc (MSG_NOTE, vect_location, "swapping oprnds: ");
2059 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, next_stmt, 0);
2060 dump_printf (MSG_NOTE, "\n");
2063 swap_ssa_operands (next_stmt,
2064 gimple_assign_rhs1_ptr (next_stmt),
2065 gimple_assign_rhs2_ptr (next_stmt));
2066 update_stmt (next_stmt);
2068 if (CONSTANT_CLASS_P (gimple_assign_rhs1 (next_stmt)))
2069 LOOP_VINFO_OPERANDS_SWAPPED (loop_info) = true;
2075 lhs = gimple_assign_lhs (next_stmt);
2076 next_stmt = GROUP_NEXT_ELEMENT (vinfo_for_stmt (next_stmt));
2079 /* Save the chain for further analysis in SLP detection. */
2080 first = GROUP_FIRST_ELEMENT (vinfo_for_stmt (current_stmt));
2081 LOOP_VINFO_REDUCTION_CHAINS (loop_info).safe_push (first);
2082 GROUP_SIZE (vinfo_for_stmt (first)) = size;
2088 /* Function vect_is_simple_reduction_1
2090 (1) Detect a cross-iteration def-use cycle that represents a simple
2091 reduction computation. We look for the following pattern:
2096 a2 = operation (a3, a1)
2103 a2 = operation (a3, a1)
2106 1. operation is commutative and associative and it is safe to
2107 change the order of the computation (if CHECK_REDUCTION is true)
2108 2. no uses for a2 in the loop (a2 is used out of the loop)
2109 3. no uses of a1 in the loop besides the reduction operation
2110 4. no uses of a1 outside the loop.
2112 Conditions 1,4 are tested here.
2113 Conditions 2,3 are tested in vect_mark_stmts_to_be_vectorized.
2115 (2) Detect a cross-iteration def-use cycle in nested loops, i.e.,
2116 nested cycles, if CHECK_REDUCTION is false.
2118 (3) Detect cycles of phi nodes in outer-loop vectorization, i.e., double
2122 inner loop (def of a3)
2125 If MODIFY is true it tries also to rework the code in-place to enable
2126 detection of more reduction patterns. For the time being we rewrite
2127 "res -= RHS" into "rhs += -RHS" when it seems worthwhile.
2131 vect_is_simple_reduction_1 (loop_vec_info loop_info, gimple phi,
2132 bool check_reduction, bool *double_reduc,
2135 struct loop *loop = (gimple_bb (phi))->loop_father;
2136 struct loop *vect_loop = LOOP_VINFO_LOOP (loop_info);
2137 edge latch_e = loop_latch_edge (loop);
2138 tree loop_arg = PHI_ARG_DEF_FROM_EDGE (phi, latch_e);
2139 gimple def_stmt, def1 = NULL, def2 = NULL;
2140 enum tree_code orig_code, code;
2141 tree op1, op2, op3 = NULL_TREE, op4 = NULL_TREE;
2145 imm_use_iterator imm_iter;
2146 use_operand_p use_p;
2149 *double_reduc = false;
2151 /* If CHECK_REDUCTION is true, we assume inner-most loop vectorization,
2152 otherwise, we assume outer loop vectorization. */
2153 gcc_assert ((check_reduction && loop == vect_loop)
2154 || (!check_reduction && flow_loop_nested_p (vect_loop, loop)));
2156 name = PHI_RESULT (phi);
2158 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, name)
2160 gimple use_stmt = USE_STMT (use_p);
2161 if (is_gimple_debug (use_stmt))
2164 if (!flow_bb_inside_loop_p (loop, gimple_bb (use_stmt)))
2166 if (dump_enabled_p ())
2167 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
2168 "intermediate value used outside loop.\n");
2173 if (vinfo_for_stmt (use_stmt)
2174 && !is_pattern_stmt_p (vinfo_for_stmt (use_stmt)))
2178 if (dump_enabled_p ())
2179 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
2180 "reduction used in loop.\n");
2185 if (TREE_CODE (loop_arg) != SSA_NAME)
2187 if (dump_enabled_p ())
2189 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
2190 "reduction: not ssa_name: ");
2191 dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM, loop_arg);
2192 dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
2197 def_stmt = SSA_NAME_DEF_STMT (loop_arg);
2200 if (dump_enabled_p ())
2201 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
2202 "reduction: no def_stmt.\n");
2206 if (!is_gimple_assign (def_stmt) && gimple_code (def_stmt) != GIMPLE_PHI)
2208 if (dump_enabled_p ())
2210 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, def_stmt, 0);
2211 dump_printf (MSG_NOTE, "\n");
2216 if (is_gimple_assign (def_stmt))
2218 name = gimple_assign_lhs (def_stmt);
2223 name = PHI_RESULT (def_stmt);
2228 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, name)
2230 gimple use_stmt = USE_STMT (use_p);
2231 if (is_gimple_debug (use_stmt))
2233 if (flow_bb_inside_loop_p (loop, gimple_bb (use_stmt))
2234 && vinfo_for_stmt (use_stmt)
2235 && !is_pattern_stmt_p (vinfo_for_stmt (use_stmt)))
2239 if (dump_enabled_p ())
2240 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
2241 "reduction used in loop.\n");
2246 /* If DEF_STMT is a phi node itself, we expect it to have a single argument
2247 defined in the inner loop. */
2250 op1 = PHI_ARG_DEF (def_stmt, 0);
2252 if (gimple_phi_num_args (def_stmt) != 1
2253 || TREE_CODE (op1) != SSA_NAME)
2255 if (dump_enabled_p ())
2256 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
2257 "unsupported phi node definition.\n");
2262 def1 = SSA_NAME_DEF_STMT (op1);
2263 if (flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))
2265 && flow_bb_inside_loop_p (loop->inner, gimple_bb (def1))
2266 && is_gimple_assign (def1))
2268 if (dump_enabled_p ())
2269 report_vect_op (MSG_NOTE, def_stmt,
2270 "detected double reduction: ");
2272 *double_reduc = true;
2279 code = orig_code = gimple_assign_rhs_code (def_stmt);
2281 /* We can handle "res -= x[i]", which is non-associative by
2282 simply rewriting this into "res += -x[i]". Avoid changing
2283 gimple instruction for the first simple tests and only do this
2284 if we're allowed to change code at all. */
2285 if (code == MINUS_EXPR
2287 && (op1 = gimple_assign_rhs1 (def_stmt))
2288 && TREE_CODE (op1) == SSA_NAME
2289 && SSA_NAME_DEF_STMT (op1) == phi)
2293 && (!commutative_tree_code (code) || !associative_tree_code (code)))
2295 if (dump_enabled_p ())
2296 report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
2297 "reduction: not commutative/associative: ");
2301 if (get_gimple_rhs_class (code) != GIMPLE_BINARY_RHS)
2303 if (code != COND_EXPR)
2305 if (dump_enabled_p ())
2306 report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
2307 "reduction: not binary operation: ");
2312 op3 = gimple_assign_rhs1 (def_stmt);
2313 if (COMPARISON_CLASS_P (op3))
2315 op4 = TREE_OPERAND (op3, 1);
2316 op3 = TREE_OPERAND (op3, 0);
2319 op1 = gimple_assign_rhs2 (def_stmt);
2320 op2 = gimple_assign_rhs3 (def_stmt);
2322 if (TREE_CODE (op1) != SSA_NAME && TREE_CODE (op2) != SSA_NAME)
2324 if (dump_enabled_p ())
2325 report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
2326 "reduction: uses not ssa_names: ");
2333 op1 = gimple_assign_rhs1 (def_stmt);
2334 op2 = gimple_assign_rhs2 (def_stmt);
2336 if (TREE_CODE (op1) != SSA_NAME && TREE_CODE (op2) != SSA_NAME)
2338 if (dump_enabled_p ())
2339 report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
2340 "reduction: uses not ssa_names: ");
2346 type = TREE_TYPE (gimple_assign_lhs (def_stmt));
2347 if ((TREE_CODE (op1) == SSA_NAME
2348 && !types_compatible_p (type,TREE_TYPE (op1)))
2349 || (TREE_CODE (op2) == SSA_NAME
2350 && !types_compatible_p (type, TREE_TYPE (op2)))
2351 || (op3 && TREE_CODE (op3) == SSA_NAME
2352 && !types_compatible_p (type, TREE_TYPE (op3)))
2353 || (op4 && TREE_CODE (op4) == SSA_NAME
2354 && !types_compatible_p (type, TREE_TYPE (op4))))
2356 if (dump_enabled_p ())
2358 dump_printf_loc (MSG_NOTE, vect_location,
2359 "reduction: multiple types: operation type: ");
2360 dump_generic_expr (MSG_NOTE, TDF_SLIM, type);
2361 dump_printf (MSG_NOTE, ", operands types: ");
2362 dump_generic_expr (MSG_NOTE, TDF_SLIM,
2364 dump_printf (MSG_NOTE, ",");
2365 dump_generic_expr (MSG_NOTE, TDF_SLIM,
2369 dump_printf (MSG_NOTE, ",");
2370 dump_generic_expr (MSG_NOTE, TDF_SLIM,
2376 dump_printf (MSG_NOTE, ",");
2377 dump_generic_expr (MSG_NOTE, TDF_SLIM,
2380 dump_printf (MSG_NOTE, "\n");
2386 /* Check that it's ok to change the order of the computation.
2387 Generally, when vectorizing a reduction we change the order of the
2388 computation. This may change the behavior of the program in some
2389 cases, so we need to check that this is ok. One exception is when
2390 vectorizing an outer-loop: the inner-loop is executed sequentially,
2391 and therefore vectorizing reductions in the inner-loop during
2392 outer-loop vectorization is safe. */
2394 /* CHECKME: check for !flag_finite_math_only too? */
2395 if (SCALAR_FLOAT_TYPE_P (type) && !flag_associative_math
2398 /* Changing the order of operations changes the semantics. */
2399 if (dump_enabled_p ())
2400 report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
2401 "reduction: unsafe fp math optimization: ");
2404 else if (INTEGRAL_TYPE_P (type) && TYPE_OVERFLOW_TRAPS (type)
2407 /* Changing the order of operations changes the semantics. */
2408 if (dump_enabled_p ())
2409 report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
2410 "reduction: unsafe int math optimization: ");
2413 else if (SAT_FIXED_POINT_TYPE_P (type) && check_reduction)
2415 /* Changing the order of operations changes the semantics. */
2416 if (dump_enabled_p ())
2417 report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
2418 "reduction: unsafe fixed-point math optimization: ");
2422 /* If we detected "res -= x[i]" earlier, rewrite it into
2423 "res += -x[i]" now. If this turns out to be useless reassoc
2424 will clean it up again. */
2425 if (orig_code == MINUS_EXPR)
2427 tree rhs = gimple_assign_rhs2 (def_stmt);
2428 tree negrhs = make_ssa_name (TREE_TYPE (rhs), NULL);
2429 gimple negate_stmt = gimple_build_assign_with_ops (NEGATE_EXPR, negrhs,
2431 gimple_stmt_iterator gsi = gsi_for_stmt (def_stmt);
2432 set_vinfo_for_stmt (negate_stmt, new_stmt_vec_info (negate_stmt,
2434 gsi_insert_before (&gsi, negate_stmt, GSI_NEW_STMT);
2435 gimple_assign_set_rhs2 (def_stmt, negrhs);
2436 gimple_assign_set_rhs_code (def_stmt, PLUS_EXPR);
2437 update_stmt (def_stmt);
2440 /* Reduction is safe. We're dealing with one of the following:
2441 1) integer arithmetic and no trapv
2442 2) floating point arithmetic, and special flags permit this optimization
2443 3) nested cycle (i.e., outer loop vectorization). */
2444 if (TREE_CODE (op1) == SSA_NAME)
2445 def1 = SSA_NAME_DEF_STMT (op1);
2447 if (TREE_CODE (op2) == SSA_NAME)
2448 def2 = SSA_NAME_DEF_STMT (op2);
2450 if (code != COND_EXPR
2451 && ((!def1 || gimple_nop_p (def1)) && (!def2 || gimple_nop_p (def2))))
2453 if (dump_enabled_p ())
2454 report_vect_op (MSG_NOTE, def_stmt, "reduction: no defs for operands: ");
2458 /* Check that one def is the reduction def, defined by PHI,
2459 the other def is either defined in the loop ("vect_internal_def"),
2460 or it's an induction (defined by a loop-header phi-node). */
2462 if (def2 && def2 == phi
2463 && (code == COND_EXPR
2464 || !def1 || gimple_nop_p (def1)
2465 || !flow_bb_inside_loop_p (loop, gimple_bb (def1))
2466 || (def1 && flow_bb_inside_loop_p (loop, gimple_bb (def1))
2467 && (is_gimple_assign (def1)
2468 || is_gimple_call (def1)
2469 || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def1))
2470 == vect_induction_def
2471 || (gimple_code (def1) == GIMPLE_PHI
2472 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def1))
2473 == vect_internal_def
2474 && !is_loop_header_bb_p (gimple_bb (def1)))))))
2476 if (dump_enabled_p ())
2477 report_vect_op (MSG_NOTE, def_stmt, "detected reduction: ");
2481 if (def1 && def1 == phi
2482 && (code == COND_EXPR
2483 || !def2 || gimple_nop_p (def2)
2484 || !flow_bb_inside_loop_p (loop, gimple_bb (def2))
2485 || (def2 && flow_bb_inside_loop_p (loop, gimple_bb (def2))
2486 && (is_gimple_assign (def2)
2487 || is_gimple_call (def2)
2488 || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def2))
2489 == vect_induction_def
2490 || (gimple_code (def2) == GIMPLE_PHI
2491 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def2))
2492 == vect_internal_def
2493 && !is_loop_header_bb_p (gimple_bb (def2)))))))
2495 if (check_reduction)
2497 /* Swap operands (just for simplicity - so that the rest of the code
2498 can assume that the reduction variable is always the last (second)
2500 if (dump_enabled_p ())
2501 report_vect_op (MSG_NOTE, def_stmt,
2502 "detected reduction: need to swap operands: ");
2504 swap_ssa_operands (def_stmt, gimple_assign_rhs1_ptr (def_stmt),
2505 gimple_assign_rhs2_ptr (def_stmt));
2507 if (CONSTANT_CLASS_P (gimple_assign_rhs1 (def_stmt)))
2508 LOOP_VINFO_OPERANDS_SWAPPED (loop_info) = true;
2512 if (dump_enabled_p ())
2513 report_vect_op (MSG_NOTE, def_stmt, "detected reduction: ");
2519 /* Try to find SLP reduction chain. */
2520 if (check_reduction && vect_is_slp_reduction (loop_info, phi, def_stmt))
2522 if (dump_enabled_p ())
2523 report_vect_op (MSG_NOTE, def_stmt,
2524 "reduction: detected reduction chain: ");
2529 if (dump_enabled_p ())
2530 report_vect_op (MSG_MISSED_OPTIMIZATION, def_stmt,
2531 "reduction: unknown pattern: ");
2536 /* Wrapper around vect_is_simple_reduction_1, that won't modify code
2537 in-place. Arguments as there. */
2540 vect_is_simple_reduction (loop_vec_info loop_info, gimple phi,
2541 bool check_reduction, bool *double_reduc)
2543 return vect_is_simple_reduction_1 (loop_info, phi, check_reduction,
2544 double_reduc, false);
2547 /* Wrapper around vect_is_simple_reduction_1, which will modify code
2548 in-place if it enables detection of more reductions. Arguments
2552 vect_force_simple_reduction (loop_vec_info loop_info, gimple phi,
2553 bool check_reduction, bool *double_reduc)
2555 return vect_is_simple_reduction_1 (loop_info, phi, check_reduction,
2556 double_reduc, true);
2559 /* Calculate the cost of one scalar iteration of the loop. */
2561 vect_get_single_scalar_iteration_cost (loop_vec_info loop_vinfo)
2563 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
2564 basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
2565 int nbbs = loop->num_nodes, factor, scalar_single_iter_cost = 0;
2566 int innerloop_iters, i, stmt_cost;
2568 /* Count statements in scalar loop. Using this as scalar cost for a single
2571 TODO: Add outer loop support.
2573 TODO: Consider assigning different costs to different scalar
2577 innerloop_iters = 1;
2579 innerloop_iters = 50; /* FIXME */
2581 for (i = 0; i < nbbs; i++)
2583 gimple_stmt_iterator si;
2584 basic_block bb = bbs[i];
2586 if (bb->loop_father == loop->inner)
2587 factor = innerloop_iters;
2591 for (si = gsi_start_bb (bb); !gsi_end_p (si); gsi_next (&si))
2593 gimple stmt = gsi_stmt (si);
2594 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
2596 if (!is_gimple_assign (stmt) && !is_gimple_call (stmt))
2599 /* Skip stmts that are not vectorized inside the loop. */
2601 && !STMT_VINFO_RELEVANT_P (stmt_info)
2602 && (!STMT_VINFO_LIVE_P (stmt_info)
2603 || !VECTORIZABLE_CYCLE_DEF (STMT_VINFO_DEF_TYPE (stmt_info)))
2604 && !STMT_VINFO_IN_PATTERN_P (stmt_info))
2607 if (STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt)))
2609 if (DR_IS_READ (STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt))))
2610 stmt_cost = vect_get_stmt_cost (scalar_load);
2612 stmt_cost = vect_get_stmt_cost (scalar_store);
2615 stmt_cost = vect_get_stmt_cost (scalar_stmt);
2617 scalar_single_iter_cost += stmt_cost * factor;
2620 return scalar_single_iter_cost;
2623 /* Calculate cost of peeling the loop PEEL_ITERS_PROLOGUE times. */
2625 vect_get_known_peeling_cost (loop_vec_info loop_vinfo, int peel_iters_prologue,
2626 int *peel_iters_epilogue,
2627 int scalar_single_iter_cost,
2628 stmt_vector_for_cost *prologue_cost_vec,
2629 stmt_vector_for_cost *epilogue_cost_vec)
2632 int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
2634 if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
2636 *peel_iters_epilogue = vf/2;
2637 if (dump_enabled_p ())
2638 dump_printf_loc (MSG_NOTE, vect_location,
2639 "cost model: epilogue peel iters set to vf/2 "
2640 "because loop iterations are unknown .\n");
2642 /* If peeled iterations are known but number of scalar loop
2643 iterations are unknown, count a taken branch per peeled loop. */
2644 retval = record_stmt_cost (prologue_cost_vec, 2, cond_branch_taken,
2645 NULL, 0, vect_prologue);
2649 int niters = LOOP_VINFO_INT_NITERS (loop_vinfo);
2650 peel_iters_prologue = niters < peel_iters_prologue ?
