2 Copyright (C) 2003-2014 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"
28 #include "stor-layout.h"
29 #include "basic-block.h"
30 #include "gimple-pretty-print.h"
31 #include "tree-ssa-alias.h"
32 #include "internal-fn.h"
33 #include "gimple-expr.h"
37 #include "gimple-iterator.h"
38 #include "gimplify-me.h"
39 #include "gimple-ssa.h"
40 #include "tree-phinodes.h"
41 #include "ssa-iterators.h"
42 #include "stringpool.h"
43 #include "tree-ssanames.h"
44 #include "tree-ssa-loop-ivopts.h"
45 #include "tree-ssa-loop-manip.h"
46 #include "tree-ssa-loop-niter.h"
47 #include "tree-pass.h"
53 #include "diagnostic-core.h"
54 #include "tree-chrec.h"
55 #include "tree-scalar-evolution.h"
56 #include "tree-vectorizer.h"
59 /* Loop Vectorization Pass.
61 This pass tries to vectorize loops.
63 For example, the vectorizer transforms the following simple loop:
65 short a[N]; short b[N]; short c[N]; int i;
71 as if it was manually vectorized by rewriting the source code into:
73 typedef int __attribute__((mode(V8HI))) v8hi;
74 short a[N]; short b[N]; short c[N]; int i;
75 v8hi *pa = (v8hi*)a, *pb = (v8hi*)b, *pc = (v8hi*)c;
78 for (i=0; i<N/8; i++){
85 The main entry to this pass is vectorize_loops(), in which
86 the vectorizer applies a set of analyses on a given set of loops,
87 followed by the actual vectorization transformation for the loops that
88 had successfully passed the analysis phase.
89 Throughout this pass we make a distinction between two types of
90 data: scalars (which are represented by SSA_NAMES), and memory references
91 ("data-refs"). These two types of data require different handling both
92 during analysis and transformation. The types of data-refs that the
93 vectorizer currently supports are ARRAY_REFS which base is an array DECL
94 (not a pointer), and INDIRECT_REFS through pointers; both array and pointer
95 accesses are required to have a simple (consecutive) access pattern.
99 The driver for the analysis phase is vect_analyze_loop().
100 It applies a set of analyses, some of which rely on the scalar evolution
101 analyzer (scev) developed by Sebastian Pop.
103 During the analysis phase the vectorizer records some information
104 per stmt in a "stmt_vec_info" struct which is attached to each stmt in the
105 loop, as well as general information about the loop as a whole, which is
106 recorded in a "loop_vec_info" struct attached to each loop.
108 Transformation phase:
109 =====================
110 The loop transformation phase scans all the stmts in the loop, and
111 creates a vector stmt (or a sequence of stmts) for each scalar stmt S in
112 the loop that needs to be vectorized. It inserts the vector code sequence
113 just before the scalar stmt S, and records a pointer to the vector code
114 in STMT_VINFO_VEC_STMT (stmt_info) (stmt_info is the stmt_vec_info struct
115 attached to S). This pointer will be used for the vectorization of following
116 stmts which use the def of stmt S. Stmt S is removed if it writes to memory;
117 otherwise, we rely on dead code elimination for removing it.
119 For example, say stmt S1 was vectorized into stmt VS1:
122 S1: b = x[i]; STMT_VINFO_VEC_STMT (stmt_info (S1)) = VS1
125 To vectorize stmt S2, the vectorizer first finds the stmt that defines
126 the operand 'b' (S1), and gets the relevant vector def 'vb' from the
127 vector stmt VS1 pointed to by STMT_VINFO_VEC_STMT (stmt_info (S1)). The
128 resulting sequence would be:
131 S1: b = x[i]; STMT_VINFO_VEC_STMT (stmt_info (S1)) = VS1
133 S2: a = b; STMT_VINFO_VEC_STMT (stmt_info (S2)) = VS2
135 Operands that are not SSA_NAMEs, are data-refs that appear in
136 load/store operations (like 'x[i]' in S1), and are handled differently.
140 Currently the only target specific information that is used is the
141 size of the vector (in bytes) - "TARGET_VECTORIZE_UNITS_PER_SIMD_WORD".
142 Targets that can support different sizes of vectors, for now will need
143 to specify one value for "TARGET_VECTORIZE_UNITS_PER_SIMD_WORD". More
144 flexibility will be added in the future.
146 Since we only vectorize operations which vector form can be
147 expressed using existing tree codes, to verify that an operation is
148 supported, the vectorizer checks the relevant optab at the relevant
149 machine_mode (e.g, optab_handler (add_optab, V8HImode)). If
150 the value found is CODE_FOR_nothing, then there's no target support, and
151 we can't vectorize the stmt.
153 For additional information on this project see:
154 http://gcc.gnu.org/projects/tree-ssa/vectorization.html
157 static void vect_estimate_min_profitable_iters (loop_vec_info
, int *, int *);
159 /* Function vect_determine_vectorization_factor
161 Determine the vectorization factor (VF). VF is the number of data elements
162 that are operated upon in parallel in a single iteration of the vectorized
163 loop. For example, when vectorizing a loop that operates on 4byte elements,
164 on a target with vector size (VS) 16byte, the VF is set to 4, since 4
165 elements can fit in a single vector register.
167 We currently support vectorization of loops in which all types operated upon
168 are of the same size. Therefore this function currently sets VF according to
169 the size of the types operated upon, and fails if there are multiple sizes
172 VF is also the factor by which the loop iterations are strip-mined, e.g.:
179 for (i=0; i<N; i+=VF){
180 a[i:VF] = b[i:VF] + c[i:VF];
185 vect_determine_vectorization_factor (loop_vec_info loop_vinfo
)
187 struct loop
*loop
= LOOP_VINFO_LOOP (loop_vinfo
);
188 basic_block
*bbs
= LOOP_VINFO_BBS (loop_vinfo
);
189 int nbbs
= loop
->num_nodes
;
190 gimple_stmt_iterator si
;
191 unsigned int vectorization_factor
= 0;
196 stmt_vec_info stmt_info
;
199 gimple stmt
, pattern_stmt
= NULL
;
200 gimple_seq pattern_def_seq
= NULL
;
201 gimple_stmt_iterator pattern_def_si
= gsi_none ();
202 bool analyze_pattern_stmt
= false;
204 if (dump_enabled_p ())
205 dump_printf_loc (MSG_NOTE
, vect_location
,
206 "=== vect_determine_vectorization_factor ===\n");
208 for (i
= 0; i
< nbbs
; i
++)
210 basic_block bb
= bbs
[i
];
212 for (si
= gsi_start_phis (bb
); !gsi_end_p (si
); gsi_next (&si
))
215 stmt_info
= vinfo_for_stmt (phi
);
216 if (dump_enabled_p ())
218 dump_printf_loc (MSG_NOTE
, vect_location
, "==> examining phi: ");
219 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, phi
, 0);
220 dump_printf (MSG_NOTE
, "\n");
223 gcc_assert (stmt_info
);
225 if (STMT_VINFO_RELEVANT_P (stmt_info
))
227 gcc_assert (!STMT_VINFO_VECTYPE (stmt_info
));
228 scalar_type
= TREE_TYPE (PHI_RESULT (phi
));
230 if (dump_enabled_p ())
232 dump_printf_loc (MSG_NOTE
, vect_location
,
233 "get vectype for scalar type: ");
234 dump_generic_expr (MSG_NOTE
, TDF_SLIM
, scalar_type
);
235 dump_printf (MSG_NOTE