2651 niters : peel_iters_prologue;
2652 *peel_iters_epilogue = (niters - peel_iters_prologue) % vf;
2653 /* If we need to peel for gaps, but no peeling is required, we have to
2654 peel VF iterations. */
2655 if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo) && !*peel_iters_epilogue)
2656 *peel_iters_epilogue = vf;
2659 if (peel_iters_prologue)
2660 retval += record_stmt_cost (prologue_cost_vec,
2661 peel_iters_prologue * scalar_single_iter_cost,
2662 scalar_stmt, NULL, 0, vect_prologue);
2663 if (*peel_iters_epilogue)
2664 retval += record_stmt_cost (epilogue_cost_vec,
2665 *peel_iters_epilogue * scalar_single_iter_cost,
2666 scalar_stmt, NULL, 0, vect_epilogue);
2670 /* Function vect_estimate_min_profitable_iters
2672 Return the number of iterations required for the vector version of the
2673 loop to be profitable relative to the cost of the scalar version of the
2677 vect_estimate_min_profitable_iters (loop_vec_info loop_vinfo,
2678 int *ret_min_profitable_niters,
2679 int *ret_min_profitable_estimate)
2681 int min_profitable_iters;
2682 int min_profitable_estimate;
2683 int peel_iters_prologue;
2684 int peel_iters_epilogue;
2685 unsigned vec_inside_cost = 0;
2686 int vec_outside_cost = 0;
2687 unsigned vec_prologue_cost = 0;
2688 unsigned vec_epilogue_cost = 0;
2689 int scalar_single_iter_cost = 0;
2690 int scalar_outside_cost = 0;
2691 int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
2692 int npeel = LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo);
2693 void *target_cost_data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo);
2695 /* Cost model disabled. */
2696 if (unlimited_cost_model ())
2698 dump_printf_loc (MSG_NOTE, vect_location, "cost model disabled.\n");
2699 *ret_min_profitable_niters = 0;
2700 *ret_min_profitable_estimate = 0;
2704 /* Requires loop versioning tests to handle misalignment. */
2705 if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo))
2707 /* FIXME: Make cost depend on complexity of individual check. */
2708 unsigned len = LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo).length ();
2709 (void) add_stmt_cost (target_cost_data, len, vector_stmt, NULL, 0,
2711 dump_printf (MSG_NOTE,
2712 "cost model: Adding cost of checks for loop "
2713 "versioning to treat misalignment.\n");
2716 /* Requires loop versioning with alias checks. */
2717 if (LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
2719 /* FIXME: Make cost depend on complexity of individual check. */
2720 unsigned len = LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo).length ();
2721 (void) add_stmt_cost (target_cost_data, len, vector_stmt, NULL, 0,
2723 dump_printf (MSG_NOTE,
2724 "cost model: Adding cost of checks for loop "
2725 "versioning aliasing.\n");
2728 if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)
2729 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
2730 (void) add_stmt_cost (target_cost_data, 1, cond_branch_taken, NULL, 0,
2733 /* Count statements in scalar loop. Using this as scalar cost for a single
2736 TODO: Add outer loop support.
2738 TODO: Consider assigning different costs to different scalar
2741 scalar_single_iter_cost = vect_get_single_scalar_iteration_cost (loop_vinfo);
2743 /* Add additional cost for the peeled instructions in prologue and epilogue
2746 FORNOW: If we don't know the value of peel_iters for prologue or epilogue
2747 at compile-time - we assume it's vf/2 (the worst would be vf-1).
2749 TODO: Build an expression that represents peel_iters for prologue and
2750 epilogue to be used in a run-time test. */
2754 peel_iters_prologue = vf/2;
2755 dump_printf (MSG_NOTE, "cost model: "
2756 "prologue peel iters set to vf/2.\n");
2758 /* If peeling for alignment is unknown, loop bound of main loop becomes
2760 peel_iters_epilogue = vf/2;
2761 dump_printf (MSG_NOTE, "cost model: "
2762 "epilogue peel iters set to vf/2 because "
2763 "peeling for alignment is unknown.\n");
2765 /* If peeled iterations are unknown, count a taken branch and a not taken
2766 branch per peeled loop. Even if scalar loop iterations are known,
2767 vector iterations are not known since peeled prologue iterations are
2768 not known. Hence guards remain the same. */
2769 (void) add_stmt_cost (target_cost_data, 2, cond_branch_taken,
2770 NULL, 0, vect_prologue);
2771 (void) add_stmt_cost (target_cost_data, 2, cond_branch_not_taken,
2772 NULL, 0, vect_prologue);
2773 /* FORNOW: Don't attempt to pass individual scalar instructions to
2774 the model; just assume linear cost for scalar iterations. */
2775 (void) add_stmt_cost (target_cost_data,
2776 peel_iters_prologue * scalar_single_iter_cost,
2777 scalar_stmt, NULL, 0, vect_prologue);
2778 (void) add_stmt_cost (target_cost_data,
2779 peel_iters_epilogue * scalar_single_iter_cost,
2780 scalar_stmt, NULL, 0, vect_epilogue);
2784 stmt_vector_for_cost prologue_cost_vec, epilogue_cost_vec;
2785 stmt_info_for_cost *si;
2787 void *data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo);
2789 prologue_cost_vec.create (2);
2790 epilogue_cost_vec.create (2);
2791 peel_iters_prologue = npeel;
2793 (void) vect_get_known_peeling_cost (loop_vinfo, peel_iters_prologue,
2794 &peel_iters_epilogue,
2795 scalar_single_iter_cost,
2797 &epilogue_cost_vec);
2799 FOR_EACH_VEC_ELT (prologue_cost_vec, j, si)
2801 struct _stmt_vec_info *stmt_info
2802 = si->stmt ? vinfo_for_stmt (si->stmt) : NULL;
2803 (void) add_stmt_cost (data, si->count, si->kind, stmt_info,
2804 si->misalign, vect_prologue);
2807 FOR_EACH_VEC_ELT (epilogue_cost_vec, j, si)
2809 struct _stmt_vec_info *stmt_info
2810 = si->stmt ? vinfo_for_stmt (si->stmt) : NULL;
2811 (void) add_stmt_cost (data, si->count, si->kind, stmt_info,
2812 si->misalign, vect_epilogue);
2815 prologue_cost_vec.release ();
2816 epilogue_cost_vec.release ();
2819 /* FORNOW: The scalar outside cost is incremented in one of the
2822 1. The vectorizer checks for alignment and aliasing and generates
2823 a condition that allows dynamic vectorization. A cost model
2824 check is ANDED with the versioning condition. Hence scalar code
2825 path now has the added cost of the versioning check.
2827 if (cost > th & versioning_check)
2830 Hence run-time scalar is incremented by not-taken branch cost.
2832 2. The vectorizer then checks if a prologue is required. If the
2833 cost model check was not done before during versioning, it has to
2834 be done before the prologue check.
2837 prologue = scalar_iters
2842 if (prologue == num_iters)
2845 Hence the run-time scalar cost is incremented by a taken branch,
2846 plus a not-taken branch, plus a taken branch cost.
2848 3. The vectorizer then checks if an epilogue is required. If the
2849 cost model check was not done before during prologue check, it
2850 has to be done with the epilogue check.
2856 if (prologue == num_iters)
2859 if ((cost <= th) | (scalar_iters-prologue-epilogue == 0))
2862 Hence the run-time scalar cost should be incremented by 2 taken
2865 TODO: The back end may reorder the BBS's differently and reverse
2866 conditions/branch directions. Change the estimates below to
2867 something more reasonable. */
2869 /* If the number of iterations is known and we do not do versioning, we can
2870 decide whether to vectorize at compile time. Hence the scalar version
2871 do not carry cost model guard costs. */
2872 if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
2873 || LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)
2874 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
2876 /* Cost model check occurs at versioning. */
2877 if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)
2878 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
2879 scalar_outside_cost += vect_get_stmt_cost (cond_branch_not_taken);
2882 /* Cost model check occurs at prologue generation. */
2883 if (LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo) < 0)
2884 scalar_outside_cost += 2 * vect_get_stmt_cost (cond_branch_taken)
2885 + vect_get_stmt_cost (cond_branch_not_taken);
2886 /* Cost model check occurs at epilogue generation. */
2888 scalar_outside_cost += 2 * vect_get_stmt_cost (cond_branch_taken);
2892 /* Complete the target-specific cost calculations. */
2893 finish_cost (LOOP_VINFO_TARGET_COST_DATA (loop_vinfo), &vec_prologue_cost,
2894 &vec_inside_cost, &vec_epilogue_cost);
2896 vec_outside_cost = (int)(vec_prologue_cost + vec_epilogue_cost);
2898 /* Calculate number of iterations required to make the vector version
2899 profitable, relative to the loop bodies only. The following condition
2901 SIC * niters + SOC > VIC * ((niters-PL_ITERS-EP_ITERS)/VF) + VOC
2903 SIC = scalar iteration cost, VIC = vector iteration cost,
2904 VOC = vector outside cost, VF = vectorization factor,
2905 PL_ITERS = prologue iterations, EP_ITERS= epilogue iterations
2906 SOC = scalar outside cost for run time cost model check. */
2908 if ((scalar_single_iter_cost * vf) > (int) vec_inside_cost)
2910 if (vec_outside_cost <= 0)
2911 min_profitable_iters = 1;
2914 min_profitable_iters = ((vec_outside_cost - scalar_outside_cost) * vf
2915 - vec_inside_cost * peel_iters_prologue
2916 - vec_inside_cost * peel_iters_epilogue)
2917 / ((scalar_single_iter_cost * vf)
2920 if ((scalar_single_iter_cost * vf * min_profitable_iters)
2921 <= (((int) vec_inside_cost * min_profitable_iters)
2922 + (((int) vec_outside_cost - scalar_outside_cost) * vf)))
2923 min_profitable_iters++;
2926 /* vector version will never be profitable. */
2929 if (dump_enabled_p ())
2930 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
2931 "cost model: the vector iteration cost = %d "
2932 "divided by the scalar iteration cost = %d "
2933 "is greater or equal to the vectorization factor = %d"
2935 vec_inside_cost, scalar_single_iter_cost, vf);
2936 *ret_min_profitable_niters = -1;
2937 *ret_min_profitable_estimate = -1;
2941 if (dump_enabled_p ())
2943 dump_printf_loc (MSG_NOTE, vect_location, "Cost model analysis: \n");
2944 dump_printf (MSG_NOTE, " Vector inside of loop cost: %d\n",
2946 dump_printf (MSG_NOTE, " Vector prologue cost: %d\n",
2948 dump_printf (MSG_NOTE, " Vector epilogue cost: %d\n",
2950 dump_printf (MSG_NOTE, " Scalar iteration cost: %d\n",
2951 scalar_single_iter_cost);
2952 dump_printf (MSG_NOTE, " Scalar outside cost: %d\n",
2953 scalar_outside_cost);
2954 dump_printf (MSG_NOTE, " Vector outside cost: %d\n",
2956 dump_printf (MSG_NOTE, " prologue iterations: %d\n",
2957 peel_iters_prologue);
2958 dump_printf (MSG_NOTE, " epilogue iterations: %d\n",
2959 peel_iters_epilogue);
2960 dump_printf (MSG_NOTE,
2961 " Calculated minimum iters for profitability: %d\n",
2962 min_profitable_iters);
2963 dump_printf (MSG_NOTE, "\n");
2966 min_profitable_iters =
2967 min_profitable_iters < vf ? vf : min_profitable_iters;
2969 /* Because the condition we create is:
2970 if (niters <= min_profitable_iters)
2971 then skip the vectorized loop. */
2972 min_profitable_iters--;
2974 if (dump_enabled_p ())
2975 dump_printf_loc (MSG_NOTE, vect_location,
2976 " Runtime profitability threshold = %d\n",
2977 min_profitable_iters);
2979 *ret_min_profitable_niters = min_profitable_iters;
2981 /* Calculate number of iterations required to make the vector version
2982 profitable, relative to the loop bodies only.
2984 Non-vectorized variant is SIC * niters and it must win over vector
2985 variant on the expected loop trip count. The following condition must hold true:
2986 SIC * niters > VIC * ((niters-PL_ITERS-EP_ITERS)/VF) + VOC + SOC */
2988 if (vec_outside_cost <= 0)
2989 min_profitable_estimate = 1;
2992 min_profitable_estimate = ((vec_outside_cost + scalar_outside_cost) * vf
2993 - vec_inside_cost * peel_iters_prologue
2994 - vec_inside_cost * peel_iters_epilogue)
2995 / ((scalar_single_iter_cost * vf)
2998 min_profitable_estimate --;
2999 min_profitable_estimate = MAX (min_profitable_estimate, min_profitable_iters);
3000 if (dump_enabled_p ())
3001 dump_printf_loc (MSG_NOTE, vect_location,
3002 " Static estimate profitability threshold = %d\n",
3003 min_profitable_iters);
3005 *ret_min_profitable_estimate = min_profitable_estimate;
3009 /* TODO: Close dependency between vect_model_*_cost and vectorizable_*
3010 functions. Design better to avoid maintenance issues. */
3012 /* Function vect_model_reduction_cost.
3014 Models cost for a reduction operation, including the vector ops
3015 generated within the strip-mine loop, the initial definition before
3016 the loop, and the epilogue code that must be generated. */
3019 vect_model_reduction_cost (stmt_vec_info stmt_info, enum tree_code reduc_code,
3022 int prologue_cost = 0, epilogue_cost = 0;
3023 enum tree_code code;
3026 gimple stmt, orig_stmt;
3028 enum machine_mode mode;
3029 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
3030 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
3031 void *target_cost_data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo);
3033 /* Cost of reduction op inside loop. */
3034 unsigned inside_cost = add_stmt_cost (target_cost_data, ncopies, vector_stmt,
3035 stmt_info, 0, vect_body);
3036 stmt = STMT_VINFO_STMT (stmt_info);
3038 switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt)))
3040 case GIMPLE_SINGLE_RHS:
3041 gcc_assert (TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt)) == ternary_op);
3042 reduction_op = TREE_OPERAND (gimple_assign_rhs1 (stmt), 2);
3044 case GIMPLE_UNARY_RHS:
3045 reduction_op = gimple_assign_rhs1 (stmt);
3047 case GIMPLE_BINARY_RHS:
3048 reduction_op = gimple_assign_rhs2 (stmt);
3050 case GIMPLE_TERNARY_RHS:
3051 reduction_op = gimple_assign_rhs3 (stmt);
3057 vectype = get_vectype_for_scalar_type (TREE_TYPE (reduction_op));
3060 if (dump_enabled_p ())
3062 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
3063 "unsupported data-type ");
3064 dump_generic_expr (MSG_MISSED_OPTIMIZATION, TDF_SLIM,
3065 TREE_TYPE (reduction_op));
3066 dump_printf (MSG_MISSED_OPTIMIZATION, "\n");
3071 mode = TYPE_MODE (vectype);
3072 orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);
3075 orig_stmt = STMT_VINFO_STMT (stmt_info);
3077 code = gimple_assign_rhs_code (orig_stmt);
3079 /* Add in cost for initial definition. */
3080 prologue_cost += add_stmt_cost (target_cost_data, 1, scalar_to_vec,
3081 stmt_info, 0, vect_prologue);
3083 /* Determine cost of epilogue code.
3085 We have a reduction operator that will reduce the vector in one statement.
3086 Also requires scalar extract. */
3088 if (!nested_in_vect_loop_p (loop, orig_stmt))
3090 if (reduc_code != ERROR_MARK)
3092 epilogue_cost += add_stmt_cost (target_cost_data, 1, vector_stmt,
3093 stmt_info, 0, vect_epilogue);
3094 epilogue_cost += add_stmt_cost (target_cost_data, 1, vec_to_scalar,
3095 stmt_info, 0, vect_epilogue);
3099 int vec_size_in_bits = tree_low_cst (TYPE_SIZE (vectype), 1);
3101 TYPE_SIZE (TREE_TYPE (gimple_assign_lhs (orig_stmt)));
3102 int element_bitsize = tree_low_cst (bitsize, 1);
3103 int nelements = vec_size_in_bits / element_bitsize;
3105 optab = optab_for_tree_code (code, vectype, optab_default);
3107 /* We have a whole vector shift available. */
3108 if (VECTOR_MODE_P (mode)
3109 && optab_handler (optab, mode) != CODE_FOR_nothing
3110 && optab_handler (vec_shr_optab, mode) != CODE_FOR_nothing)
3112 /* Final reduction via vector shifts and the reduction operator.
3113 Also requires scalar extract. */
3114 epilogue_cost += add_stmt_cost (target_cost_data,
3115 exact_log2 (nelements) * 2,
3116 vector_stmt, stmt_info, 0,
3118 epilogue_cost += add_stmt_cost (target_cost_data, 1,
3119 vec_to_scalar, stmt_info, 0,
3123 /* Use extracts and reduction op for final reduction. For N
3124 elements, we have N extracts and N-1 reduction ops. */
3125 epilogue_cost += add_stmt_cost (target_cost_data,
3126 nelements + nelements - 1,
3127 vector_stmt, stmt_info, 0,
3132 if (dump_enabled_p ())
3133 dump_printf (MSG_NOTE,
3134 "vect_model_reduction_cost: inside_cost = %d, "
3135 "prologue_cost = %d, epilogue_cost = %d .\n", inside_cost,
3136 prologue_cost, epilogue_cost);
3142 /* Function vect_model_induction_cost.
3144 Models cost for induction operations. */
3147 vect_model_induction_cost (stmt_vec_info stmt_info, int ncopies)
3149 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
3150 void *target_cost_data = LOOP_VINFO_TARGET_COST_DATA (loop_vinfo);
3151 unsigned inside_cost, prologue_cost;
3153 /* loop cost for vec_loop. */
3154 inside_cost = add_stmt_cost (target_cost_data, ncopies, vector_stmt,
3155 stmt_info, 0, vect_body);
3157 /* prologue cost for vec_init and vec_step. */
3158 prologue_cost = add_stmt_cost (target_cost_data, 2, scalar_to_vec,
3159 stmt_info, 0, vect_prologue);
3161 if (dump_enabled_p ())
3162 dump_printf_loc (MSG_NOTE, vect_location,
3163 "vect_model_induction_cost: inside_cost = %d, "
3164 "prologue_cost = %d .\n", inside_cost, prologue_cost);
3168 /* Function get_initial_def_for_induction
3171 STMT - a stmt that performs an induction operation in the loop.
3172 IV_PHI - the initial value of the induction variable
3175 Return a vector variable, initialized with the first VF values of
3176 the induction variable. E.g., for an iv with IV_PHI='X' and
3177 evolution S, for a vector of 4 units, we want to return:
3178 [X, X + S, X + 2*S, X + 3*S]. */
3181 get_initial_def_for_induction (gimple iv_phi)
3183 stmt_vec_info stmt_vinfo = vinfo_for_stmt (iv_phi);
3184 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo);
3185 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
3188 edge pe = loop_preheader_edge (loop);
3189 struct loop *iv_loop;
3191 tree new_vec, vec_init, vec_step, t;
3195 gimple init_stmt, induction_phi, new_stmt;
3196 tree induc_def, vec_def, vec_dest;
3197 tree init_expr, step_expr;
3198 int vf = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
3203 stmt_vec_info phi_info = vinfo_for_stmt (iv_phi);
3204 bool nested_in_vect_loop = false;
3205 gimple_seq stmts = NULL;
3206 imm_use_iterator imm_iter;
3207 use_operand_p use_p;
3211 gimple_stmt_iterator si;
3212 basic_block bb = gimple_bb (iv_phi);
3216 /* Is phi in an inner-loop, while vectorizing an enclosing outer-loop? */
3217 if (nested_in_vect_loop_p (loop, iv_phi))
3219 nested_in_vect_loop = true;
3220 iv_loop = loop->inner;
3224 gcc_assert (iv_loop == (gimple_bb (iv_phi))->loop_father);
3226 latch_e = loop_latch_edge (iv_loop);
3227 loop_arg = PHI_ARG_DEF_FROM_EDGE (iv_phi, latch_e);
3229 access_fn = analyze_scalar_evolution (iv_loop, PHI_RESULT (iv_phi));
3230 gcc_assert (access_fn);
3231 STRIP_NOPS (access_fn);
3232 ok = vect_is_simple_iv_evolution (iv_loop->num, access_fn,
3233 &init_expr, &step_expr);
3235 pe = loop_preheader_edge (iv_loop);
3237 vectype = get_vectype_for_scalar_type (TREE_TYPE (init_expr));
3238 resvectype = get_vectype_for_scalar_type (TREE_TYPE (PHI_RESULT (iv_phi)));
3239 gcc_assert (vectype);
3240 nunits = TYPE_VECTOR_SUBPARTS (vectype);
3241 ncopies = vf / nunits;
3243 gcc_assert (phi_info);
3244 gcc_assert (ncopies >= 1);
3246 /* Find the first insertion point in the BB. */
3247 si = gsi_after_labels (bb);
3249 /* Create the vector that holds the initial_value of the induction. */
3250 if (nested_in_vect_loop)
3252 /* iv_loop is nested in the loop to be vectorized. init_expr had already
3253 been created during vectorization of previous stmts. We obtain it
3254 from the STMT_VINFO_VEC_STMT of the defining stmt. */
3255 tree iv_def = PHI_ARG_DEF_FROM_EDGE (iv_phi,
3256 loop_preheader_edge (iv_loop));
3257 vec_init = vect_get_vec_def_for_operand (iv_def, iv_phi, NULL);
3258 /* If the initial value is not of proper type, convert it. */
3259 if (!useless_type_conversion_p (vectype, TREE_TYPE (vec_init)))
3261 new_stmt = gimple_build_assign_with_ops
3263 vect_get_new_vect_var (vectype, vect_simple_var, "vec_iv_"),
3264 build1 (VIEW_CONVERT_EXPR, vectype, vec_init), NULL_TREE);
3265 vec_init = make_ssa_name (gimple_assign_lhs (new_stmt), new_stmt);
3266 gimple_assign_set_lhs (new_stmt, vec_init);
3267 new_bb = gsi_insert_on_edge_immediate (loop_preheader_edge (iv_loop),
3269 gcc_assert (!new_bb);
3270 set_vinfo_for_stmt (new_stmt,
3271 new_stmt_vec_info (new_stmt, loop_vinfo, NULL));
3276 vec<constructor_elt, va_gc> *v;
3278 /* iv_loop is the loop to be vectorized. Create:
3279 vec_init = [X, X+S, X+2*S, X+3*S] (S = step_expr, X = init_expr) */
3280 new_var = vect_get_new_vect_var (TREE_TYPE (vectype),
3281 vect_scalar_var, "var_");
3282 new_name = force_gimple_operand (fold_convert (TREE_TYPE (vectype),
3284 &stmts, false, new_var);
3287 new_bb = gsi_insert_seq_on_edge_immediate (pe, stmts);
3288 gcc_assert (!new_bb);
3291 vec_alloc (v, nunits);
3292 bool constant_p = is_gimple_min_invariant (new_name);
3293 CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, new_name);
3294 for (i = 1; i < nunits; i++)
3296 /* Create: new_name_i = new_name + step_expr */
3297 new_name = fold_build2 (PLUS_EXPR, TREE_TYPE (new_name),
3298 new_name, step_expr);
3299 if (!is_gimple_min_invariant (new_name))
3301 init_stmt = gimple_build_assign (new_var, new_name);
3302 new_name = make_ssa_name (new_var, init_stmt);
3303 gimple_assign_set_lhs (init_stmt, new_name);
3304 new_bb = gsi_insert_on_edge_immediate (pe, init_stmt);
3305 gcc_assert (!new_bb);
3306 if (dump_enabled_p ())
3308 dump_printf_loc (MSG_NOTE, vect_location,
3309 "created new init_stmt: ");
3310 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, init_stmt, 0);
3311 dump_printf (MSG_NOTE, "\n");
3315 CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, new_name);
3317 /* Create a vector from [new_name_0, new_name_1, ..., new_name_nunits-1] */
3319 new_vec = build_vector_from_ctor (vectype, v);
3321 new_vec = build_constructor (vectype, v);
3322 vec_init = vect_init_vector (iv_phi, new_vec, vectype, NULL);
3326 /* Create the vector that holds the step of the induction. */
3327 if (nested_in_vect_loop)
3328 /* iv_loop is nested in the loop to be vectorized. Generate:
3329 vec_step = [S, S, S, S] */
3330 new_name = step_expr;
3333 /* iv_loop is the loop to be vectorized. Generate:
3334 vec_step = [VF*S, VF*S, VF*S, VF*S] */
3335 if (SCALAR_FLOAT_TYPE_P (TREE_TYPE (step_expr)))
3337 expr = build_int_cst (integer_type_node, vf);
3338 expr = fold_convert (TREE_TYPE (step_expr), expr);
3341 expr = build_int_cst (TREE_TYPE (step_expr), vf);
3342 new_name = fold_build2 (MULT_EXPR, TREE_TYPE (step_expr),
3344 if (TREE_CODE (step_expr) == SSA_NAME)
3345 new_name = vect_init_vector (iv_phi, new_name,
3346 TREE_TYPE (step_expr), NULL);
3349 t = unshare_expr (new_name);
3350 gcc_assert (CONSTANT_CLASS_P (new_name)
3351 || TREE_CODE (new_name) == SSA_NAME);
3352 stepvectype = get_vectype_for_scalar_type (TREE_TYPE (new_name));
3353 gcc_assert (stepvectype);
3354 new_vec = build_vector_from_val (stepvectype, t);
3355 vec_step = vect_init_vector (iv_phi, new_vec, stepvectype, NULL);
3358 /* Create the following def-use cycle:
3363 vec_iv = PHI <vec_init, vec_loop>
3367 vec_loop = vec_iv + vec_step; */
3369 /* Create the induction-phi that defines the induction-operand. */
3370 vec_dest = vect_get_new_vect_var (vectype, vect_simple_var, "vec_iv_");
3371 induction_phi = create_phi_node (vec_dest, iv_loop->header);
3372 set_vinfo_for_stmt (induction_phi,
3373 new_stmt_vec_info (induction_phi, loop_vinfo, NULL));
3374 induc_def = PHI_RESULT (induction_phi);
3376 /* Create the iv update inside the loop */
3377 new_stmt = gimple_build_assign_with_ops (PLUS_EXPR, vec_dest,
3378 induc_def, vec_step);
3379 vec_def = make_ssa_name (vec_dest, new_stmt);
3380 gimple_assign_set_lhs (new_stmt, vec_def);
3381 gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
3382 set_vinfo_for_stmt (new_stmt, new_stmt_vec_info (new_stmt, loop_vinfo,
3385 /* Set the arguments of the phi node: */
3386 add_phi_arg (induction_phi, vec_init, pe, UNKNOWN_LOCATION);
3387 add_phi_arg (induction_phi, vec_def, loop_latch_edge (iv_loop),
3391 /* In case that vectorization factor (VF) is bigger than the number
3392 of elements that we can fit in a vectype (nunits), we have to generate
3393 more than one vector stmt - i.e - we need to "unroll" the
3394 vector stmt by a factor VF/nunits. For more details see documentation
3395 in vectorizable_operation. */
3399 stmt_vec_info prev_stmt_vinfo;
3400 /* FORNOW. This restriction should be relaxed. */
3401 gcc_assert (!nested_in_vect_loop);
3403 /* Create the vector that holds the step of the induction. */
3404 if (SCALAR_FLOAT_TYPE_P (TREE_TYPE (step_expr)))
3406 expr = build_int_cst (integer_type_node, nunits);
3407 expr = fold_convert (TREE_TYPE (step_expr), expr);
3410 expr = build_int_cst (TREE_TYPE (step_expr), nunits);
3411 new_name = fold_build2 (MULT_EXPR, TREE_TYPE (step_expr),
3413 if (TREE_CODE (step_expr) == SSA_NAME)
3414 new_name = vect_init_vector (iv_phi, new_name,
3415 TREE_TYPE (step_expr), NULL);
3416 t = unshare_expr (new_name);
3417 gcc_assert (CONSTANT_CLASS_P (new_name)
3418 || TREE_CODE (new_name) == SSA_NAME);
3419 new_vec = build_vector_from_val (stepvectype, t);
3420 vec_step = vect_init_vector (iv_phi, new_vec, stepvectype, NULL);
3422 vec_def = induc_def;
3423 prev_stmt_vinfo = vinfo_for_stmt (induction_phi);
3424 for (i = 1; i < ncopies; i++)
3426 /* vec_i = vec_prev + vec_step */
3427 new_stmt = gimple_build_assign_with_ops (PLUS_EXPR, vec_dest,
3429 vec_def = make_ssa_name (vec_dest, new_stmt);
3430 gimple_assign_set_lhs (new_stmt, vec_def);
3432 gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
3433 if (!useless_type_conversion_p (resvectype, vectype))
3435 new_stmt = gimple_build_assign_with_ops
3437 vect_get_new_vect_var (resvectype, vect_simple_var,
3439 build1 (VIEW_CONVERT_EXPR, resvectype,
3440 gimple_assign_lhs (new_stmt)), NULL_TREE);
3441 gimple_assign_set_lhs (new_stmt,
3443 (gimple_assign_lhs (new_stmt), new_stmt));
3444 gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
3446 set_vinfo_for_stmt (new_stmt,
3447 new_stmt_vec_info (new_stmt, loop_vinfo, NULL));
3448 STMT_VINFO_RELATED_STMT (prev_stmt_vinfo) = new_stmt;
3449 prev_stmt_vinfo = vinfo_for_stmt (new_stmt);
3453 if (nested_in_vect_loop)
3455 /* Find the loop-closed exit-phi of the induction, and record
3456 the final vector of induction results: */
3458 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, loop_arg)
3460 if (!flow_bb_inside_loop_p (iv_loop, gimple_bb (USE_STMT (use_p))))
3462 exit_phi = USE_STMT (use_p);
3468 stmt_vec_info stmt_vinfo = vinfo_for_stmt (exit_phi);
3469 /* FORNOW. Currently not supporting the case that an inner-loop induction
3470 is not used in the outer-loop (i.e. only outside the outer-loop). */
3471 gcc_assert (STMT_VINFO_RELEVANT_P (stmt_vinfo)
3472 && !STMT_VINFO_LIVE_P (stmt_vinfo));
3474 STMT_VINFO_VEC_STMT (stmt_vinfo) = new_stmt;
3475 if (dump_enabled_p ())
3477 dump_printf_loc (MSG_NOTE, vect_location,
3478 "vector of inductions after inner-loop:");
3479 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, new_stmt, 0);
3480 dump_printf (MSG_NOTE, "\n");
3486 if (dump_enabled_p ())
3488 dump_printf_loc (MSG_NOTE, vect_location,
3489 "transform induction: created def-use cycle: ");
3490 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, induction_phi, 0);
3491 dump_printf (MSG_NOTE, "\n");
3492 dump_gimple_stmt (MSG_NOTE, TDF_SLIM,
3493 SSA_NAME_DEF_STMT (vec_def), 0);
3494 dump_printf (MSG_NOTE, "\n");
3497 STMT_VINFO_VEC_STMT (phi_info) = induction_phi;
3498 if (!useless_type_conversion_p (resvectype, vectype))
3500 new_stmt = gimple_build_assign_with_ops
3502 vect_get_new_vect_var (resvectype, vect_simple_var, "vec_iv_"),
3503 build1 (VIEW_CONVERT_EXPR, resvectype, induc_def), NULL_TREE);
3504 induc_def = make_ssa_name (gimple_assign_lhs (new_stmt), new_stmt);
3505 gimple_assign_set_lhs (new_stmt, induc_def);
3506 si = gsi_after_labels (bb);
3507 gsi_insert_before (&si, new_stmt, GSI_SAME_STMT);
3508 set_vinfo_for_stmt (new_stmt,
3509 new_stmt_vec_info (new_stmt, loop_vinfo, NULL));
3510 STMT_VINFO_RELATED_STMT (vinfo_for_stmt (new_stmt))
3511 = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (induction_phi));
3518 /* Function get_initial_def_for_reduction
3521 STMT - a stmt that performs a reduction operation in the loop.
3522 INIT_VAL - the initial value of the reduction variable
3525 ADJUSTMENT_DEF - a tree that holds a value to be added to the final result
3526 of the reduction (used for adjusting the epilog - see below).