, "\n");
238 vectype
= get_vectype_for_scalar_type (scalar_type
);
241 if (dump_enabled_p ())
243 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
244 "not vectorized: unsupported "
246 dump_generic_expr (MSG_MISSED_OPTIMIZATION
, TDF_SLIM
,
248 dump_printf (MSG_MISSED_OPTIMIZATION
, "\n");
252 STMT_VINFO_VECTYPE (stmt_info
) = vectype
;
254 if (dump_enabled_p ())
256 dump_printf_loc (MSG_NOTE
, vect_location
, "vectype: ");
257 dump_generic_expr (MSG_NOTE
, TDF_SLIM
, vectype
);
258 dump_printf (MSG_NOTE
, "\n");
261 nunits
= TYPE_VECTOR_SUBPARTS (vectype
);
262 if (dump_enabled_p ())
263 dump_printf_loc (MSG_NOTE
, vect_location
, "nunits = %d\n",
266 if (!vectorization_factor
267 || (nunits
> vectorization_factor
))
268 vectorization_factor
= nunits
;
272 for (si
= gsi_start_bb (bb
); !gsi_end_p (si
) || analyze_pattern_stmt
;)
276 if (analyze_pattern_stmt
)
279 stmt
= gsi_stmt (si
);
281 stmt_info
= vinfo_for_stmt (stmt
);
283 if (dump_enabled_p ())
285 dump_printf_loc (MSG_NOTE
, vect_location
,
286 "==> examining statement: ");
287 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, stmt
, 0);
288 dump_printf (MSG_NOTE
, "\n");
291 gcc_assert (stmt_info
);
293 /* Skip stmts which do not need to be vectorized. */
294 if ((!STMT_VINFO_RELEVANT_P (stmt_info
)
295 && !STMT_VINFO_LIVE_P (stmt_info
))
296 || gimple_clobber_p (stmt
))
298 if (STMT_VINFO_IN_PATTERN_P (stmt_info
)
299 && (pattern_stmt
= STMT_VINFO_RELATED_STMT (stmt_info
))
300 && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt
))
301 || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt
))))
304 stmt_info
= vinfo_for_stmt (pattern_stmt
);
305 if (dump_enabled_p ())
307 dump_printf_loc (MSG_NOTE
, vect_location
,
308 "==> examining pattern statement: ");
309 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, stmt
, 0);
310 dump_printf (MSG_NOTE
, "\n");
315 if (dump_enabled_p ())
316 dump_printf_loc (MSG_NOTE
, vect_location
, "skip.\n");
321 else if (STMT_VINFO_IN_PATTERN_P (stmt_info
)
322 && (pattern_stmt
= STMT_VINFO_RELATED_STMT (stmt_info
))
323 && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt
))
324 || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt
))))
325 analyze_pattern_stmt
= true;
327 /* If a pattern statement has def stmts, analyze them too. */
328 if (is_pattern_stmt_p (stmt_info
))
330 if (pattern_def_seq
== NULL
)
332 pattern_def_seq
= STMT_VINFO_PATTERN_DEF_SEQ (stmt_info
);
333 pattern_def_si
= gsi_start (pattern_def_seq
);
335 else if (!gsi_end_p (pattern_def_si
))
336 gsi_next (&pattern_def_si
);
337 if (pattern_def_seq
!= NULL
)
339 gimple pattern_def_stmt
= NULL
;
340 stmt_vec_info pattern_def_stmt_info
= NULL
;
342 while (!gsi_end_p (pattern_def_si
))
344 pattern_def_stmt
= gsi_stmt (pattern_def_si
);
345 pattern_def_stmt_info
346 = vinfo_for_stmt (pattern_def_stmt
);
347 if (STMT_VINFO_RELEVANT_P (pattern_def_stmt_info
)
348 || STMT_VINFO_LIVE_P (pattern_def_stmt_info
))
350 gsi_next (&pattern_def_si
);
353 if (!gsi_end_p (pattern_def_si
))
355 if (dump_enabled_p ())
357 dump_printf_loc (MSG_NOTE
, vect_location
,
358 "==> examining pattern def stmt: ");
359 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
,
360 pattern_def_stmt
, 0);
361 dump_printf (MSG_NOTE
, "\n");
364 stmt
= pattern_def_stmt
;
365 stmt_info
= pattern_def_stmt_info
;
369 pattern_def_si
= gsi_none ();
370 analyze_pattern_stmt
= false;
374 analyze_pattern_stmt
= false;
377 if (gimple_get_lhs (stmt
) == NULL_TREE
378 /* MASK_STORE has no lhs, but is ok. */
379 && (!is_gimple_call (stmt
)
380 || !gimple_call_internal_p (stmt
)
381 || gimple_call_internal_fn (stmt
) != IFN_MASK_STORE
))
383 if (is_gimple_call (stmt
))
385 /* Ignore calls with no lhs. These must be calls to
386 #pragma omp simd functions, and what vectorization factor
387 it really needs can't be determined until
388 vectorizable_simd_clone_call. */
389 if (!analyze_pattern_stmt
&& gsi_end_p (pattern_def_si
))
391 pattern_def_seq
= NULL
;
396 if (dump_enabled_p ())
398 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
399 "not vectorized: irregular stmt.");
400 dump_gimple_stmt (MSG_MISSED_OPTIMIZATION
, TDF_SLIM
, stmt
,
402 dump_printf (MSG_MISSED_OPTIMIZATION
, "\n");
407 if (VECTOR_MODE_P (TYPE_MODE (gimple_expr_type (stmt
))))
409 if (dump_enabled_p ())
411 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
412 "not vectorized: vector stmt in loop:");
413 dump_gimple_stmt (MSG_MISSED_OPTIMIZATION
, TDF_SLIM
, stmt
, 0);
414 dump_printf (MSG_MISSED_OPTIMIZATION
, "\n");
419 if (STMT_VINFO_VECTYPE (stmt_info
))
421 /* The only case when a vectype had been already set is for stmts
422 that contain a dataref, or for "pattern-stmts" (stmts
423 generated by the vectorizer to represent/replace a certain
425 gcc_assert (STMT_VINFO_DATA_REF (stmt_info
)
426 || is_pattern_stmt_p (stmt_info
)
427 || !gsi_end_p (pattern_def_si
));
428 vectype
= STMT_VINFO_VECTYPE (stmt_info
);
432 gcc_assert (!STMT_VINFO_DATA_REF (stmt_info
));
433 if (is_gimple_call (stmt
)
434 && gimple_call_internal_p (stmt
)
435 && gimple_call_internal_fn (stmt
) == IFN_MASK_STORE
)
436 scalar_type
= TREE_TYPE (gimple_call_arg (stmt
, 3));
438 scalar_type
= TREE_TYPE (gimple_get_lhs (stmt
));
439 if (dump_enabled_p ())
441 dump_printf_loc (MSG_NOTE
, vect_location
,
442 "get vectype for scalar type: ");
443 dump_generic_expr (MSG_NOTE
, TDF_SLIM
, scalar_type
);
444 dump_printf (MSG_NOTE
, "\n");
446 vectype
= get_vectype_for_scalar_type (scalar_type
);
449 if (dump_enabled_p ())
451 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
452 "not vectorized: unsupported "
454 dump_generic_expr (MSG_MISSED_OPTIMIZATION
, TDF_SLIM
,
456 dump_printf (MSG_MISSED_OPTIMIZATION
, "\n");
461 STMT_VINFO_VECTYPE (stmt_info
) = vectype
;
463 if (dump_enabled_p ())
465 dump_printf_loc (MSG_NOTE
, vect_location
, "vectype: ");
466 dump_generic_expr (MSG_NOTE
, TDF_SLIM
, vectype
);
467 dump_printf (MSG_NOTE
, "\n");
471 /* The vectorization factor is according to the smallest
472 scalar type (or the largest vector size, but we only
473 support one vector size per loop). */
474 scalar_type
= vect_get_smallest_scalar_type (stmt
, &dummy
,
476 if (dump_enabled_p ())
478 dump_printf_loc (MSG_NOTE
, vect_location
,
479 "get vectype for scalar type: ");
480 dump_generic_expr (MSG_NOTE
, TDF_SLIM
, scalar_type
);
481 dump_printf (MSG_NOTE
, "\n");
483 vf_vectype
= get_vectype_for_scalar_type (scalar_type
);
486 if (dump_enabled_p ())
488 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
489 "not vectorized: unsupported data-type ");
490 dump_generic_expr (MSG_MISSED_OPTIMIZATION
, TDF_SLIM
,
492 dump_printf (MSG_MISSED_OPTIMIZATION
, "\n");
497 if ((GET_MODE_SIZE (TYPE_MODE (vectype
))
498 != GET_MODE_SIZE (TYPE_MODE (vf_vectype
))))