3527 Return a vector variable, initialized according to the operation that STMT
3528 performs. This vector will be used as the initial value of the
3529 vector of partial results.
3531 Option1 (adjust in epilog): Initialize the vector as follows:
3532 add/bit or/xor: [0,0,...,0,0]
3533 mult/bit and: [1,1,...,1,1]
3534 min/max/cond_expr: [init_val,init_val,..,init_val,init_val]
3535 and when necessary (e.g. add/mult case) let the caller know
3536 that it needs to adjust the result by init_val.
3538 Option2: Initialize the vector as follows:
3539 add/bit or/xor: [init_val,0,0,...,0]
3540 mult/bit and: [init_val,1,1,...,1]
3541 min/max/cond_expr: [init_val,init_val,...,init_val]
3542 and no adjustments are needed.
3544 For example, for the following code:
3550 STMT is 's = s + a[i]', and the reduction variable is 's'.
3551 For a vector of 4 units, we want to return either [0,0,0,init_val],
3552 or [0,0,0,0] and let the caller know that it needs to adjust
3553 the result at the end by 'init_val'.
3555 FORNOW, we are using the 'adjust in epilog' scheme, because this way the
3556 initialization vector is simpler (same element in all entries), if
3557 ADJUSTMENT_DEF is not NULL, and Option2 otherwise.
3559 A cost model should help decide between these two schemes. */
3562 get_initial_def_for_reduction (gimple stmt, tree init_val,
3563 tree *adjustment_def)
3565 stmt_vec_info stmt_vinfo = vinfo_for_stmt (stmt);
3566 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_vinfo);
3567 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
3568 tree scalar_type = TREE_TYPE (init_val);
3569 tree vectype = get_vectype_for_scalar_type (scalar_type);
3571 enum tree_code code = gimple_assign_rhs_code (stmt);
3576 bool nested_in_vect_loop = false;
3578 REAL_VALUE_TYPE real_init_val = dconst0;
3579 int int_init_val = 0;
3580 gimple def_stmt = NULL;
3582 gcc_assert (vectype);
3583 nunits = TYPE_VECTOR_SUBPARTS (vectype);
3585 gcc_assert (POINTER_TYPE_P (scalar_type) || INTEGRAL_TYPE_P (scalar_type)
3586 || SCALAR_FLOAT_TYPE_P (scalar_type));
3588 if (nested_in_vect_loop_p (loop, stmt))
3589 nested_in_vect_loop = true;
3591 gcc_assert (loop == (gimple_bb (stmt))->loop_father);
3593 /* In case of double reduction we only create a vector variable to be put
3594 in the reduction phi node. The actual statement creation is done in
3595 vect_create_epilog_for_reduction. */
3596 if (adjustment_def && nested_in_vect_loop
3597 && TREE_CODE (init_val) == SSA_NAME
3598 && (def_stmt = SSA_NAME_DEF_STMT (init_val))
3599 && gimple_code (def_stmt) == GIMPLE_PHI
3600 && flow_bb_inside_loop_p (loop, gimple_bb (def_stmt))
3601 && vinfo_for_stmt (def_stmt)
3602 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt))
3603 == vect_double_reduction_def)
3605 *adjustment_def = NULL;
3606 return vect_create_destination_var (init_val, vectype);
3609 if (TREE_CONSTANT (init_val))
3611 if (SCALAR_FLOAT_TYPE_P (scalar_type))
3612 init_value = build_real (scalar_type, TREE_REAL_CST (init_val));
3614 init_value = build_int_cst (scalar_type, TREE_INT_CST_LOW (init_val));
3617 init_value = init_val;
3621 case WIDEN_SUM_EXPR:
3629 /* ADJUSMENT_DEF is NULL when called from
3630 vect_create_epilog_for_reduction to vectorize double reduction. */
3633 if (nested_in_vect_loop)
3634 *adjustment_def = vect_get_vec_def_for_operand (init_val, stmt,
3637 *adjustment_def = init_val;
3640 if (code == MULT_EXPR)
3642 real_init_val = dconst1;
3646 if (code == BIT_AND_EXPR)
3649 if (SCALAR_FLOAT_TYPE_P (scalar_type))
3650 def_for_init = build_real (scalar_type, real_init_val);
3652 def_for_init = build_int_cst (scalar_type, int_init_val);
3654 /* Create a vector of '0' or '1' except the first element. */
3655 elts = XALLOCAVEC (tree, nunits);
3656 for (i = nunits - 2; i >= 0; --i)
3657 elts[i + 1] = def_for_init;
3659 /* Option1: the first element is '0' or '1' as well. */
3662 elts[0] = def_for_init;
3663 init_def = build_vector (vectype, elts);
3667 /* Option2: the first element is INIT_VAL. */
3669 if (TREE_CONSTANT (init_val))
3670 init_def = build_vector (vectype, elts);
3673 vec<constructor_elt, va_gc> *v;
3674 vec_alloc (v, nunits);
3675 CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, init_val);
3676 for (i = 1; i < nunits; ++i)
3677 CONSTRUCTOR_APPEND_ELT (v, NULL_TREE, elts[i]);
3678 init_def = build_constructor (vectype, v);
3688 *adjustment_def = NULL_TREE;
3689 init_def = vect_get_vec_def_for_operand (init_val, stmt, NULL);
3693 init_def = build_vector_from_val (vectype, init_value);
3704 /* Function vect_create_epilog_for_reduction
3706 Create code at the loop-epilog to finalize the result of a reduction
3709 VECT_DEFS is list of vector of partial results, i.e., the lhs's of vector
3710 reduction statements.
3711 STMT is the scalar reduction stmt that is being vectorized.
3712 NCOPIES is > 1 in case the vectorization factor (VF) is bigger than the
3713 number of elements that we can fit in a vectype (nunits). In this case
3714 we have to generate more than one vector stmt - i.e - we need to "unroll"
3715 the vector stmt by a factor VF/nunits. For more details see documentation
3716 in vectorizable_operation.
3717 REDUC_CODE is the tree-code for the epilog reduction.
3718 REDUCTION_PHIS is a list of the phi-nodes that carry the reduction
3720 REDUC_INDEX is the index of the operand in the right hand side of the
3721 statement that is defined by REDUCTION_PHI.
3722 DOUBLE_REDUC is TRUE if double reduction phi nodes should be handled.
3723 SLP_NODE is an SLP node containing a group of reduction statements. The
3724 first one in this group is STMT.
3727 1. Creates the reduction def-use cycles: sets the arguments for
3729 The loop-entry argument is the vectorized initial-value of the reduction.
3730 The loop-latch argument is taken from VECT_DEFS - the vector of partial
3732 2. "Reduces" each vector of partial results VECT_DEFS into a single result,
3733 by applying the operation specified by REDUC_CODE if available, or by
3734 other means (whole-vector shifts or a scalar loop).
3735 The function also creates a new phi node at the loop exit to preserve
3736 loop-closed form, as illustrated below.
3738 The flow at the entry to this function:
3741 vec_def = phi <null, null> # REDUCTION_PHI
3742 VECT_DEF = vector_stmt # vectorized form of STMT
3743 s_loop = scalar_stmt # (scalar) STMT
3745 s_out0 = phi <s_loop> # (scalar) EXIT_PHI
3749 The above is transformed by this function into:
3752 vec_def = phi <vec_init, VECT_DEF> # REDUCTION_PHI
3753 VECT_DEF = vector_stmt # vectorized form of STMT
3754 s_loop = scalar_stmt # (scalar) STMT
3756 s_out0 = phi <s_loop> # (scalar) EXIT_PHI
3757 v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
3758 v_out2 = reduce <v_out1>
3759 s_out3 = extract_field <v_out2, 0>
3760 s_out4 = adjust_result <s_out3>
3766 vect_create_epilog_for_reduction (vec<tree> vect_defs, gimple stmt,
3767 int ncopies, enum tree_code reduc_code,
3768 vec<gimple> reduction_phis,
3769 int reduc_index, bool double_reduc,
3772 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
3773 stmt_vec_info prev_phi_info;
3775 enum machine_mode mode;
3776 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
3777 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo), *outer_loop = NULL;
3778 basic_block exit_bb;
3781 gimple new_phi = NULL, phi;
3782 gimple_stmt_iterator exit_gsi;
3784 tree new_temp = NULL_TREE, new_dest, new_name, new_scalar_dest;
3785 gimple epilog_stmt = NULL;
3786 enum tree_code code = gimple_assign_rhs_code (stmt);
3788 tree bitsize, bitpos;
3789 tree adjustment_def = NULL;
3790 tree vec_initial_def = NULL;
3791 tree reduction_op, expr, def;
3792 tree orig_name, scalar_result;
3793 imm_use_iterator imm_iter, phi_imm_iter;
3794 use_operand_p use_p, phi_use_p;
3795 bool extract_scalar_result = false;
3796 gimple use_stmt, orig_stmt, reduction_phi = NULL;
3797 bool nested_in_vect_loop = false;
3798 vec<gimple> new_phis = vNULL;
3799 vec<gimple> inner_phis = vNULL;
3800 enum vect_def_type dt = vect_unknown_def_type;
3802 vec<tree> scalar_results = vNULL;
3803 unsigned int group_size = 1, k, ratio;
3804 vec<tree> vec_initial_defs = vNULL;
3806 bool slp_reduc = false;
3807 tree new_phi_result;
3808 gimple inner_phi = NULL;
3811 group_size = SLP_TREE_SCALAR_STMTS (slp_node).length ();
3813 if (nested_in_vect_loop_p (loop, stmt))
3817 nested_in_vect_loop = true;
3818 gcc_assert (!slp_node);
3821 switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt)))
3823 case GIMPLE_SINGLE_RHS:
3824 gcc_assert (TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt))
3826 reduction_op = TREE_OPERAND (gimple_assign_rhs1 (stmt), reduc_index);
3828 case GIMPLE_UNARY_RHS:
3829 reduction_op = gimple_assign_rhs1 (stmt);
3831 case GIMPLE_BINARY_RHS:
3832 reduction_op = reduc_index ?
3833 gimple_assign_rhs2 (stmt) : gimple_assign_rhs1 (stmt);
3835 case GIMPLE_TERNARY_RHS:
3836 reduction_op = gimple_op (stmt, reduc_index + 1);
3842 vectype = get_vectype_for_scalar_type (TREE_TYPE (reduction_op));
3843 gcc_assert (vectype);
3844 mode = TYPE_MODE (vectype);
3846 /* 1. Create the reduction def-use cycle:
3847 Set the arguments of REDUCTION_PHIS, i.e., transform
3850 vec_def = phi <null, null> # REDUCTION_PHI
3851 VECT_DEF = vector_stmt # vectorized form of STMT
3857 vec_def = phi <vec_init, VECT_DEF> # REDUCTION_PHI
3858 VECT_DEF = vector_stmt # vectorized form of STMT
3861 (in case of SLP, do it for all the phis). */
3863 /* Get the loop-entry arguments. */
3865 vect_get_vec_defs (reduction_op, NULL_TREE, stmt, &vec_initial_defs,
3866 NULL, slp_node, reduc_index);
3869 vec_initial_defs.create (1);
3870 /* For the case of reduction, vect_get_vec_def_for_operand returns
3871 the scalar def before the loop, that defines the initial value
3872 of the reduction variable. */
3873 vec_initial_def = vect_get_vec_def_for_operand (reduction_op, stmt,
3875 vec_initial_defs.quick_push (vec_initial_def);
3878 /* Set phi nodes arguments. */
3879 FOR_EACH_VEC_ELT (reduction_phis, i, phi)
3881 tree vec_init_def = vec_initial_defs[i];
3882 tree def = vect_defs[i];
3883 for (j = 0; j < ncopies; j++)
3885 /* Set the loop-entry arg of the reduction-phi. */
3886 add_phi_arg (phi, vec_init_def, loop_preheader_edge (loop),
3889 /* Set the loop-latch arg for the reduction-phi. */
3891 def = vect_get_vec_def_for_stmt_copy (vect_unknown_def_type, def);
3893 add_phi_arg (phi, def, loop_latch_edge (loop), UNKNOWN_LOCATION);
3895 if (dump_enabled_p ())
3897 dump_printf_loc (MSG_NOTE, vect_location,
3898 "transform reduction: created def-use cycle: ");
3899 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0);
3900 dump_printf (MSG_NOTE, "\n");
3901 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, SSA_NAME_DEF_STMT (def), 0);
3902 dump_printf (MSG_NOTE, "\n");
3905 phi = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi));
3909 vec_initial_defs.release ();
3911 /* 2. Create epilog code.
3912 The reduction epilog code operates across the elements of the vector
3913 of partial results computed by the vectorized loop.
3914 The reduction epilog code consists of:
3916 step 1: compute the scalar result in a vector (v_out2)
3917 step 2: extract the scalar result (s_out3) from the vector (v_out2)
3918 step 3: adjust the scalar result (s_out3) if needed.
3920 Step 1 can be accomplished using one the following three schemes:
3921 (scheme 1) using reduc_code, if available.
3922 (scheme 2) using whole-vector shifts, if available.
3923 (scheme 3) using a scalar loop. In this case steps 1+2 above are
3926 The overall epilog code looks like this:
3928 s_out0 = phi <s_loop> # original EXIT_PHI
3929 v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
3930 v_out2 = reduce <v_out1> # step 1
3931 s_out3 = extract_field <v_out2, 0> # step 2
3932 s_out4 = adjust_result <s_out3> # step 3
3934 (step 3 is optional, and steps 1 and 2 may be combined).