500 if (dump_enabled_p ())
502 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
503 "not vectorized: different sized vector "
504 "types in statement, ");
505 dump_generic_expr (MSG_MISSED_OPTIMIZATION
, TDF_SLIM
,
507 dump_printf (MSG_MISSED_OPTIMIZATION
, " and ");
508 dump_generic_expr (MSG_MISSED_OPTIMIZATION
, TDF_SLIM
,
510 dump_printf (MSG_MISSED_OPTIMIZATION
, "\n");
515 if (dump_enabled_p ())
517 dump_printf_loc (MSG_NOTE
, vect_location
, "vectype: ");
518 dump_generic_expr (MSG_NOTE
, TDF_SLIM
, vf_vectype
);
519 dump_printf (MSG_NOTE
, "\n");
522 nunits
= TYPE_VECTOR_SUBPARTS (vf_vectype
);
523 if (dump_enabled_p ())
524 dump_printf_loc (MSG_NOTE
, vect_location
, "nunits = %d\n", nunits
);
525 if (!vectorization_factor
526 || (nunits
> vectorization_factor
))
527 vectorization_factor
= nunits
;
529 if (!analyze_pattern_stmt
&& gsi_end_p (pattern_def_si
))
531 pattern_def_seq
= NULL
;
537 /* TODO: Analyze cost. Decide if worth while to vectorize. */
538 if (dump_enabled_p ())
539 dump_printf_loc (MSG_NOTE
, vect_location
, "vectorization factor = %d\n",
540 vectorization_factor
);
541 if (vectorization_factor
<= 1)
543 if (dump_enabled_p ())
544 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
545 "not vectorized: unsupported data-type\n");
548 LOOP_VINFO_VECT_FACTOR (loop_vinfo
) = vectorization_factor
;
554 /* Function vect_is_simple_iv_evolution.
556 FORNOW: A simple evolution of an induction variables in the loop is
557 considered a polynomial evolution. */
560 vect_is_simple_iv_evolution (unsigned loop_nb
, tree access_fn
, tree
* init
,
565 tree evolution_part
= evolution_part_in_loop_num (access_fn
, loop_nb
);
568 /* When there is no evolution in this loop, the evolution function
570 if (evolution_part
== NULL_TREE
)
573 /* When the evolution is a polynomial of degree >= 2
574 the evolution function is not "simple". */
575 if (tree_is_chrec (evolution_part
))
578 step_expr
= evolution_part
;
579 init_expr
= unshare_expr (initial_condition_in_loop_num (access_fn
, loop_nb
));
581 if (dump_enabled_p ())
583 dump_printf_loc (MSG_NOTE
, vect_location
, "step: ");
584 dump_generic_expr (MSG_NOTE
, TDF_SLIM
, step_expr
);
585 dump_printf (MSG_NOTE
, ", init: ");
586 dump_generic_expr (MSG_NOTE
, TDF_SLIM
, init_expr
);
587 dump_printf (MSG_NOTE
, "\n");
593 if (TREE_CODE (step_expr
) != INTEGER_CST
594 && (TREE_CODE (step_expr
) != SSA_NAME
595 || ((bb
= gimple_bb (SSA_NAME_DEF_STMT (step_expr
)))
596 && flow_bb_inside_loop_p (get_loop (cfun
, loop_nb
), bb
))
597 || (!INTEGRAL_TYPE_P (TREE_TYPE (step_expr
))
598 && (!SCALAR_FLOAT_TYPE_P (TREE_TYPE (step_expr
))
599 || !flag_associative_math
)))
600 && (TREE_CODE (step_expr
) != REAL_CST
601 || !flag_associative_math
))
603 if (dump_enabled_p ())
604 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
612 /* Function vect_analyze_scalar_cycles_1.
614 Examine the cross iteration def-use cycles of scalar variables
615 in LOOP. LOOP_VINFO represents the loop that is now being
616 considered for vectorization (can be LOOP, or an outer-loop
620 vect_analyze_scalar_cycles_1 (loop_vec_info loop_vinfo
, struct loop
*loop
)
622 basic_block bb
= loop
->header
;
624 auto_vec
<gimple
, 64> worklist
;
625 gimple_stmt_iterator gsi
;
628 if (dump_enabled_p ())
629 dump_printf_loc (MSG_NOTE
, vect_location
,
630 "=== vect_analyze_scalar_cycles ===\n");
632 /* First - identify all inductions. Reduction detection assumes that all the
633 inductions have been identified, therefore, this order must not be
635 for (gsi
= gsi_start_phis (bb
); !gsi_end_p (gsi
); gsi_next (&gsi
))
637 gimple phi
= gsi_stmt (gsi
);
638 tree access_fn
= NULL
;
639 tree def
= PHI_RESULT (phi
);
640 stmt_vec_info stmt_vinfo
= vinfo_for_stmt (phi
);
642 if (dump_enabled_p ())
644 dump_printf_loc (MSG_NOTE
, vect_location
, "Analyze phi: ");
645 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, phi
, 0);
646 dump_printf (MSG_NOTE
, "\n");
649 /* Skip virtual phi's. The data dependences that are associated with
650 virtual defs/uses (i.e., memory accesses) are analyzed elsewhere. */
651 if (virtual_operand_p (def
))
654 STMT_VINFO_DEF_TYPE (stmt_vinfo
) = vect_unknown_def_type
;
656 /* Analyze the evolution function. */
657 access_fn
= analyze_scalar_evolution (loop
, def
);
660 STRIP_NOPS (access_fn
);
661 if (dump_enabled_p ())
663 dump_printf_loc (MSG_NOTE
, vect_location
,
664 "Access function of PHI: ");
665 dump_generic_expr (MSG_NOTE
, TDF_SLIM
, access_fn
);
666 dump_printf (MSG_NOTE
, "\n");
668 STMT_VINFO_LOOP_PHI_EVOLUTION_PART (stmt_vinfo
)
669 = evolution_part_in_loop_num (access_fn
, loop
->num
);
673 || !vect_is_simple_iv_evolution (loop
->num
, access_fn
, &init
, &step
)
674 || (LOOP_VINFO_LOOP (loop_vinfo
) != loop
675 && TREE_CODE (step
) != INTEGER_CST
))
677 worklist
.safe_push (phi
);
681 gcc_assert (STMT_VINFO_LOOP_PHI_EVOLUTION_PART (stmt_vinfo
) != NULL_TREE
);
683 if (dump_enabled_p ())
684 dump_printf_loc (MSG_NOTE
, vect_location
, "Detected induction.\n");
685 STMT_VINFO_DEF_TYPE (stmt_vinfo
) = vect_induction_def
;
689 /* Second - identify all reductions and nested cycles. */
690 while (worklist
.length () > 0)
692 gimple phi
= worklist
.pop ();
693 tree def
= PHI_RESULT (phi
);
694 stmt_vec_info stmt_vinfo
= vinfo_for_stmt (phi
);
698 if (dump_enabled_p ())
700 dump_printf_loc (MSG_NOTE
, vect_location
, "Analyze phi: ");
701 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, phi
, 0);
702 dump_printf (MSG_NOTE
, "\n");
705 gcc_assert (!virtual_operand_p (def
)
706 && STMT_VINFO_DEF_TYPE (stmt_vinfo
) == vect_unknown_def_type
);
708 nested_cycle
= (loop
!= LOOP_VINFO_LOOP (loop_vinfo
));
709 reduc_stmt
= vect_force_simple_reduction (loop_vinfo
, phi
, !nested_cycle
,
715 if (dump_enabled_p ())
716 dump_printf_loc (MSG_NOTE
, vect_location
,
717 "Detected double reduction.\n");
719 STMT_VINFO_DEF_TYPE (stmt_vinfo
) = vect_double_reduction_def
;
720 STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt
)) =
721 vect_double_reduction_def
;
727 if (dump_enabled_p ())
728 dump_printf_loc (MSG_NOTE
, vect_location
,
729 "Detected vectorizable nested cycle.\n");
731 STMT_VINFO_DEF_TYPE (stmt_vinfo
) = vect_nested_cycle
;
732 STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt
)) =
737 if (dump_enabled_p ())
738 dump_printf_loc (MSG_NOTE
, vect_location
,
739 "Detected reduction.\n");
741 STMT_VINFO_DEF_TYPE (stmt_vinfo
) = vect_reduction_def
;
742 STMT_VINFO_DEF_TYPE (vinfo_for_stmt (reduc_stmt
)) =
744 /* Store the reduction cycles for possible vectorization in
746 LOOP_VINFO_REDUCTIONS (loop_vinfo
).safe_push (reduc_stmt
);
751 if (dump_enabled_p ())
752 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
753 "Unknown def-use cycle pattern.\n");
758 /* Function vect_analyze_scalar_cycles.