3935 Lastly, the uses of s_out0 are replaced by s_out4. */
3938 /* 2.1 Create new loop-exit-phis to preserve loop-closed form:
3939 v_out1 = phi <VECT_DEF>
3940 Store them in NEW_PHIS. */
3942 exit_bb = single_exit (loop)->dest;
3943 prev_phi_info = NULL;
3944 new_phis.create (vect_defs.length ());
3945 FOR_EACH_VEC_ELT (vect_defs, i, def)
3947 for (j = 0; j < ncopies; j++)
3949 tree new_def = copy_ssa_name (def, NULL);
3950 phi = create_phi_node (new_def, exit_bb);
3951 set_vinfo_for_stmt (phi, new_stmt_vec_info (phi, loop_vinfo, NULL));
3953 new_phis.quick_push (phi);
3956 def = vect_get_vec_def_for_stmt_copy (dt, def);
3957 STMT_VINFO_RELATED_STMT (prev_phi_info) = phi;
3960 SET_PHI_ARG_DEF (phi, single_exit (loop)->dest_idx, def);
3961 prev_phi_info = vinfo_for_stmt (phi);
3965 /* The epilogue is created for the outer-loop, i.e., for the loop being
3966 vectorized. Create exit phis for the outer loop. */
3970 exit_bb = single_exit (loop)->dest;
3971 inner_phis.create (vect_defs.length ());
3972 FOR_EACH_VEC_ELT (new_phis, i, phi)
3974 tree new_result = copy_ssa_name (PHI_RESULT (phi), NULL);
3975 gimple outer_phi = create_phi_node (new_result, exit_bb);
3976 SET_PHI_ARG_DEF (outer_phi, single_exit (loop)->dest_idx,
3978 set_vinfo_for_stmt (outer_phi, new_stmt_vec_info (outer_phi,
3980 inner_phis.quick_push (phi);
3981 new_phis[i] = outer_phi;
3982 prev_phi_info = vinfo_for_stmt (outer_phi);
3983 while (STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi)))
3985 phi = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi));
3986 new_result = copy_ssa_name (PHI_RESULT (phi), NULL);
3987 outer_phi = create_phi_node (new_result, exit_bb);
3988 SET_PHI_ARG_DEF (outer_phi, single_exit (loop)->dest_idx,
3990 set_vinfo_for_stmt (outer_phi, new_stmt_vec_info (outer_phi,
3992 STMT_VINFO_RELATED_STMT (prev_phi_info) = outer_phi;
3993 prev_phi_info = vinfo_for_stmt (outer_phi);
3998 exit_gsi = gsi_after_labels (exit_bb);
4000 /* 2.2 Get the relevant tree-code to use in the epilog for schemes 2,3
4001 (i.e. when reduc_code is not available) and in the final adjustment
4002 code (if needed). Also get the original scalar reduction variable as
4003 defined in the loop. In case STMT is a "pattern-stmt" (i.e. - it
4004 represents a reduction pattern), the tree-code and scalar-def are
4005 taken from the original stmt that the pattern-stmt (STMT) replaces.
4006 Otherwise (it is a regular reduction) - the tree-code and scalar-def
4007 are taken from STMT. */
4009 orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);
4012 /* Regular reduction */
4017 /* Reduction pattern */
4018 stmt_vec_info stmt_vinfo = vinfo_for_stmt (orig_stmt);
4019 gcc_assert (STMT_VINFO_IN_PATTERN_P (stmt_vinfo));
4020 gcc_assert (STMT_VINFO_RELATED_STMT (stmt_vinfo) == stmt);
4023 code = gimple_assign_rhs_code (orig_stmt);
4024 /* For MINUS_EXPR the initial vector is [init_val,0,...,0], therefore,
4025 partial results are added and not subtracted. */
4026 if (code == MINUS_EXPR)
4029 scalar_dest = gimple_assign_lhs (orig_stmt);
4030 scalar_type = TREE_TYPE (scalar_dest);
4031 scalar_results.create (group_size);
4032 new_scalar_dest = vect_create_destination_var (scalar_dest, NULL);
4033 bitsize = TYPE_SIZE (scalar_type);
4035 /* In case this is a reduction in an inner-loop while vectorizing an outer
4036 loop - we don't need to extract a single scalar result at the end of the
4037 inner-loop (unless it is double reduction, i.e., the use of reduction is
4038 outside the outer-loop). The final vector of partial results will be used
4039 in the vectorized outer-loop, or reduced to a scalar result at the end of
4041 if (nested_in_vect_loop && !double_reduc)
4042 goto vect_finalize_reduction;
4044 /* SLP reduction without reduction chain, e.g.,
4048 b2 = operation (b1) */
4049 slp_reduc = (slp_node && !GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)));
4051 /* In case of reduction chain, e.g.,
4054 a3 = operation (a2),
4056 we may end up with more than one vector result. Here we reduce them to
4058 if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)))
4060 tree first_vect = PHI_RESULT (new_phis[0]);
4062 gimple new_vec_stmt = NULL;
4064 vec_dest = vect_create_destination_var (scalar_dest, vectype);
4065 for (k = 1; k < new_phis.length (); k++)
4067 gimple next_phi = new_phis[k];
4068 tree second_vect = PHI_RESULT (next_phi);
4070 tmp = build2 (code, vectype, first_vect, second_vect);
4071 new_vec_stmt = gimple_build_assign (vec_dest, tmp);
4072 first_vect = make_ssa_name (vec_dest, new_vec_stmt);
4073 gimple_assign_set_lhs (new_vec_stmt, first_vect);
4074 gsi_insert_before (&exit_gsi, new_vec_stmt, GSI_SAME_STMT);
4077 new_phi_result = first_vect;
4080 new_phis.truncate (0);
4081 new_phis.safe_push (new_vec_stmt);
4085 new_phi_result = PHI_RESULT (new_phis[0]);
4087 /* 2.3 Create the reduction code, using one of the three schemes described
4088 above. In SLP we simply need to extract all the elements from the
4089 vector (without reducing them), so we use scalar shifts. */
4090 if (reduc_code != ERROR_MARK && !slp_reduc)
4094 /*** Case 1: Create:
4095 v_out2 = reduc_expr <v_out1> */
4097 if (dump_enabled_p ())
4098 dump_printf_loc (MSG_NOTE, vect_location,
4099 "Reduce using direct vector reduction.\n");
4101 vec_dest = vect_create_destination_var (scalar_dest, vectype);
4102 tmp = build1 (reduc_code, vectype, new_phi_result);
4103 epilog_stmt = gimple_build_assign (vec_dest, tmp);
4104 new_temp = make_ssa_name (vec_dest, epilog_stmt);
4105 gimple_assign_set_lhs (epilog_stmt, new_temp);
4106 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
4108 extract_scalar_result = true;
4112 enum tree_code shift_code = ERROR_MARK;
4113 bool have_whole_vector_shift = true;
4115 int element_bitsize = tree_low_cst (bitsize, 1);
4116 int vec_size_in_bits = tree_low_cst (TYPE_SIZE (vectype), 1);
4119 if (optab_handler (vec_shr_optab, mode) != CODE_FOR_nothing)
4120 shift_code = VEC_RSHIFT_EXPR;
4122 have_whole_vector_shift = false;
4124 /* Regardless of whether we have a whole vector shift, if we're
4125 emulating the operation via tree-vect-generic, we don't want
4126 to use it. Only the first round of the reduction is likely
4127 to still be profitable via emulation. */
4128 /* ??? It might be better to emit a reduction tree code here, so that
4129 tree-vect-generic can expand the first round via bit tricks. */
4130 if (!VECTOR_MODE_P (mode))
4131 have_whole_vector_shift = false;
4134 optab optab = optab_for_tree_code (code, vectype, optab_default);
4135 if (optab_handler (optab, mode) == CODE_FOR_nothing)
4136 have_whole_vector_shift = false;
4139 if (have_whole_vector_shift && !slp_reduc)
4141 /*** Case 2: Create:
4142 for (offset = VS/2; offset >= element_size; offset/=2)
4144 Create: va' = vec_shift <va, offset>
4145 Create: va = vop <va, va'>
4148 if (dump_enabled_p ())
4149 dump_printf_loc (MSG_NOTE, vect_location,
4150 "Reduce using vector shifts\n");
4152 vec_dest = vect_create_destination_var (scalar_dest, vectype);
4153 new_temp = new_phi_result;
4154 for (bit_offset = vec_size_in_bits/2;
4155 bit_offset >= element_bitsize;
4158 tree bitpos = size_int (bit_offset);
4160 epilog_stmt = gimple_build_assign_with_ops (shift_code,
4161 vec_dest, new_temp, bitpos);
4162 new_name = make_ssa_name (vec_dest, epilog_stmt);
4163 gimple_assign_set_lhs (epilog_stmt, new_name);
4164 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
4166 epilog_stmt = gimple_build_assign_with_ops (code, vec_dest,
4167 new_name, new_temp);
4168 new_temp = make_ssa_name (vec_dest, epilog_stmt);
4169 gimple_assign_set_lhs (epilog_stmt, new_temp);
4170 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
4173 extract_scalar_result = true;
4179 /*** Case 3: Create:
4180 s = extract_field <v_out2, 0>
4181 for (offset = element_size;
4182 offset < vector_size;
4183 offset += element_size;)
4185 Create: s' = extract_field <v_out2, offset>
4186 Create: s = op <s, s'> // For non SLP cases
4189 if (dump_enabled_p ())
4190 dump_printf_loc (MSG_NOTE, vect_location,
4191 "Reduce using scalar code.\n");
4193 vec_size_in_bits = tree_low_cst (TYPE_SIZE (vectype), 1);
4194 FOR_EACH_VEC_ELT (new_phis, i, new_phi)
4196 if (gimple_code (new_phi) == GIMPLE_PHI)
4197 vec_temp = PHI_RESULT (new_phi);
4199 vec_temp = gimple_assign_lhs (new_phi);
4200 rhs = build3 (BIT_FIELD_REF, scalar_type, vec_temp, bitsize,
4202 epilog_stmt = gimple_build_assign (new_scalar_dest, rhs);
4203 new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
4204 gimple_assign_set_lhs (epilog_stmt, new_temp);
4205 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
4207 /* In SLP we don't need to apply reduction operation, so we just
4208 collect s' values in SCALAR_RESULTS. */
4210 scalar_results.safe_push (new_temp);
4212 for (bit_offset = element_bitsize;
4213 bit_offset < vec_size_in_bits;
4214 bit_offset += element_bitsize)
4216 tree bitpos = bitsize_int (bit_offset);
4217 tree rhs = build3 (BIT_FIELD_REF, scalar_type, vec_temp,
4220 epilog_stmt = gimple_build_assign (new_scalar_dest, rhs);
4221 new_name = make_ssa_name (new_scalar_dest, epilog_stmt);
4222 gimple_assign_set_lhs (epilog_stmt, new_name);
4223 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
4227 /* In SLP we don't need to apply reduction operation, so
4228 we just collect s' values in SCALAR_RESULTS. */
4229 new_temp = new_name;
4230 scalar_results.safe_push (new_name);
4234 epilog_stmt = gimple_build_assign_with_ops (code,
4235 new_scalar_dest, new_name, new_temp);
4236 new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
4237 gimple_assign_set_lhs (epilog_stmt, new_temp);
4238 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
4243 /* The only case where we need to reduce scalar results in SLP, is
4244 unrolling. If the size of SCALAR_RESULTS is greater than
4245 GROUP_SIZE, we reduce them combining elements modulo
4249 tree res, first_res, new_res;
4252 /* Reduce multiple scalar results in case of SLP unrolling. */
4253 for (j = group_size; scalar_results.iterate (j, &res);
4256 first_res = scalar_results[j % group_size];
4257 new_stmt = gimple_build_assign_with_ops (code,
4258 new_scalar_dest, first_res, res);
4259 new_res = make_ssa_name (new_scalar_dest, new_stmt);
4260 gimple_assign_set_lhs (new_stmt, new_res);
4261 gsi_insert_before (&exit_gsi, new_stmt, GSI_SAME_STMT);
4262 scalar_results[j % group_size] = new_res;
4266 /* Not SLP - we have one scalar to keep in SCALAR_RESULTS. */
4267 scalar_results.safe_push (new_temp);
4269 extract_scalar_result = false;
4273 /* 2.4 Extract the final scalar result. Create:
4274 s_out3 = extract_field <v_out2, bitpos> */
4276 if (extract_scalar_result)
4280 if (dump_enabled_p ())
4281 dump_printf_loc (MSG_NOTE, vect_location,
4282 "extract scalar result\n");
4284 if (BYTES_BIG_ENDIAN)
4285 bitpos = size_binop (MULT_EXPR,
4286 bitsize_int (TYPE_VECTOR_SUBPARTS (vectype) - 1),
4287 TYPE_SIZE (scalar_type));
4289 bitpos = bitsize_zero_node;
4291 rhs = build3 (BIT_FIELD_REF, scalar_type, new_temp, bitsize, bitpos);
4292 epilog_stmt = gimple_build_assign (new_scalar_dest, rhs);
4293 new_temp = make_ssa_name (new_scalar_dest, epilog_stmt);
4294 gimple_assign_set_lhs (epilog_stmt, new_temp);
4295 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
4296 scalar_results.safe_push (new_temp);
4299 vect_finalize_reduction:
4304 /* 2.5 Adjust the final result by the initial value of the reduction
4305 variable. (When such adjustment is not needed, then
4306 'adjustment_def' is zero). For example, if code is PLUS we create:
4307 new_temp = loop_exit_def + adjustment_def */
4311 gcc_assert (!slp_reduc);
4312 if (nested_in_vect_loop)
4314 new_phi = new_phis[0];
4315 gcc_assert (TREE_CODE (TREE_TYPE (adjustment_def)) == VECTOR_TYPE);
4316 expr = build2 (code, vectype, PHI_RESULT (new_phi), adjustment_def);
4317 new_dest = vect_create_destination_var (scalar_dest, vectype);
4321 new_temp = scalar_results[0];
4322 gcc_assert (TREE_CODE (TREE_TYPE (adjustment_def)) != VECTOR_TYPE);
4323 expr = build2 (code, scalar_type, new_temp, adjustment_def);
4324 new_dest = vect_create_destination_var (scalar_dest, scalar_type);
4327 epilog_stmt = gimple_build_assign (new_dest, expr);
4328 new_temp = make_ssa_name (new_dest, epilog_stmt);
4329 gimple_assign_set_lhs (epilog_stmt, new_temp);
4330 SSA_NAME_DEF_STMT (new_temp) = epilog_stmt;
4331 gsi_insert_before (&exit_gsi, epilog_stmt, GSI_SAME_STMT);
4332 if (nested_in_vect_loop)
4334 set_vinfo_for_stmt (epilog_stmt,
4335 new_stmt_vec_info (epilog_stmt, loop_vinfo,
4337 STMT_VINFO_RELATED_STMT (vinfo_for_stmt (epilog_stmt)) =
4338 STMT_VINFO_RELATED_STMT (vinfo_for_stmt (new_phi));
4341 scalar_results.quick_push (new_temp);
4343 scalar_results[0] = new_temp;
4346 scalar_results[0] = new_temp;
4348 new_phis[0] = epilog_stmt;
4351 /* 2.6 Handle the loop-exit phis. Replace the uses of scalar loop-exit
4352 phis with new adjusted scalar results, i.e., replace use <s_out0>
4357 s_out0 = phi <s_loop> # (scalar) EXIT_PHI
4358 v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
4359 v_out2 = reduce <v_out1>
4360 s_out3 = extract_field <v_out2, 0>
4361 s_out4 = adjust_result <s_out3>
4368 s_out0 = phi <s_loop> # (scalar) EXIT_PHI
4369 v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
4370 v_out2 = reduce <v_out1>
4371 s_out3 = extract_field <v_out2, 0>
4372 s_out4 = adjust_result <s_out3>
4377 /* In SLP reduction chain we reduce vector results into one vector if
4378 necessary, hence we set here GROUP_SIZE to 1. SCALAR_DEST is the LHS of
4379 the last stmt in the reduction chain, since we are looking for the loop
4381 if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)))
4383 scalar_dest = gimple_assign_lhs (
4384 SLP_TREE_SCALAR_STMTS (slp_node)[group_size - 1]);
4388 /* In SLP we may have several statements in NEW_PHIS and REDUCTION_PHIS (in
4389 case that GROUP_SIZE is greater than vectorization factor). Therefore, we
4390 need to match SCALAR_RESULTS with corresponding statements. The first
4391 (GROUP_SIZE / number of new vector stmts) scalar results correspond to
4392 the first vector stmt, etc.
4393 (RATIO is equal to (GROUP_SIZE / number of new vector stmts)). */
4394 if (group_size > new_phis.length ())
4396 ratio = group_size / new_phis.length ();
4397 gcc_assert (!(group_size % new_phis.length ()));
4402 for (k = 0; k < group_size; k++)
4406 epilog_stmt = new_phis[k / ratio];
4407 reduction_phi = reduction_phis[k / ratio];
4409 inner_phi = inner_phis[k / ratio];
4414 gimple current_stmt = SLP_TREE_SCALAR_STMTS (slp_node)[k];
4416 orig_stmt = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (current_stmt));
4417 /* SLP statements can't participate in patterns. */
4418 gcc_assert (!orig_stmt);
4419 scalar_dest = gimple_assign_lhs (current_stmt);
4423 /* Find the loop-closed-use at the loop exit of the original scalar
4424 result. (The reduction result is expected to have two immediate uses -
4425 one at the latch block, and one at the loop exit). */
4426 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, scalar_dest)
4427 if (!flow_bb_inside_loop_p (loop, gimple_bb (USE_STMT (use_p)))
4428 && !is_gimple_debug (USE_STMT (use_p)))
4429 phis.safe_push (USE_STMT (use_p));
4431 /* While we expect to have found an exit_phi because of loop-closed-ssa
4432 form we can end up without one if the scalar cycle is dead. */
4434 FOR_EACH_VEC_ELT (phis, i, exit_phi)
4438 stmt_vec_info exit_phi_vinfo = vinfo_for_stmt (exit_phi);
4441 /* FORNOW. Currently not supporting the case that an inner-loop
4442 reduction is not used in the outer-loop (but only outside the
4443 outer-loop), unless it is double reduction. */
4444 gcc_assert ((STMT_VINFO_RELEVANT_P (exit_phi_vinfo)
4445 && !STMT_VINFO_LIVE_P (exit_phi_vinfo))
4448 STMT_VINFO_VEC_STMT (exit_phi_vinfo) = epilog_stmt;
4450 || STMT_VINFO_DEF_TYPE (exit_phi_vinfo)
4451 != vect_double_reduction_def)
4454 /* Handle double reduction:
4456 stmt1: s1 = phi <s0, s2> - double reduction phi (outer loop)
4457 stmt2: s3 = phi <s1, s4> - (regular) reduc phi (inner loop)
4458 stmt3: s4 = use (s3) - (regular) reduc stmt (inner loop)
4459 stmt4: s2 = phi <s4> - double reduction stmt (outer loop)
4461 At that point the regular reduction (stmt2 and stmt3) is
4462 already vectorized, as well as the exit phi node, stmt4.
4463 Here we vectorize the phi node of double reduction, stmt1, and
4464 update all relevant statements. */
4466 /* Go through all the uses of s2 to find double reduction phi
4467 node, i.e., stmt1 above. */
4468 orig_name = PHI_RESULT (exit_phi);
4469 FOR_EACH_IMM_USE_STMT (use_stmt, imm_iter, orig_name)
4471 stmt_vec_info use_stmt_vinfo;
4472 stmt_vec_info new_phi_vinfo;
4473 tree vect_phi_init, preheader_arg, vect_phi_res, init_def;
4474 basic_block bb = gimple_bb (use_stmt);
4477 /* Check that USE_STMT is really double reduction phi
4479 if (gimple_code (use_stmt) != GIMPLE_PHI
4480 || gimple_phi_num_args (use_stmt) != 2
4481 || bb->loop_father != outer_loop)
4483 use_stmt_vinfo = vinfo_for_stmt (use_stmt);
4485 || STMT_VINFO_DEF_TYPE (use_stmt_vinfo)
4486 != vect_double_reduction_def)
4489 /* Create vector phi node for double reduction:
4490 vs1 = phi <vs0, vs2>
4491 vs1 was created previously in this function by a call to
4492 vect_get_vec_def_for_operand and is stored in
4494 vs2 is defined by INNER_PHI, the vectorized EXIT_PHI;
4495 vs0 is created here. */
4497 /* Create vector phi node. */
4498 vect_phi = create_phi_node (vec_initial_def, bb);
4499 new_phi_vinfo = new_stmt_vec_info (vect_phi,
4500 loop_vec_info_for_loop (outer_loop), NULL);
4501 set_vinfo_for_stmt (vect_phi, new_phi_vinfo);
4503 /* Create vs0 - initial def of the double reduction phi. */
4504 preheader_arg = PHI_ARG_DEF_FROM_EDGE (use_stmt,
4505 loop_preheader_edge (outer_loop));
4506 init_def = get_initial_def_for_reduction (stmt,
4507 preheader_arg, NULL);
4508 vect_phi_init = vect_init_vector (use_stmt, init_def,
4511 /* Update phi node arguments with vs0 and vs2. */
4512 add_phi_arg (vect_phi, vect_phi_init,
4513 loop_preheader_edge (outer_loop),
4515 add_phi_arg (vect_phi, PHI_RESULT (inner_phi),
4516 loop_latch_edge (outer_loop), UNKNOWN_LOCATION);
4517 if (dump_enabled_p ())
4519 dump_printf_loc (MSG_NOTE, vect_location,
4520 "created double reduction phi node: ");
4521 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, vect_phi, 0);
4522 dump_printf (MSG_NOTE, "\n");
4525 vect_phi_res = PHI_RESULT (vect_phi);
4527 /* Replace the use, i.e., set the correct vs1 in the regular
4528 reduction phi node. FORNOW, NCOPIES is always 1, so the
4529 loop is redundant. */
4530 use = reduction_phi;
4531 for (j = 0; j < ncopies; j++)
4533 edge pr_edge = loop_preheader_edge (loop);
4534 SET_PHI_ARG_DEF (use, pr_edge->dest_idx, vect_phi_res);
4535 use = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (use));
4542 if (nested_in_vect_loop)
4551 /* Find the loop-closed-use at the loop exit of the original scalar
4552 result. (The reduction result is expected to have two immediate uses,
4553 one at the latch block, and one at the loop exit). For double
4554 reductions we are looking for exit phis of the outer loop. */
4555 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, scalar_dest)
4557 if (!flow_bb_inside_loop_p (loop, gimple_bb (USE_STMT (use_p))))
4559 if (!is_gimple_debug (USE_STMT (use_p)))
4560 phis.safe_push (USE_STMT (use_p));
4564 if (double_reduc && gimple_code (USE_STMT (use_p)) == GIMPLE_PHI)
4566 tree phi_res = PHI_RESULT (USE_STMT (use_p));
4568 FOR_EACH_IMM_USE_FAST (phi_use_p, phi_imm_iter, phi_res)
4570 if (!flow_bb_inside_loop_p (loop,
4571 gimple_bb (USE_STMT (phi_use_p)))
4572 && !is_gimple_debug (USE_STMT (phi_use_p)))
4573 phis.safe_push (USE_STMT (phi_use_p));
4579 FOR_EACH_VEC_ELT (phis, i, exit_phi)
4581 /* Replace the uses: */
4582 orig_name = PHI_RESULT (exit_phi);
4583 scalar_result = scalar_results[k];
4584 FOR_EACH_IMM_USE_STMT (use_stmt, imm_iter, orig_name)
4585 FOR_EACH_IMM_USE_ON_STMT (use_p, imm_iter)
4586 SET_USE (use_p, scalar_result);
4592 scalar_results.release ();
4593 inner_phis.release ();
4594 new_phis.release ();
4598 /* Function vectorizable_reduction.
4600 Check if STMT performs a reduction operation that can be vectorized.
4601 If VEC_STMT is also passed, vectorize the STMT: create a vectorized
4602 stmt to replace it, put it in VEC_STMT, and insert it at GSI.
4603 Return FALSE if not a vectorizable STMT, TRUE otherwise.
4605 This function also handles reduction idioms (patterns) that have been
4606 recognized in advance during vect_pattern_recog. In this case, STMT may be
4608 X = pattern_expr (arg0, arg1, ..., X)
4609 and it's STMT_VINFO_RELATED_STMT points to the last stmt in the original
4610 sequence that had been detected and replaced by the pattern-stmt (STMT).
4612 In some cases of reduction patterns, the type of the reduction variable X is
4613 different than the type of the other arguments of STMT.
4614 In such cases, the vectype that is used when transforming STMT into a vector
4615 stmt is different than the vectype that is used to determine the
4616 vectorization factor, because it consists of a different number of elements
4617 than the actual number of elements that are being operated upon in parallel.
4619 For example, consider an accumulation of shorts into an int accumulator.
4620 On some targets it's possible to vectorize this pattern operating on 8
4621 shorts at a time (hence, the vectype for purposes of determining the
4622 vectorization factor should be V8HI); on the other hand, the vectype that
4623 is used to create the vector form is actually V4SI (the type of the result).
4625 Upon entry to this function, STMT_VINFO_VECTYPE records the vectype that
4626 indicates what is the actual level of parallelism (V8HI in the example), so
4627 that the right vectorization factor would be derived. This vectype
4628 corresponds to the type of arguments to the reduction stmt, and should *NOT*
4629 be used to create the vectorized stmt. The right vectype for the vectorized
4630 stmt is obtained from the type of the result X:
4631 get_vectype_for_scalar_type (TREE_TYPE (X))
4633 This means that, contrary to "regular" reductions (or "regular" stmts in
4634 general), the following equation:
4635 STMT_VINFO_VECTYPE == get_vectype_for_scalar_type (TREE_TYPE (X))
4636 does *NOT* necessarily hold for reduction patterns. */
4639 vectorizable_reduction (gimple stmt, gimple_stmt_iterator *gsi,
4640 gimple *vec_stmt, slp_tree slp_node)
4644 tree loop_vec_def0 = NULL_TREE, loop_vec_def1 = NULL_TREE;
4645 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
4646 tree vectype_out = STMT_VINFO_VECTYPE (stmt_info);
4647 tree vectype_in = NULL_TREE;
4648 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
4649 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
4650 enum tree_code code, orig_code, epilog_reduc_code;
4651 enum machine_mode vec_mode;
4653 optab optab, reduc_optab;
4654 tree new_temp = NULL_TREE;
4657 enum vect_def_type dt;
4658 gimple new_phi = NULL;
4662 stmt_vec_info orig_stmt_info;
4663 tree expr = NULL_TREE;
4667 stmt_vec_info prev_stmt_info, prev_phi_info;
4668 bool single_defuse_cycle = false;
4669 tree reduc_def = NULL_TREE;
4670 gimple new_stmt = NULL;
4673 bool nested_cycle = false, found_nested_cycle_def = false;
4674 gimple reduc_def_stmt = NULL;
4675 /* The default is that the reduction variable is the last in statement. */
4676 int reduc_index = 2;
4677 bool double_reduc = false, dummy;
4679 struct loop * def_stmt_loop, *outer_loop = NULL;
4681 gimple def_arg_stmt;
4682 vec<tree> vec_oprnds0 = vNULL;
4683 vec<tree> vec_oprnds1 = vNULL;
4684 vec<tree> vect_defs = vNULL;
4685 vec<gimple> phis = vNULL;
4687 tree def0, def1, tem, op0, op1 = NULL_TREE;
4689 /* In case of reduction chain we switch to the first stmt in the chain, but
4690 we don't update STMT_INFO, since only the last stmt is marked as reduction
4691 and has reduction properties. */
4692 if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt)))
4693 stmt = GROUP_FIRST_ELEMENT (stmt_info);
4695 if (nested_in_vect_loop_p (loop, stmt))
4699 nested_cycle = true;
4702 /* 1. Is vectorizable reduction? */
4703 /* Not supportable if the reduction variable is used in the loop, unless
4704 it's a reduction chain. */
4705 if (STMT_VINFO_RELEVANT (stmt_info) > vect_used_in_outer
4706 && !GROUP_FIRST_ELEMENT (stmt_info))
4709 /* Reductions that are not used even in an enclosing outer-loop,
4710 are expected to be "live" (used out of the loop). */
4711 if (STMT_VINFO_RELEVANT (stmt_info) == vect_unused_in_scope
4712 && !STMT_VINFO_LIVE_P (stmt_info))
4715 /* Make sure it was already recognized as a reduction computation. */
4716 if (STMT_VINFO_DEF_TYPE (stmt_info) != vect_reduction_def
4717 && STMT_VINFO_DEF_TYPE (stmt_info) != vect_nested_cycle)
4720 /* 2. Has this been recognized as a reduction pattern?
4722 Check if STMT represents a pattern that has been recognized
4723 in earlier analysis stages. For stmts that represent a pattern,
4724 the STMT_VINFO_RELATED_STMT field records the last stmt in
4725 the original sequence that constitutes the pattern. */
4727 orig_stmt = STMT_VINFO_RELATED_STMT (stmt_info);
4730 orig_stmt_info = vinfo_for_stmt (orig_stmt);
4731 gcc_assert (STMT_VINFO_IN_PATTERN_P (orig_stmt_info));
4732 gcc_assert (!STMT_VINFO_IN_PATTERN_P (stmt_info));
4735 /* 3. Check the operands of the operation. The first operands are defined
4736 inside the loop body. The last operand is the reduction variable,
4737 which is defined by the loop-header-phi. */
4739 gcc_assert (is_gimple_assign (stmt));
4742 switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt)))
4744 case GIMPLE_SINGLE_RHS:
4745 op_type = TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt));
4746 if (op_type == ternary_op)
4748 tree rhs = gimple_assign_rhs1 (stmt);
4749 ops[0] = TREE_OPERAND (rhs, 0);
4750 ops[1] = TREE_OPERAND (rhs, 1);
4751 ops[2] = TREE_OPERAND (rhs, 2);
4752 code = TREE_CODE (rhs);
4758 case GIMPLE_BINARY_RHS:
4759 code = gimple_assign_rhs_code (stmt);
4760 op_type = TREE_CODE_LENGTH (code);
4761 gcc_assert (op_type == binary_op);
4762 ops[0] = gimple_assign_rhs1 (stmt);
4763 ops[1] = gimple_assign_rhs2 (stmt);
4766 case GIMPLE_TERNARY_RHS:
4767 code = gimple_assign_rhs_code (stmt);
4768 op_type = TREE_CODE_LENGTH (code);
4769 gcc_assert (op_type == ternary_op);
4770 ops[0] = gimple_assign_rhs1 (stmt);
4771 ops[1] = gimple_assign_rhs2 (stmt);
4772 ops[2] = gimple_assign_rhs3 (stmt);
4775 case GIMPLE_UNARY_RHS:
4782 if (code == COND_EXPR && slp_node)
4785 scalar_dest = gimple_assign_lhs (stmt);
4786 scalar_type = TREE_TYPE (scalar_dest);
4787 if (!POINTER_TYPE_P (scalar_type) && !INTEGRAL_TYPE_P (scalar_type)
4788 && !SCALAR_FLOAT_TYPE_P (scalar_type))
4791 /* Do not try to vectorize bit-precision reductions. */
4792 if ((TYPE_PRECISION (scalar_type)
4793 != GET_MODE_PRECISION (TYPE_MODE (scalar_type))))
4796 /* All uses but the last are expected to be defined in the loop.
4797 The last use is the reduction variable. In case of nested cycle this
4798 assumption is not true: we use reduc_index to record the index of the
4799 reduction variable. */
4800 for (i = 0; i < op_type - 1; i++)
4802 /* The condition of COND_EXPR is checked in vectorizable_condition(). */
4803 if (i == 0 && code == COND_EXPR)
4806 is_simple_use = vect_is_simple_use_1 (ops[i], stmt, loop_vinfo, NULL,
4807 &def_stmt, &def, &dt, &tem);
4810 gcc_assert (is_simple_use);
4812 if (dt != vect_internal_def
4813 && dt != vect_external_def
4814 && dt != vect_constant_def
4815 && dt != vect_induction_def
4816 && !(dt == vect_nested_cycle && nested_cycle))
4819 if (dt == vect_nested_cycle)
4821 found_nested_cycle_def = true;
4822 reduc_def_stmt = def_stmt;
4827 is_simple_use = vect_is_simple_use_1 (ops[i], stmt, loop_vinfo, NULL,
4828 &def_stmt, &def, &dt, &tem);
4831 gcc_assert (is_simple_use);
4832 if (!(dt == vect_reduction_def
4833 || dt == vect_nested_cycle
4834 || ((dt == vect_internal_def || dt == vect_external_def
4835 || dt == vect_constant_def || dt == vect_induction_def)
4836 && nested_cycle && found_nested_cycle_def)))
4838 /* For pattern recognized stmts, orig_stmt might be a reduction,
4839 but some helper statements for the pattern might not, or
4840 might be COND_EXPRs with reduction uses in the condition. */
4841 gcc_assert (orig_stmt);
4844 if (!found_nested_cycle_def)
4845 reduc_def_stmt = def_stmt;
4847 gcc_assert (gimple_code (reduc_def_stmt) == GIMPLE_PHI);
4849 gcc_assert (orig_stmt == vect_is_simple_reduction (loop_vinfo,
4855 gimple tmp = vect_is_simple_reduction (loop_vinfo, reduc_def_stmt,
4856 !nested_cycle, &dummy);
4857 /* We changed STMT to be the first stmt in reduction chain, hence we
4858 check that in this case the first element in the chain is STMT. */
4859 gcc_assert (stmt == tmp
4860 || GROUP_FIRST_ELEMENT (vinfo_for_stmt (tmp)) == stmt);
4863 if (STMT_VINFO_LIVE_P (vinfo_for_stmt (reduc_def_stmt)))
4866 if (slp_node || PURE_SLP_STMT (stmt_info))
4869 ncopies = (LOOP_VINFO_VECT_FACTOR (loop_vinfo)
4870 / TYPE_VECTOR_SUBPARTS (vectype_in));
4872 gcc_assert (ncopies >= 1);
4874 vec_mode = TYPE_MODE (vectype_in);
4876 if (code == COND_EXPR)
4878 if (!vectorizable_condition (stmt, gsi, NULL, ops[reduc_index], 0, NULL))
4880 if (dump_enabled_p ())
4881 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
4882 "unsupported condition in reduction\n");
4889 /* 4. Supportable by target? */
4891 if (code == LSHIFT_EXPR || code == RSHIFT_EXPR
4892 || code == LROTATE_EXPR || code == RROTATE_EXPR)
4894 /* Shifts and rotates are only supported by vectorizable_shifts,
4895 not vectorizable_reduction. */
4896 if (dump_enabled_p ())
4897 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
4898 "unsupported shift or rotation.\n");
4902 /* 4.1. check support for the operation in the loop */
4903 optab = optab_for_tree_code (code, vectype_in, optab_default);
4906 if (dump_enabled_p ())
4907 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
4913 if (optab_handler (optab, vec_mode) == CODE_FOR_nothing)
4915 if (dump_enabled_p ())
4916 dump_printf (MSG_NOTE, "op not supported by target.\n");
4918 if (GET_MODE_SIZE (vec_mode) != UNITS_PER_WORD
4919 || LOOP_VINFO_VECT_FACTOR (loop_vinfo)
4920 < vect_min_worthwhile_factor (code))
4923 if (dump_enabled_p ())
4924 dump_printf (MSG_NOTE, "proceeding using word mode.\n");
4927 /* Worthwhile without SIMD support? */
4928 if (!VECTOR_MODE_P (TYPE_MODE (vectype_in))
4929 && LOOP_VINFO_VECT_FACTOR (loop_vinfo)
4930 < vect_min_worthwhile_factor (code))
4932 if (dump_enabled_p ())
4933 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
4934 "not worthwhile without SIMD support.\n");
4940 /* 4.2. Check support for the epilog operation.