760 Examine the cross iteration def-use cycles of scalar variables, by
761 analyzing the loop-header PHIs of scalar variables. Classify each
762 cycle as one of the following: invariant, induction, reduction, unknown.
763 We do that for the loop represented by LOOP_VINFO, and also to its
764 inner-loop, if exists.
765 Examples for scalar cycles:
780 vect_analyze_scalar_cycles (loop_vec_info loop_vinfo
)
782 struct loop
*loop
= LOOP_VINFO_LOOP (loop_vinfo
);
784 vect_analyze_scalar_cycles_1 (loop_vinfo
, loop
);
786 /* When vectorizing an outer-loop, the inner-loop is executed sequentially.
787 Reductions in such inner-loop therefore have different properties than
788 the reductions in the nest that gets vectorized:
789 1. When vectorized, they are executed in the same order as in the original
790 scalar loop, so we can't change the order of computation when
792 2. FIXME: Inner-loop reductions can be used in the inner-loop, so the
793 current checks are too strict. */
796 vect_analyze_scalar_cycles_1 (loop_vinfo
, loop
->inner
);
800 /* Function vect_get_loop_niters.
802 Determine how many iterations the loop is executed and place it
803 in NUMBER_OF_ITERATIONS. Place the number of latch iterations
804 in NUMBER_OF_ITERATIONSM1.
806 Return the loop exit condition. */
809 vect_get_loop_niters (struct loop
*loop
, tree
*number_of_iterations
,
810 tree
*number_of_iterationsm1
)
814 if (dump_enabled_p ())
815 dump_printf_loc (MSG_NOTE
, vect_location
,
816 "=== get_loop_niters ===\n");
818 niters
= number_of_latch_executions (loop
);
819 *number_of_iterationsm1
= niters
;
821 /* We want the number of loop header executions which is the number
822 of latch executions plus one.
823 ??? For UINT_MAX latch executions this number overflows to zero
824 for loops like do { n++; } while (n != 0); */
825 if (niters
&& !chrec_contains_undetermined (niters
))
826 niters
= fold_build2 (PLUS_EXPR
, TREE_TYPE (niters
), unshare_expr (niters
),
827 build_int_cst (TREE_TYPE (niters
), 1));
828 *number_of_iterations
= niters
;
830 return get_loop_exit_condition (loop
);
834 /* Function bb_in_loop_p
836 Used as predicate for dfs order traversal of the loop bbs. */
839 bb_in_loop_p (const_basic_block bb
, const void *data
)
841 const struct loop
*const loop
= (const struct loop
*)data
;
842 if (flow_bb_inside_loop_p (loop
, bb
))
848 /* Function new_loop_vec_info.
850 Create and initialize a new loop_vec_info struct for LOOP, as well as
851 stmt_vec_info structs for all the stmts in LOOP. */
854 new_loop_vec_info (struct loop
*loop
)
858 gimple_stmt_iterator si
;
859 unsigned int i
, nbbs
;
861 res
= (loop_vec_info
) xcalloc (1, sizeof (struct _loop_vec_info
));
862 LOOP_VINFO_LOOP (res
) = loop
;
864 bbs
= get_loop_body (loop
);
866 /* Create/Update stmt_info for all stmts in the loop. */
867 for (i
= 0; i
< loop
->num_nodes
; i
++)
869 basic_block bb
= bbs
[i
];
871 /* BBs in a nested inner-loop will have been already processed (because
872 we will have called vect_analyze_loop_form for any nested inner-loop).
873 Therefore, for stmts in an inner-loop we just want to update the
874 STMT_VINFO_LOOP_VINFO field of their stmt_info to point to the new
875 loop_info of the outer-loop we are currently considering to vectorize
876 (instead of the loop_info of the inner-loop).