4942 If STMT represents a reduction pattern, then the type of the
4943 reduction variable may be different than the type of the rest
4944 of the arguments. For example, consider the case of accumulation
4945 of shorts into an int accumulator; The original code:
4946 S1: int_a = (int) short_a;
4947 orig_stmt-> S2: int_acc = plus <int_a ,int_acc>;
4950 STMT: int_acc = widen_sum <short_a, int_acc>
4953 1. The tree-code that is used to create the vector operation in the
4954 epilog code (that reduces the partial results) is not the
4955 tree-code of STMT, but is rather the tree-code of the original
4956 stmt from the pattern that STMT is replacing. I.e, in the example
4957 above we want to use 'widen_sum' in the loop, but 'plus' in the
4959 2. The type (mode) we use to check available target support
4960 for the vector operation to be created in the *epilog*, is
4961 determined by the type of the reduction variable (in the example
4962 above we'd check this: optab_handler (plus_optab, vect_int_mode])).
4963 However the type (mode) we use to check available target support
4964 for the vector operation to be created *inside the loop*, is
4965 determined by the type of the other arguments to STMT (in the
4966 example we'd check this: optab_handler (widen_sum_optab,
4969 This is contrary to "regular" reductions, in which the types of all
4970 the arguments are the same as the type of the reduction variable.
4971 For "regular" reductions we can therefore use the same vector type
4972 (and also the same tree-code) when generating the epilog code and
4973 when generating the code inside the loop. */
4977 /* This is a reduction pattern: get the vectype from the type of the
4978 reduction variable, and get the tree-code from orig_stmt. */
4979 orig_code = gimple_assign_rhs_code (orig_stmt);
4980 gcc_assert (vectype_out);
4981 vec_mode = TYPE_MODE (vectype_out);
4985 /* Regular reduction: use the same vectype and tree-code as used for
4986 the vector code inside the loop can be used for the epilog code. */
4992 def_bb = gimple_bb (reduc_def_stmt);
4993 def_stmt_loop = def_bb->loop_father;
4994 def_arg = PHI_ARG_DEF_FROM_EDGE (reduc_def_stmt,
4995 loop_preheader_edge (def_stmt_loop));
4996 if (TREE_CODE (def_arg) == SSA_NAME
4997 && (def_arg_stmt = SSA_NAME_DEF_STMT (def_arg))
4998 && gimple_code (def_arg_stmt) == GIMPLE_PHI
4999 && flow_bb_inside_loop_p (outer_loop, gimple_bb (def_arg_stmt))
5000 && vinfo_for_stmt (def_arg_stmt)
5001 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_arg_stmt))
5002 == vect_double_reduction_def)
5003 double_reduc = true;
5006 epilog_reduc_code = ERROR_MARK;
5007 if (reduction_code_for_scalar_code (orig_code, &epilog_reduc_code))
5009 reduc_optab = optab_for_tree_code (epilog_reduc_code, vectype_out,
5013 if (dump_enabled_p ())
5014 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
5015 "no optab for reduction.\n");
5017 epilog_reduc_code = ERROR_MARK;
5021 && optab_handler (reduc_optab, vec_mode) == CODE_FOR_nothing)
5023 if (dump_enabled_p ())
5024 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
5025 "reduc op not supported by target.\n");
5027 epilog_reduc_code = ERROR_MARK;
5032 if (!nested_cycle || double_reduc)
5034 if (dump_enabled_p ())
5035 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
5036 "no reduc code for scalar code.\n");
5042 if (double_reduc && ncopies > 1)
5044 if (dump_enabled_p ())
5045 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
5046 "multiple types in double reduction\n");
5051 /* In case of widenning multiplication by a constant, we update the type
5052 of the constant to be the type of the other operand. We check that the
5053 constant fits the type in the pattern recognition pass. */
5054 if (code == DOT_PROD_EXPR
5055 && !types_compatible_p (TREE_TYPE (ops[0]), TREE_TYPE (ops[1])))
5057 if (TREE_CODE (ops[0]) == INTEGER_CST)
5058 ops[0] = fold_convert (TREE_TYPE (ops[1]), ops[0]);
5059 else if (TREE_CODE (ops[1]) == INTEGER_CST)
5060 ops[1] = fold_convert (TREE_TYPE (ops[0]), ops[1]);
5063 if (dump_enabled_p ())
5064 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
5065 "invalid types in dot-prod\n");
5071 if (!vec_stmt) /* transformation not required. */
5073 if (!vect_model_reduction_cost (stmt_info, epilog_reduc_code, ncopies))
5075 STMT_VINFO_TYPE (stmt_info) = reduc_vec_info_type;
5081 if (dump_enabled_p ())
5082 dump_printf_loc (MSG_NOTE, vect_location, "transform reduction.\n");
5084 /* FORNOW: Multiple types are not supported for condition. */
5085 if (code == COND_EXPR)
5086 gcc_assert (ncopies == 1);
5088 /* Create the destination vector */
5089 vec_dest = vect_create_destination_var (scalar_dest, vectype_out);
5091 /* In case the vectorization factor (VF) is bigger than the number
5092 of elements that we can fit in a vectype (nunits), we have to generate
5093 more than one vector stmt - i.e - we need to "unroll" the
5094 vector stmt by a factor VF/nunits. For more details see documentation
5095 in vectorizable_operation. */
5097 /* If the reduction is used in an outer loop we need to generate
5098 VF intermediate results, like so (e.g. for ncopies=2):
5103 (i.e. we generate VF results in 2 registers).
5104 In this case we have a separate def-use cycle for each copy, and therefore
5105 for each copy we get the vector def for the reduction variable from the
5106 respective phi node created for this copy.
5108 Otherwise (the reduction is unused in the loop nest), we can combine
5109 together intermediate results, like so (e.g. for ncopies=2):
5113 (i.e. we generate VF/2 results in a single register).
5114 In this case for each copy we get the vector def for the reduction variable
5115 from the vectorized reduction operation generated in the previous iteration.
5118 if (STMT_VINFO_RELEVANT (stmt_info) == vect_unused_in_scope)
5120 single_defuse_cycle = true;
5124 epilog_copies = ncopies;
5126 prev_stmt_info = NULL;
5127 prev_phi_info = NULL;
5130 vec_num = SLP_TREE_NUMBER_OF_VEC_STMTS (slp_node);
5131 gcc_assert (TYPE_VECTOR_SUBPARTS (vectype_out)
5132 == TYPE_VECTOR_SUBPARTS (vectype_in));
5137 vec_oprnds0.create (1);
5138 if (op_type == ternary_op)
5139 vec_oprnds1.create (1);
5142 phis.create (vec_num);
5143 vect_defs.create (vec_num);
5145 vect_defs.quick_push (NULL_TREE);
5147 for (j = 0; j < ncopies; j++)
5149 if (j == 0 || !single_defuse_cycle)
5151 for (i = 0; i < vec_num; i++)
5153 /* Create the reduction-phi that defines the reduction
5155 new_phi = create_phi_node (vec_dest, loop->header);
5156 set_vinfo_for_stmt (new_phi,
5157 new_stmt_vec_info (new_phi, loop_vinfo,
5159 if (j == 0 || slp_node)
5160 phis.quick_push (new_phi);
5164 if (code == COND_EXPR)
5166 gcc_assert (!slp_node);
5167 vectorizable_condition (stmt, gsi, vec_stmt,
5168 PHI_RESULT (phis[0]),
5170 /* Multiple types are not supported for condition. */
5177 op0 = ops[!reduc_index];
5178 if (op_type == ternary_op)
5180 if (reduc_index == 0)
5187 vect_get_vec_defs (op0, op1, stmt, &vec_oprnds0, &vec_oprnds1,
5191 loop_vec_def0 = vect_get_vec_def_for_operand (ops[!reduc_index],
5193 vec_oprnds0.quick_push (loop_vec_def0);
5194 if (op_type == ternary_op)
5196 loop_vec_def1 = vect_get_vec_def_for_operand (op1, stmt,
5198 vec_oprnds1.quick_push (loop_vec_def1);
5206 enum vect_def_type dt;
5210 vect_is_simple_use (ops[!reduc_index], stmt, loop_vinfo, NULL,
5211 &dummy_stmt, &dummy, &dt);
5212 loop_vec_def0 = vect_get_vec_def_for_stmt_copy (dt,
5214 vec_oprnds0[0] = loop_vec_def0;
5215 if (op_type == ternary_op)
5217 vect_is_simple_use (op1, stmt, loop_vinfo, NULL, &dummy_stmt,
5219 loop_vec_def1 = vect_get_vec_def_for_stmt_copy (dt,
5221 vec_oprnds1[0] = loop_vec_def1;
5225 if (single_defuse_cycle)
5226 reduc_def = gimple_assign_lhs (new_stmt);
5228 STMT_VINFO_RELATED_STMT (prev_phi_info) = new_phi;
5231 FOR_EACH_VEC_ELT (vec_oprnds0, i, def0)
5234 reduc_def = PHI_RESULT (phis[i]);
5237 if (!single_defuse_cycle || j == 0)
5238 reduc_def = PHI_RESULT (new_phi);
5241 def1 = ((op_type == ternary_op)
5242 ? vec_oprnds1[i] : NULL);
5243 if (op_type == binary_op)
5245 if (reduc_index == 0)
5246 expr = build2 (code, vectype_out, reduc_def, def0);
5248 expr = build2 (code, vectype_out, def0, reduc_def);
5252 if (reduc_index == 0)
5253 expr = build3 (code, vectype_out, reduc_def, def0, def1);
5256 if (reduc_index == 1)
5257 expr = build3 (code, vectype_out, def0, reduc_def, def1);
5259 expr = build3 (code, vectype_out, def0, def1, reduc_def);
5263 new_stmt = gimple_build_assign (vec_dest, expr);
5264 new_temp = make_ssa_name (vec_dest, new_stmt);
5265 gimple_assign_set_lhs (new_stmt, new_temp);
5266 vect_finish_stmt_generation (stmt, new_stmt, gsi);
5270 SLP_TREE_VEC_STMTS (slp_node).quick_push (new_stmt);
5271 vect_defs.quick_push (new_temp);
5274 vect_defs[0] = new_temp;
5281 STMT_VINFO_VEC_STMT (stmt_info) = *vec_stmt = new_stmt;
5283 STMT_VINFO_RELATED_STMT (prev_stmt_info) = new_stmt;
5285 prev_stmt_info = vinfo_for_stmt (new_stmt);
5286 prev_phi_info = vinfo_for_stmt (new_phi);
5289 /* Finalize the reduction-phi (set its arguments) and create the
5290 epilog reduction code. */
5291 if ((!single_defuse_cycle || code == COND_EXPR) && !slp_node)
5293 new_temp = gimple_assign_lhs (*vec_stmt);
5294 vect_defs[0] = new_temp;
5297 vect_create_epilog_for_reduction (vect_defs, stmt, epilog_copies,
5298 epilog_reduc_code, phis, reduc_index,
5299 double_reduc, slp_node);
5302 vect_defs.release ();
5303 vec_oprnds0.release ();
5304 vec_oprnds1.release ();
5309 /* Function vect_min_worthwhile_factor.
5311 For a loop where we could vectorize the operation indicated by CODE,
5312 return the minimum vectorization factor that makes it worthwhile
5313 to use generic vectors. */
5315 vect_min_worthwhile_factor (enum tree_code code)
5336 /* Function vectorizable_induction
5338 Check if PHI performs an induction computation that can be vectorized.
5339 If VEC_STMT is also passed, vectorize the induction PHI: create a vectorized
5340 phi to replace it, put it in VEC_STMT, and add it to the same basic block.
5341 Return FALSE if not a vectorizable STMT, TRUE otherwise. */
5344 vectorizable_induction (gimple phi, gimple_stmt_iterator *gsi ATTRIBUTE_UNUSED,
5347 stmt_vec_info stmt_info = vinfo_for_stmt (phi);
5348 tree vectype = STMT_VINFO_VECTYPE (stmt_info);
5349 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
5350 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
5351 int nunits = TYPE_VECTOR_SUBPARTS (vectype);
5352 int ncopies = LOOP_VINFO_VECT_FACTOR (loop_vinfo) / nunits;
5355 gcc_assert (ncopies >= 1);
5356 /* FORNOW. These restrictions should be relaxed. */
5357 if (nested_in_vect_loop_p (loop, phi))
5359 imm_use_iterator imm_iter;
5360 use_operand_p use_p;
5367 if (dump_enabled_p ())
5368 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
5369 "multiple types in nested loop.\n");
5374 latch_e = loop_latch_edge (loop->inner);
5375 loop_arg = PHI_ARG_DEF_FROM_EDGE (phi, latch_e);
5376 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, loop_arg)
5378 if (!flow_bb_inside_loop_p (loop->inner,
5379 gimple_bb (USE_STMT (use_p))))
5381 exit_phi = USE_STMT (use_p);
5387 stmt_vec_info exit_phi_vinfo = vinfo_for_stmt (exit_phi);
5388 if (!(STMT_VINFO_RELEVANT_P (exit_phi_vinfo)
5389 && !STMT_VINFO_LIVE_P (exit_phi_vinfo)))
5391 if (dump_enabled_p ())
5392 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
5393 "inner-loop induction only used outside "
5394 "of the outer vectorized loop.\n");
5400 if (!STMT_VINFO_RELEVANT_P (stmt_info))
5403 /* FORNOW: SLP not supported. */
5404 if (STMT_SLP_TYPE (stmt_info))
5407 gcc_assert (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def);
5409 if (gimple_code (phi) != GIMPLE_PHI)
5412 if (!vec_stmt) /* transformation not required. */
5414 STMT_VINFO_TYPE (stmt_info) = induc_vec_info_type;
5415 if (dump_enabled_p ())
5416 dump_printf_loc (MSG_NOTE, vect_location,
5417 "=== vectorizable_induction ===\n");
5418 vect_model_induction_cost (stmt_info, ncopies);
5424 if (dump_enabled_p ())
5425 dump_printf_loc (MSG_NOTE, vect_location, "transform induction phi.\n");
5427 vec_def = get_initial_def_for_induction (phi);
5428 *vec_stmt = SSA_NAME_DEF_STMT (vec_def);
5432 /* Function vectorizable_live_operation.
5434 STMT computes a value that is used outside the loop. Check if
5435 it can be supported. */
5438 vectorizable_live_operation (gimple stmt,
5439 gimple_stmt_iterator *gsi ATTRIBUTE_UNUSED,
5442 stmt_vec_info stmt_info = vinfo_for_stmt (stmt);
5443 loop_vec_info loop_vinfo = STMT_VINFO_LOOP_VINFO (stmt_info);
5444 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
5450 enum vect_def_type dt;
5451 enum tree_code code;
5452 enum gimple_rhs_class rhs_class;
5454 gcc_assert (STMT_VINFO_LIVE_P (stmt_info));
5456 if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_reduction_def)
5459 if (!is_gimple_assign (stmt))
5461 if (gimple_call_internal_p (stmt)
5462 && gimple_call_internal_fn (stmt) == IFN_GOMP_SIMD_LANE
5463 && gimple_call_lhs (stmt)
5465 && TREE_CODE (gimple_call_arg (stmt, 0)) == SSA_NAME
5467 == SSA_NAME_VAR (gimple_call_arg (stmt, 0)))
5469 edge e = single_exit (loop);
5470 basic_block merge_bb = e->dest;
5471 imm_use_iterator imm_iter;
5472 use_operand_p use_p;
5473 tree lhs = gimple_call_lhs (stmt);
5475 FOR_EACH_IMM_USE_FAST (use_p, imm_iter, lhs)
5477 gimple use_stmt = USE_STMT (use_p);
5478 if (gimple_code (use_stmt) == GIMPLE_PHI
5479 || gimple_bb (use_stmt) == merge_bb)
5484 = build_int_cst (unsigned_type_node,
5485 loop_vinfo->vectorization_factor - 1);
5486 SET_PHI_ARG_DEF (use_stmt, e->dest_idx, vfm1);
5496 if (TREE_CODE (gimple_assign_lhs (stmt)) != SSA_NAME)
5499 /* FORNOW. CHECKME. */
5500 if (nested_in_vect_loop_p (loop, stmt))
5503 code = gimple_assign_rhs_code (stmt);
5504 op_type = TREE_CODE_LENGTH (code);
5505 rhs_class = get_gimple_rhs_class (code);
5506 gcc_assert (rhs_class != GIMPLE_UNARY_RHS || op_type == unary_op);
5507 gcc_assert (rhs_class != GIMPLE_BINARY_RHS || op_type == binary_op);
5509 /* FORNOW: support only if all uses are invariant. This means
5510 that the scalar operations can remain in place, unvectorized.
5511 The original last scalar value that they compute will be used. */
5513 for (i = 0; i < op_type; i++)
5515 if (rhs_class == GIMPLE_SINGLE_RHS)
5516 op = TREE_OPERAND (gimple_op (stmt, 1), i);
5518 op = gimple_op (stmt, i + 1);
5520 && !vect_is_simple_use (op, stmt, loop_vinfo, NULL, &def_stmt, &def,
5523 if (dump_enabled_p ())
5524 dump_printf_loc (MSG_MISSED_OPTIMIZATION, vect_location,
5525 "use not simple.\n");
5529 if (dt != vect_external_def && dt != vect_constant_def)
5533 /* No transformation is required for the cases we currently support. */
5537 /* Kill any debug uses outside LOOP of SSA names defined in STMT. */
5540 vect_loop_kill_debug_uses (struct loop *loop, gimple stmt)
5542 ssa_op_iter op_iter;
5543 imm_use_iterator imm_iter;
5544 def_operand_p def_p;
5547 FOR_EACH_PHI_OR_STMT_DEF (def_p, stmt, op_iter, SSA_OP_DEF)
5549 FOR_EACH_IMM_USE_STMT (ustmt, imm_iter, DEF_FROM_PTR (def_p))
5553 if (!is_gimple_debug (ustmt))
5556 bb = gimple_bb (ustmt);
5558 if (!flow_bb_inside_loop_p (loop, bb))
5560 if (gimple_debug_bind_p (ustmt))
5562 if (dump_enabled_p ())
5563 dump_printf_loc (MSG_NOTE, vect_location,
5564 "killing debug use\n");
5566 gimple_debug_bind_reset_value (ustmt);
5567 update_stmt (ustmt);
5576 /* Function vect_transform_loop.
5578 The analysis phase has determined that the loop is vectorizable.
5579 Vectorize the loop - created vectorized stmts to replace the scalar
5580 stmts in the loop, and update the loop exit condition. */
5583 vect_transform_loop (loop_vec_info loop_vinfo)
5585 struct loop *loop = LOOP_VINFO_LOOP (loop_vinfo);
5586 basic_block *bbs = LOOP_VINFO_BBS (loop_vinfo);
5587 int nbbs = loop->num_nodes;
5588 gimple_stmt_iterator si;
5591 int vectorization_factor = LOOP_VINFO_VECT_FACTOR (loop_vinfo);
5593 bool slp_scheduled = false;
5594 unsigned int nunits;
5595 gimple stmt, pattern_stmt;
5596 gimple_seq pattern_def_seq = NULL;
5597 gimple_stmt_iterator pattern_def_si = gsi_none ();
5598 bool transform_pattern_stmt = false;
5599 bool check_profitability = false;
5601 /* Record number of iterations before we started tampering with the profile. */
5602 gcov_type expected_iterations = expected_loop_iterations_unbounded (loop);
5604 if (dump_enabled_p ())
5605 dump_printf_loc (MSG_NOTE, vect_location, "=== vec_transform_loop ===\n");
5607 /* If profile is inprecise, we have chance to fix it up. */
5608 if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
5609 expected_iterations = LOOP_VINFO_INT_NITERS (loop_vinfo);
5611 /* Use the more conservative vectorization threshold. If the number
5612 of iterations is constant assume the cost check has been performed
5613 by our caller. If the threshold makes all loops profitable that
5614 run at least the vectorization factor number of times checking
5615 is pointless, too. */
5616 th = ((PARAM_VALUE (PARAM_MIN_VECT_LOOP_BOUND)
5617 * LOOP_VINFO_VECT_FACTOR (loop_vinfo)) - 1);
5618 th = MAX (th, LOOP_VINFO_COST_MODEL_MIN_ITERS (loop_vinfo));
5619 if (th >= LOOP_VINFO_VECT_FACTOR (loop_vinfo) - 1
5620 && !LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
5622 if (dump_enabled_p ())
5623 dump_printf_loc (MSG_NOTE, vect_location,
5624 "Profitability threshold is %d loop iterations.\n",
5626 check_profitability = true;
5629 /* Version the loop first, if required, so the profitability check
5632 if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo)
5633 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo))
5635 vect_loop_versioning (loop_vinfo, th, check_profitability);
5636 check_profitability = false;
5639 /* Peel the loop if there are data refs with unknown alignment.
5640 Only one data ref with unknown store is allowed. */
5642 if (LOOP_PEELING_FOR_ALIGNMENT (loop_vinfo))
5644 vect_do_peeling_for_alignment (loop_vinfo, th, check_profitability);
5645 check_profitability = false;
5648 /* If the loop has a symbolic number of iterations 'n' (i.e. it's not a
5649 compile time constant), or it is a constant that doesn't divide by the
5650 vectorization factor, then an epilog loop needs to be created.
5651 We therefore duplicate the loop: the original loop will be vectorized,
5652 and will compute the first (n/VF) iterations. The second copy of the loop
5653 will remain scalar and will compute the remaining (n%VF) iterations.
5654 (VF is the vectorization factor). */
5656 if ((int) tree_ctz (LOOP_VINFO_NITERS (loop_vinfo))
5657 < exact_log2 (vectorization_factor)
5658 || LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo))
5659 vect_do_peeling_for_loop_bound (loop_vinfo, &ratio,
5660 th, check_profitability);
5661 else if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo))
5662 ratio = build_int_cst (TREE_TYPE (LOOP_VINFO_NITERS (loop_vinfo)),
5663 LOOP_VINFO_INT_NITERS (loop_vinfo) / vectorization_factor);
5666 tree ni_name, ratio_mult_vf;
5667 vect_generate_tmps_on_preheader (loop_vinfo, &ni_name, &ratio_mult_vf,
5671 /* 1) Make sure the loop header has exactly two entries
5672 2) Make sure we have a preheader basic block. */
5674 gcc_assert (EDGE_COUNT (loop->header->preds) == 2);
5676 split_edge (loop_preheader_edge (loop));
5678 /* FORNOW: the vectorizer supports only loops which body consist
5679 of one basic block (header + empty latch). When the vectorizer will
5680 support more involved loop forms, the order by which the BBs are
5681 traversed need to be reconsidered. */
5683 for (i = 0; i < nbbs; i++)
5685 basic_block bb = bbs[i];
5686 stmt_vec_info stmt_info;
5689 for (si = gsi_start_phis (bb); !gsi_end_p (si); gsi_next (&si))
5691 phi = gsi_stmt (si);
5692 if (dump_enabled_p ())
5694 dump_printf_loc (MSG_NOTE, vect_location,
5695 "------>vectorizing phi: ");
5696 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, phi, 0);
5697 dump_printf (MSG_NOTE, "\n");
5699 stmt_info = vinfo_for_stmt (phi);
5703 if (MAY_HAVE_DEBUG_STMTS && !STMT_VINFO_LIVE_P (stmt_info))
5704 vect_loop_kill_debug_uses (loop, phi);
5706 if (!STMT_VINFO_RELEVANT_P (stmt_info)
5707 && !STMT_VINFO_LIVE_P (stmt_info))
5710 if ((TYPE_VECTOR_SUBPARTS (STMT_VINFO_VECTYPE (stmt_info))
5711 != (unsigned HOST_WIDE_INT) vectorization_factor)
5712 && dump_enabled_p ())
5713 dump_printf_loc (MSG_NOTE, vect_location, "multiple-types.\n");
5715 if (STMT_VINFO_DEF_TYPE (stmt_info) == vect_induction_def)
5717 if (dump_enabled_p ())
5718 dump_printf_loc (MSG_NOTE, vect_location, "transform phi.\n");
5719 vect_transform_stmt (phi, NULL, NULL, NULL, NULL);
5723 pattern_stmt = NULL;
5724 for (si = gsi_start_bb (bb); !gsi_end_p (si) || transform_pattern_stmt;)
5728 if (transform_pattern_stmt)
5729 stmt = pattern_stmt;
5732 stmt = gsi_stmt (si);
5733 /* During vectorization remove existing clobber stmts. */
5734 if (gimple_clobber_p (stmt))
5736 unlink_stmt_vdef (stmt);
5737 gsi_remove (&si, true);
5738 release_defs (stmt);
5743 if (dump_enabled_p ())
5745 dump_printf_loc (MSG_NOTE, vect_location,
5746 "------>vectorizing statement: ");
5747 dump_gimple_stmt (MSG_NOTE, TDF_SLIM, stmt, 0);
5748 dump_printf (MSG_NOTE, "\n");
5751 stmt_info = vinfo_for_stmt (stmt);
5753 /* vector stmts created in the outer-loop during vectorization of
5754 stmts in an inner-loop may not have a stmt_info, and do not
5755 need to be vectorized. */
5762 if (MAY_HAVE_DEBUG_STMTS && !STMT_VINFO_LIVE_P (stmt_info))
5763 vect_loop_kill_debug_uses (loop, stmt);
5765 if (!STMT_VINFO_RELEVANT_P (stmt_info)
5766 && !STMT_VINFO_LIVE_P (stmt_info))
5768 if (STMT_VINFO_IN_PATTERN_P (stmt_info)
5769 && (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info))
5770 && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt))
5771 || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt))))
5773 stmt = pattern_stmt;
5774 stmt_info = vinfo_for_stmt (stmt);
5782 else if (STMT_VINFO_IN_PATTERN_P (stmt_info)
5783 && (pattern_stmt = STMT_VINFO_RELATED_STMT (stmt_info))
5784 && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt))
5785 || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt))))
5786 transform_pattern_stmt = true;
5788 /* If pattern statement has def stmts, vectorize them too. */
5789 if (is_pattern_stmt_p (stmt_info))
5791 if (pattern_def_seq == NULL)
5793 pattern_def_seq = STMT_VINFO_PATTERN_DEF_SEQ (stmt_info);
5794 pattern_def_si = gsi_start (pattern_def_seq);
5796 else if (!gsi_end_p (pattern_def_si))
5797 gsi_next (&pattern_def_si);
5798 if (pattern_def_seq != NULL)
5800 gimple pattern_def_stmt = NULL;
5801 stmt_vec_info pattern_def_stmt_info = NULL;
5803 while (!gsi_end_p (pattern_def_si))
5805 pattern_def_stmt = gsi_stmt (pattern_def_si);
5806 pattern_def_stmt_info
5807 = vinfo_for_stmt (pattern_def_stmt);
5808 if (STMT_VINFO_RELEVANT_P (pattern_def_stmt_info)
5809 || STMT_VINFO_LIVE_P (pattern_def_stmt_info))
5811 gsi_next (&pattern_def_si);
5814 if (!gsi_end_p (pattern_def_si))
5816 if (dump_enabled_p ())
5818 dump_printf_loc (MSG_NOTE, vect_location,
5819 "==> vectorizing pattern def "
5821 dump_gimple_stmt (MSG_NOTE, TDF_SLIM,
5822 pattern_def_stmt, 0);
5823 dump_printf (MSG_NOTE, "\n");
5826 stmt = pattern_def_stmt;
5827 stmt_info = pattern_def_stmt_info;
5831 pattern_def_si = gsi_none ();
5832 transform_pattern_stmt = false;
5836 transform_pattern_stmt = false;
5839 gcc_assert (STMT_VINFO_VECTYPE (stmt_info));
5840 nunits = (unsigned int) TYPE_VECTOR_SUBPARTS (
5841 STMT_VINFO_VECTYPE (stmt_info));
5842 if (!STMT_SLP_TYPE (stmt_info)
5843 && nunits != (unsigned int) vectorization_factor
5844 && dump_enabled_p ())
5845 /* For SLP VF is set according to unrolling factor, and not to
5846 vector size, hence for SLP this print is not valid. */
5847 dump_printf_loc (MSG_NOTE, vect_location,
5848 "multiple-types.\n");
5850 /* SLP. Schedule all the SLP instances when the first SLP stmt is
5852 if (STMT_SLP_TYPE (stmt_info))
5856 slp_scheduled = true;
5858 if (dump_enabled_p ())
5859 dump_printf_loc (MSG_NOTE, vect_location,
5860 "=== scheduling SLP instances ===\n");
5862 vect_schedule_slp (loop_vinfo, NULL);
5865 /* Hybrid SLP stmts must be vectorized in addition to SLP. */
5866 if (!vinfo_for_stmt (stmt) || PURE_SLP_STMT (stmt_info))
5868 if (!transform_pattern_stmt && gsi_end_p (pattern_def_si))
5870 pattern_def_seq = NULL;
5877 /* -------- vectorize statement ------------ */
5878 if (dump_enabled_p ())
5879 dump_printf_loc (MSG_NOTE, vect_location, "transform statement.\n");
5881 grouped_store = false;
5882 is_store = vect_transform_stmt (stmt, &si, &grouped_store, NULL, NULL);
5885 if (STMT_VINFO_GROUPED_ACCESS (stmt_info))
5887 /* Interleaving. If IS_STORE is TRUE, the vectorization of the
5888 interleaving chain was completed - free all the stores in
5891 vect_remove_stores (GROUP_FIRST_ELEMENT (stmt_info));
5896 /* Free the attached stmt_vec_info and remove the stmt. */
5897 gimple store = gsi_stmt (si);
5898 free_stmt_vec_info (store);
5899 unlink_stmt_vdef (store);
5900 gsi_remove (&si, true);
5901 release_defs (store);
5906 if (!transform_pattern_stmt && gsi_end_p (pattern_def_si))
5908 pattern_def_seq = NULL;
5914 slpeel_make_loop_iterate_ntimes (loop, ratio);
5916 /* Reduce loop iterations by the vectorization factor. */
5917 scale_loop_profile (loop, GCOV_COMPUTE_SCALE (1, vectorization_factor),
5918 expected_iterations / vectorization_factor);
5919 loop->nb_iterations_upper_bound
5920 = loop->nb_iterations_upper_bound.udiv (double_int::from_uhwi (vectorization_factor),
5922 if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo)
5923 && loop->nb_iterations_upper_bound != double_int_zero)
5924 loop->nb_iterations_upper_bound = loop->nb_iterations_upper_bound - double_int_one;
5925 if (loop->any_estimate)
5927 loop->nb_iterations_estimate
5928 = loop->nb_iterations_estimate.udiv (double_int::from_uhwi (vectorization_factor),
5930 if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo)
5931 && loop->nb_iterations_estimate != double_int_zero)
5932 loop->nb_iterations_estimate = loop->nb_iterations_estimate - double_int_one;
5935 if (dump_enabled_p ())
5937 dump_printf_loc (MSG_NOTE, vect_location,
5938 "LOOP VECTORIZED\n");
5940 dump_printf_loc (MSG_NOTE, vect_location,
5941 "OUTER LOOP VECTORIZED\n");
5942 dump_printf (MSG_NOTE, "\n");