877 For stmts in other BBs we need to create a stmt_info from scratch. */
878 if (bb
->loop_father
!= loop
)
881 gcc_assert (loop
->inner
&& bb
->loop_father
== loop
->inner
);
882 for (si
= gsi_start_phis (bb
); !gsi_end_p (si
); gsi_next (&si
))
884 gimple phi
= gsi_stmt (si
);
885 stmt_vec_info stmt_info
= vinfo_for_stmt (phi
);
886 loop_vec_info inner_loop_vinfo
=
887 STMT_VINFO_LOOP_VINFO (stmt_info
);
888 gcc_assert (loop
->inner
== LOOP_VINFO_LOOP (inner_loop_vinfo
));
889 STMT_VINFO_LOOP_VINFO (stmt_info
) = res
;
891 for (si
= gsi_start_bb (bb
); !gsi_end_p (si
); gsi_next (&si
))
893 gimple stmt
= gsi_stmt (si
);
894 stmt_vec_info stmt_info
= vinfo_for_stmt (stmt
);
895 loop_vec_info inner_loop_vinfo
=
896 STMT_VINFO_LOOP_VINFO (stmt_info
);
897 gcc_assert (loop
->inner
== LOOP_VINFO_LOOP (inner_loop_vinfo
));
898 STMT_VINFO_LOOP_VINFO (stmt_info
) = res
;
903 /* bb in current nest. */
904 for (si
= gsi_start_phis (bb
); !gsi_end_p (si
); gsi_next (&si
))
906 gimple phi
= gsi_stmt (si
);
907 gimple_set_uid (phi
, 0);
908 set_vinfo_for_stmt (phi
, new_stmt_vec_info (phi
, res
, NULL
));
911 for (si
= gsi_start_bb (bb
); !gsi_end_p (si
); gsi_next (&si
))
913 gimple stmt
= gsi_stmt (si
);
914 gimple_set_uid (stmt
, 0);
915 set_vinfo_for_stmt (stmt
, new_stmt_vec_info (stmt
, res
, NULL
));
920 /* CHECKME: We want to visit all BBs before their successors (except for
921 latch blocks, for which this assertion wouldn't hold). In the simple
922 case of the loop forms we allow, a dfs order of the BBs would the same
923 as reversed postorder traversal, so we are safe. */
926 bbs
= XCNEWVEC (basic_block
, loop
->num_nodes
);
927 nbbs
= dfs_enumerate_from (loop
->header
, 0, bb_in_loop_p
,
928 bbs
, loop
->num_nodes
, loop
);
929 gcc_assert (nbbs
== loop
->num_nodes
);
931 LOOP_VINFO_BBS (res
) = bbs
;
932 LOOP_VINFO_NITERSM1 (res
) = NULL
;
933 LOOP_VINFO_NITERS (res
) = NULL
;
934 LOOP_VINFO_NITERS_UNCHANGED (res
) = NULL
;
935 LOOP_VINFO_COST_MODEL_MIN_ITERS (res
) = 0;
936 LOOP_VINFO_COST_MODEL_THRESHOLD (res
) = 0;
937 LOOP_VINFO_VECTORIZABLE_P (res
) = 0;
938 LOOP_VINFO_PEELING_FOR_ALIGNMENT (res
) = 0;
939 LOOP_VINFO_VECT_FACTOR (res
) = 0;
940 LOOP_VINFO_LOOP_NEST (res
).create (3);
941 LOOP_VINFO_DATAREFS (res
).create (10);
942 LOOP_VINFO_DDRS (res
).create (10 * 10);
943 LOOP_VINFO_UNALIGNED_DR (res
) = NULL
;
944 LOOP_VINFO_MAY_MISALIGN_STMTS (res
).create (
945 PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIGNMENT_CHECKS
));
946 LOOP_VINFO_MAY_ALIAS_DDRS (res
).create (
947 PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIAS_CHECKS
));
948 LOOP_VINFO_GROUPED_STORES (res
).create (10);
949 LOOP_VINFO_REDUCTIONS (res
).create (10);
950 LOOP_VINFO_REDUCTION_CHAINS (res
).create (10);
951 LOOP_VINFO_SLP_INSTANCES (res
).create (10);
952 LOOP_VINFO_SLP_UNROLLING_FACTOR (res
) = 1;
953 LOOP_VINFO_TARGET_COST_DATA (res
) = init_cost (loop
);
954 LOOP_VINFO_PEELING_FOR_GAPS (res
) = false;
955 LOOP_VINFO_PEELING_FOR_NITER (res
) = false;
956 LOOP_VINFO_OPERANDS_SWAPPED (res
) = false;
962 /* Function destroy_loop_vec_info.
964 Free LOOP_VINFO struct, as well as all the stmt_vec_info structs of all the
965 stmts in the loop. */
968 destroy_loop_vec_info (loop_vec_info loop_vinfo
, bool clean_stmts
)
973 gimple_stmt_iterator si
;
975 vec
<slp_instance
> slp_instances
;
976 slp_instance instance
;
982 loop
= LOOP_VINFO_LOOP (loop_vinfo
);
984 bbs
= LOOP_VINFO_BBS (loop_vinfo
);
985 nbbs
= clean_stmts
? loop
->num_nodes
: 0;
986 swapped
= LOOP_VINFO_OPERANDS_SWAPPED (loop_vinfo
);
988 for (j
= 0; j
< nbbs
; j
++)
990 basic_block bb
= bbs
[j
];
991 for (si
= gsi_start_phis (bb
); !gsi_end_p (si
); gsi_next (&si
))
992 free_stmt_vec_info (gsi_stmt (si
));
994 for (si
= gsi_start_bb (bb
); !gsi_end_p (si
); )
996 gimple stmt
= gsi_stmt (si
);
998 /* We may have broken canonical form by moving a constant
999 into RHS1 of a commutative op. Fix such occurrences. */
1000 if (swapped
&& is_gimple_assign (stmt
))
1002 enum tree_code code
= gimple_assign_rhs_code (stmt
);
1004 if ((code
== PLUS_EXPR
1005 || code
== POINTER_PLUS_EXPR
1006 || code
== MULT_EXPR
)
1007 && CONSTANT_CLASS_P (gimple_assign_rhs1 (stmt
)))
1008 swap_ssa_operands (stmt
,
1009 gimple_assign_rhs1_ptr (stmt
),
1010 gimple_assign_rhs2_ptr (stmt
));
1013 /* Free stmt_vec_info. */
1014 free_stmt_vec_info (stmt
);
1019 free (LOOP_VINFO_BBS (loop_vinfo
));
1020 vect_destroy_datarefs (loop_vinfo
, NULL
);
1021 free_dependence_relations (LOOP_VINFO_DDRS (loop_vinfo
));
1022 LOOP_VINFO_LOOP_NEST (loop_vinfo
).release ();
1023 LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo
).release ();
1024 LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo
).release ();
1025 slp_instances
= LOOP_VINFO_SLP_INSTANCES (loop_vinfo
);
1026 FOR_EACH_VEC_ELT (slp_instances
, j
, instance
)
1027 vect_free_slp_instance (instance
);
1029 LOOP_VINFO_SLP_INSTANCES (loop_vinfo
).release ();
1030 LOOP_VINFO_GROUPED_STORES (loop_vinfo
).release ();
1031 LOOP_VINFO_REDUCTIONS (loop_vinfo
).release ();
1032 LOOP_VINFO_REDUCTION_CHAINS (loop_vinfo
).release ();
1034 if (LOOP_VINFO_PEELING_HTAB (loop_vinfo
).is_created ())
1035 LOOP_VINFO_PEELING_HTAB (loop_vinfo
).dispose ();
1037 destroy_cost_data (LOOP_VINFO_TARGET_COST_DATA (loop_vinfo
));
1044 /* Function vect_analyze_loop_1.
1046 Apply a set of analyses on LOOP, and create a loop_vec_info struct
1047 for it. The different analyses will record information in the
1048 loop_vec_info struct. This is a subset of the analyses applied in
1049 vect_analyze_loop, to be applied on an inner-loop nested in the loop
1050 that is now considered for (outer-loop) vectorization. */
1052 static loop_vec_info
1053 vect_analyze_loop_1 (struct loop
*loop
)
1055 loop_vec_info loop_vinfo
;
1057 if (dump_enabled_p ())
1058 dump_printf_loc (MSG_NOTE
, vect_location
,
1059 "===== analyze_loop_nest_1 =====\n");
1061 /* Check the CFG characteristics of the loop (nesting, entry/exit, etc. */
1063 loop_vinfo
= vect_analyze_loop_form (loop
);
1066 if (dump_enabled_p ())
1067 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1068 "bad inner-loop form.\n");
1076 /* Function vect_analyze_loop_form.
1078 Verify that certain CFG restrictions hold, including:
1079 - the loop has a pre-header
1080 - the loop has a single entry and exit
1081 - the loop exit condition is simple enough, and the number of iterations
1082 can be analyzed (a countable loop). */
1085 vect_analyze_loop_form (struct loop
*loop
)
1087 loop_vec_info loop_vinfo
;
1089 tree number_of_iterations
= NULL
, number_of_iterationsm1
= NULL
;
1090 loop_vec_info inner_loop_vinfo
= NULL
;
1092 if (dump_enabled_p ())
1093 dump_printf_loc (MSG_NOTE
, vect_location
,
1094 "=== vect_analyze_loop_form ===\n");
1096 /* Different restrictions apply when we are considering an inner-most loop,
1097 vs. an outer (nested) loop.
1098 (FORNOW. May want to relax some of these restrictions in the future). */
1102 /* Inner-most loop. We currently require that the number of BBs is
1103 exactly 2 (the header and latch). Vectorizable inner-most loops
1114 if (loop
->num_nodes
!= 2)
1116 if (dump_enabled_p ())
1117 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1118 "not vectorized: control flow in loop.\n");
1122 if (empty_block_p (loop
->header
))
1124 if (dump_enabled_p ())
1125 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1126 "not vectorized: empty loop.\n");
1132 struct loop
*innerloop
= loop
->inner
;
1135 /* Nested loop. We currently require that the loop is doubly-nested,
1136 contains a single inner loop, and the number of BBs is exactly 5.
1137 Vectorizable outer-loops look like this:
1149 The inner-loop has the properties expected of inner-most loops
1150 as described above. */
1152 if ((loop
->inner
)->inner
|| (loop
->inner
)->next
)
1154 if (dump_enabled_p ())
1155 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1156 "not vectorized: multiple nested loops.\n");
1160 /* Analyze the inner-loop. */
1161 inner_loop_vinfo
= vect_analyze_loop_1 (loop
->inner
);
1162 if (!inner_loop_vinfo
)
1164 if (dump_enabled_p ())
1165 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1166 "not vectorized: Bad inner loop.\n");
1170 if (!expr_invariant_in_loop_p (loop
,
1171 LOOP_VINFO_NITERS (inner_loop_vinfo
)))
1173 if (dump_enabled_p ())
1174 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1175 "not vectorized: inner-loop count not"
1177 destroy_loop_vec_info (inner_loop_vinfo
, true);
1181 if (loop
->num_nodes
!= 5)
1183 if (dump_enabled_p ())
1184 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1185 "not vectorized: control flow in loop.\n");
1186 destroy_loop_vec_info (inner_loop_vinfo
, true);
1190 gcc_assert (EDGE_COUNT (innerloop
->header
->preds
) == 2);
1191 entryedge
= EDGE_PRED (innerloop
->header
, 0);
1192 if (EDGE_PRED (innerloop
->header
, 0)->src
== innerloop
->latch
)
1193 entryedge
= EDGE_PRED (innerloop
->header
, 1);
1195 if (entryedge
->src
!= loop
->header
1196 || !single_exit (innerloop
)
1197 || single_exit (innerloop
)->dest
!= EDGE_PRED (loop
->latch
, 0)->src
)
1199 if (dump_enabled_p ())
1200 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1201 "not vectorized: unsupported outerloop form.\n");
1202 destroy_loop_vec_info (inner_loop_vinfo
, true);
1206 if (dump_enabled_p ())
1207 dump_printf_loc (MSG_NOTE
, vect_location
,
1208 "Considering outer-loop vectorization.\n");
1211 if (!single_exit (loop
)
1212 || EDGE_COUNT (loop
->header
->preds
) != 2)
1214 if (dump_enabled_p ())
1216 if (!single_exit (loop
))
1217 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1218 "not vectorized: multiple exits.\n");
1219 else if (EDGE_COUNT (loop
->header
->preds
) != 2)
1220 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1221 "not vectorized: too many incoming edges.\n");
1223 if (inner_loop_vinfo
)
1224 destroy_loop_vec_info (inner_loop_vinfo
, true);
1228 /* We assume that the loop exit condition is at the end of the loop. i.e,
1229 that the loop is represented as a do-while (with a proper if-guard
1230 before the loop if needed), where the loop header contains all the
1231 executable statements, and the latch is empty. */
1232 if (!empty_block_p (loop
->latch
)
1233 || !gimple_seq_empty_p (phi_nodes (loop
->latch
)))
1235 if (dump_enabled_p ())
1236 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1237 "not vectorized: latch block not empty.\n");
1238 if (inner_loop_vinfo
)
1239 destroy_loop_vec_info (inner_loop_vinfo
, true);
1243 /* Make sure there exists a single-predecessor exit bb: */
1244 if (!single_pred_p (single_exit (loop
)->dest
))
1246 edge e
= single_exit (loop
);
1247 if (!(e
->flags
& EDGE_ABNORMAL
))
1249 split_loop_exit_edge (e
);
1250 if (dump_enabled_p ())
1251 dump_printf (MSG_NOTE
, "split exit edge.\n");
1255 if (dump_enabled_p ())
1256 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1257 "not vectorized: abnormal loop exit edge.\n");
1258 if (inner_loop_vinfo
)
1259 destroy_loop_vec_info (inner_loop_vinfo
, true);
1264 loop_cond
= vect_get_loop_niters (loop
, &number_of_iterations
,
1265 &number_of_iterationsm1
);
1268 if (dump_enabled_p ())
1269 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1270 "not vectorized: complicated exit condition.\n");
1271 if (inner_loop_vinfo
)
1272 destroy_loop_vec_info (inner_loop_vinfo
, true);
1276 if (!number_of_iterations
1277 || chrec_contains_undetermined (number_of_iterations
))
1279 if (dump_enabled_p ())
1280 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1281 "not vectorized: number of iterations cannot be "
1283 if (inner_loop_vinfo
)
1284 destroy_loop_vec_info (inner_loop_vinfo
, true);
1288 if (integer_zerop (number_of_iterations
))
1290 if (dump_enabled_p ())
1291 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1292 "not vectorized: number of iterations = 0.\n");
1293 if (inner_loop_vinfo
)
1294 destroy_loop_vec_info (inner_loop_vinfo
, true);
1298 loop_vinfo
= new_loop_vec_info (loop
);
1299 LOOP_VINFO_NITERSM1 (loop_vinfo
) = number_of_iterationsm1
;
1300 LOOP_VINFO_NITERS (loop_vinfo
) = number_of_iterations
;
1301 LOOP_VINFO_NITERS_UNCHANGED (loop_vinfo
) = number_of_iterations
;
1303 if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo
))
1305 if (dump_enabled_p ())
1307 dump_printf_loc (MSG_NOTE
, vect_location
,
1308 "Symbolic number of iterations is ");
1309 dump_generic_expr (MSG_NOTE
, TDF_DETAILS
, number_of_iterations
);
1310 dump_printf (MSG_NOTE
, "\n");
1314 STMT_VINFO_TYPE (vinfo_for_stmt (loop_cond
)) = loop_exit_ctrl_vec_info_type
;
1316 /* CHECKME: May want to keep it around it in the future. */
1317 if (inner_loop_vinfo
)
1318 destroy_loop_vec_info (inner_loop_vinfo
, false);
1320 gcc_assert (!loop
->aux
);
1321 loop
->aux
= loop_vinfo
;
1326 /* Function vect_analyze_loop_operations.
1328 Scan the loop stmts and make sure they are all vectorizable. */
1331 vect_analyze_loop_operations (loop_vec_info loop_vinfo
, bool slp
)
1333 struct loop
*loop
= LOOP_VINFO_LOOP (loop_vinfo
);
1334 basic_block
*bbs
= LOOP_VINFO_BBS (loop_vinfo
);
1335 int nbbs
= loop
->num_nodes
;
1336 gimple_stmt_iterator si
;
1337 unsigned int vectorization_factor
= 0;
1340 stmt_vec_info stmt_info
;
1341 bool need_to_vectorize
= false;
1342 int min_profitable_iters
;
1343 int min_scalar_loop_bound
;
1345 bool only_slp_in_loop
= true, ok
;
1346 HOST_WIDE_INT max_niter
;
1347 HOST_WIDE_INT estimated_niter
;
1348 int min_profitable_estimate
;
1350 if (dump_enabled_p ())
1351 dump_printf_loc (MSG_NOTE
, vect_location
,
1352 "=== vect_analyze_loop_operations ===\n");
1354 gcc_assert (LOOP_VINFO_VECT_FACTOR (loop_vinfo
));
1355 vectorization_factor
= LOOP_VINFO_VECT_FACTOR (loop_vinfo
);
1358 /* If all the stmts in the loop can be SLPed, we perform only SLP, and
1359 vectorization factor of the loop is the unrolling factor required by
1360 the SLP instances. If that unrolling factor is 1, we say, that we
1361 perform pure SLP on loop - cross iteration parallelism is not
1363 for (i
= 0; i
< nbbs
; i
++)
1365 basic_block bb
= bbs
[i
];
1366 for (si
= gsi_start_bb (bb
); !gsi_end_p (si
); gsi_next (&si
))
1368 gimple stmt
= gsi_stmt (si
);
1369 stmt_vec_info stmt_info
= vinfo_for_stmt (stmt
);
1370 gcc_assert (stmt_info
);
1371 if ((STMT_VINFO_RELEVANT_P (stmt_info
)
1372 || VECTORIZABLE_CYCLE_DEF (STMT_VINFO_DEF_TYPE (stmt_info
)))
1373 && !PURE_SLP_STMT (stmt_info
))
1374 /* STMT needs both SLP and loop-based vectorization. */
1375 only_slp_in_loop
= false;
1379 if (only_slp_in_loop
)
1380 vectorization_factor
= LOOP_VINFO_SLP_UNROLLING_FACTOR (loop_vinfo
);
1382 vectorization_factor
= least_common_multiple (vectorization_factor
,
1383 LOOP_VINFO_SLP_UNROLLING_FACTOR (loop_vinfo
));
1385 LOOP_VINFO_VECT_FACTOR (loop_vinfo
) = vectorization_factor
;
1386 if (dump_enabled_p ())
1387 dump_printf_loc (MSG_NOTE
, vect_location
,
1388 "Updating vectorization factor to %d\n",
1389 vectorization_factor
);
1392 for (i
= 0; i
< nbbs
; i
++)
1394 basic_block bb
= bbs
[i
];
1396 for (si
= gsi_start_phis (bb
); !gsi_end_p (si
); gsi_next (&si
))
1398 phi
= gsi_stmt (si
);
1401 stmt_info
= vinfo_for_stmt (phi
);
1402 if (dump_enabled_p ())
1404 dump_printf_loc (MSG_NOTE
, vect_location
, "examining phi: ");
1405 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, phi
, 0);
1406 dump_printf (MSG_NOTE
, "\n");
1409 /* Inner-loop loop-closed exit phi in outer-loop vectorization
1410 (i.e., a phi in the tail of the outer-loop). */
1411 if (! is_loop_header_bb_p (bb
))
1413 /* FORNOW: we currently don't support the case that these phis
1414 are not used in the outerloop (unless it is double reduction,
1415 i.e., this phi is vect_reduction_def), cause this case
1416 requires to actually do something here. */
1417 if ((!STMT_VINFO_RELEVANT_P (stmt_info
)
1418 || STMT_VINFO_LIVE_P (stmt_info
))
1419 && STMT_VINFO_DEF_TYPE (stmt_info
)
1420 != vect_double_reduction_def
)
1422 if (dump_enabled_p ())
1423 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1424 "Unsupported loop-closed phi in "
1429 /* If PHI is used in the outer loop, we check that its operand
1430 is defined in the inner loop. */
1431 if (STMT_VINFO_RELEVANT_P (stmt_info
))
1436 if (gimple_phi_num_args (phi
) != 1)
1439 phi_op
= PHI_ARG_DEF (phi
, 0);
1440 if (TREE_CODE (phi_op
) != SSA_NAME
)
1443 op_def_stmt
= SSA_NAME_DEF_STMT (phi_op
);
1444 if (gimple_nop_p (op_def_stmt
)
1445 || !flow_bb_inside_loop_p (loop
, gimple_bb (op_def_stmt
))
1446 || !vinfo_for_stmt (op_def_stmt
))
1449 if (STMT_VINFO_RELEVANT (vinfo_for_stmt (op_def_stmt
))
1450 != vect_used_in_outer
1451 && STMT_VINFO_RELEVANT (vinfo_for_stmt (op_def_stmt
))
1452 != vect_used_in_outer_by_reduction
)
1459 gcc_assert (stmt_info
);
1461 if (STMT_VINFO_LIVE_P (stmt_info
))
1463 /* FORNOW: not yet supported. */
1464 if (dump_enabled_p ())
1465 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1466 "not vectorized: value used after loop.\n");
1470 if (STMT_VINFO_RELEVANT (stmt_info
) == vect_used_in_scope
1471 && STMT_VINFO_DEF_TYPE (stmt_info
) != vect_induction_def
)
1473 /* A scalar-dependence cycle that we don't support. */
1474 if (dump_enabled_p ())
1475 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1476 "not vectorized: scalar dependence cycle.\n");
1480 if (STMT_VINFO_RELEVANT_P (stmt_info
))
1482 need_to_vectorize
= true;
1483 if (STMT_VINFO_DEF_TYPE (stmt_info
) == vect_induction_def
)
1484 ok
= vectorizable_induction (phi
, NULL
, NULL
);
1489 if (dump_enabled_p ())
1491 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1492 "not vectorized: relevant phi not "
1494 dump_gimple_stmt (MSG_MISSED_OPTIMIZATION
, TDF_SLIM
, phi
, 0);
1495 dump_printf (MSG_MISSED_OPTIMIZATION
, "\n");
1501 for (si
= gsi_start_bb (bb
); !gsi_end_p (si
); gsi_next (&si
))
1503 gimple stmt
= gsi_stmt (si
);
1504 if (!gimple_clobber_p (stmt
)
1505 && !vect_analyze_stmt (stmt
, &need_to_vectorize
, NULL
))
1510 /* All operations in the loop are either irrelevant (deal with loop
1511 control, or dead), or only used outside the loop and can be moved
1512 out of the loop (e.g. invariants, inductions). The loop can be
1513 optimized away by scalar optimizations. We're better off not
1514 touching this loop. */
1515 if (!need_to_vectorize
)
1517 if (dump_enabled_p ())
1518 dump_printf_loc (MSG_NOTE
, vect_location
,
1519 "All the computation can be taken out of the loop.\n");
1520 if (dump_enabled_p ())
1521 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1522 "not vectorized: redundant loop. no profit to "
1527 if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo
) && dump_enabled_p ())
1528 dump_printf_loc (MSG_NOTE
, vect_location
,
1529 "vectorization_factor = %d, niters = "
1530 HOST_WIDE_INT_PRINT_DEC
"\n", vectorization_factor
,
1531 LOOP_VINFO_INT_NITERS (loop_vinfo
));
1533 if ((LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo
)
1534 && (LOOP_VINFO_INT_NITERS (loop_vinfo
) < vectorization_factor
))
1535 || ((max_niter
= max_stmt_executions_int (loop
)) != -1
1536 && (unsigned HOST_WIDE_INT
) max_niter
< vectorization_factor
))
1538 if (dump_enabled_p ())
1539 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1540 "not vectorized: iteration count too small.\n");
1541 if (dump_enabled_p ())
1542 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1543 "not vectorized: iteration count smaller than "
1544 "vectorization factor.\n");
1548 /* Analyze cost. Decide if worth while to vectorize. */
1550 /* Once VF is set, SLP costs should be updated since the number of created
1551 vector stmts depends on VF. */
1552 vect_update_slp_costs_according_to_vf (loop_vinfo
);
1554 vect_estimate_min_profitable_iters (loop_vinfo
, &min_profitable_iters
,
1555 &min_profitable_estimate
);
1556 LOOP_VINFO_COST_MODEL_MIN_ITERS (loop_vinfo
) = min_profitable_iters
;
1558 if (min_profitable_iters
< 0)
1560 if (dump_enabled_p ())
1561 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1562 "not vectorized: vectorization not profitable.\n");
1563 if (dump_enabled_p ())
1564 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1565 "not vectorized: vector version will never be "
1570 min_scalar_loop_bound
= ((PARAM_VALUE (PARAM_MIN_VECT_LOOP_BOUND
)
1571 * vectorization_factor
) - 1);
1574 /* Use the cost model only if it is more conservative than user specified
1577 th
= (unsigned) min_scalar_loop_bound
;
1578 if (min_profitable_iters
1579 && (!min_scalar_loop_bound
1580 || min_profitable_iters
> min_scalar_loop_bound
))
1581 th
= (unsigned) min_profitable_iters
;
1583 LOOP_VINFO_COST_MODEL_THRESHOLD (loop_vinfo
) = th
;
1585 if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo
)
1586 && LOOP_VINFO_INT_NITERS (loop_vinfo
) <= th
)
1588 if (dump_enabled_p ())
1589 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1590 "not vectorized: vectorization not profitable.\n");
1591 if (dump_enabled_p ())
1592 dump_printf_loc (MSG_NOTE
, vect_location
,
1593 "not vectorized: iteration count smaller than user "
1594 "specified loop bound parameter or minimum profitable "
1595 "iterations (whichever is more conservative).\n");
1599 if ((estimated_niter
= estimated_stmt_executions_int (loop
)) != -1
1600 && ((unsigned HOST_WIDE_INT
) estimated_niter
1601 <= MAX (th
, (unsigned)min_profitable_estimate
)))
1603 if (dump_enabled_p ())
1604 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1605 "not vectorized: estimated iteration count too "
1607 if (dump_enabled_p ())
1608 dump_printf_loc (MSG_NOTE
, vect_location
,
1609 "not vectorized: estimated iteration count smaller "
1610 "than specified loop bound parameter or minimum "
1611 "profitable iterations (whichever is more "
1612 "conservative).\n");
1620 /* Function vect_analyze_loop_2.
1622 Apply a set of analyses on LOOP, and create a loop_vec_info struct
1623 for it. The different analyses will record information in the
1624 loop_vec_info struct. */
1626 vect_analyze_loop_2 (loop_vec_info loop_vinfo
)
1628 bool ok
, slp
= false;
1629 int max_vf
= MAX_VECTORIZATION_FACTOR
;
1632 unsigned int n_stmts
= 0;
1634 /* Find all data references in the loop (which correspond to vdefs/vuses)
1635 and analyze their evolution in the loop. Also adjust the minimal
1636 vectorization factor according to the loads and stores.
1638 FORNOW: Handle only simple, array references, which
1639 alignment can be forced, and aligned pointer-references. */
1641 ok
= vect_analyze_data_refs (loop_vinfo
, NULL
, &min_vf
, &n_stmts
);
1644 if (dump_enabled_p ())
1645 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1646 "bad data references.\n");
1650 /* Analyze the access patterns of the data-refs in the loop (consecutive,
1651 complex, etc.). FORNOW: Only handle consecutive access pattern. */
1653 ok
= vect_analyze_data_ref_accesses (loop_vinfo
, NULL
);
1656 if (dump_enabled_p ())
1657 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1658 "bad data access.\n");
1662 /* Classify all cross-iteration scalar data-flow cycles.
1663 Cross-iteration cycles caused by virtual phis are analyzed separately. */
1665 vect_analyze_scalar_cycles (loop_vinfo
);
1667 vect_pattern_recog (loop_vinfo
, NULL
);
1669 /* Data-flow analysis to detect stmts that do not need to be vectorized. */
1671 ok
= vect_mark_stmts_to_be_vectorized (loop_vinfo
);
1674 if (dump_enabled_p ())
1675 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1676 "unexpected pattern.\n");
1680 /* Analyze data dependences between the data-refs in the loop
1681 and adjust the maximum vectorization factor according to
1683 FORNOW: fail at the first data dependence that we encounter. */
1685 ok
= vect_analyze_data_ref_dependences (loop_vinfo
, &max_vf
);
1689 if (dump_enabled_p ())
1690 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1691 "bad data dependence.\n");
1695 ok
= vect_determine_vectorization_factor (loop_vinfo
);
1698 if (dump_enabled_p ())
1699 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1700 "can't determine vectorization factor.\n");
1703 if (max_vf
< LOOP_VINFO_VECT_FACTOR (loop_vinfo
))
1705 if (dump_enabled_p ())
1706 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1707 "bad data dependence.\n");
1711 /* Analyze the alignment of the data-refs in the loop.
1712 Fail if a data reference is found that cannot be vectorized. */
1714 ok
= vect_analyze_data_refs_alignment (loop_vinfo
, NULL
);
1717 if (dump_enabled_p ())
1718 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1719 "bad data alignment.\n");
1723 /* Prune the list of ddrs to be tested at run-time by versioning for alias.
1724 It is important to call pruning after vect_analyze_data_ref_accesses,
1725 since we use grouping information gathered by interleaving analysis. */
1726 ok
= vect_prune_runtime_alias_test_list (loop_vinfo
);
1729 if (dump_enabled_p ())
1730 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1731 "number of versioning for alias "
1732 "run-time tests exceeds %d "
1733 "(--param vect-max-version-for-alias-checks)\n",
1734 PARAM_VALUE (PARAM_VECT_MAX_VERSION_FOR_ALIAS_CHECKS
));
1738 /* This pass will decide on using loop versioning and/or loop peeling in
1739 order to enhance the alignment of data references in the loop. */
1741 ok
= vect_enhance_data_refs_alignment (loop_vinfo
);
1744 if (dump_enabled_p ())
1745 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1746 "bad data alignment.\n");
1750 /* Check the SLP opportunities in the loop, analyze and build SLP trees. */
1751 ok
= vect_analyze_slp (loop_vinfo
, NULL
, n_stmts
);
1754 /* Decide which possible SLP instances to SLP. */
1755 slp
= vect_make_slp_decision (loop_vinfo
);
1757 /* Find stmts that need to be both vectorized and SLPed. */
1758 vect_detect_hybrid_slp (loop_vinfo
);
1763 /* Scan all the operations in the loop and make sure they are
1766 ok
= vect_analyze_loop_operations (loop_vinfo
, slp
);
1769 if (dump_enabled_p ())
1770 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1771 "bad operation or unsupported loop bound.\n");
1775 /* Decide whether we need to create an epilogue loop to handle
1776 remaining scalar iterations. */
1777 th
= ((LOOP_VINFO_COST_MODEL_THRESHOLD (loop_vinfo
) + 1)
1778 / LOOP_VINFO_VECT_FACTOR (loop_vinfo
))
1779 * LOOP_VINFO_VECT_FACTOR (loop_vinfo
);
1781 if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo
)
1782 && LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo
) > 0)
1784 if (ctz_hwi (LOOP_VINFO_INT_NITERS (loop_vinfo
)
1785 - LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo
))
1786 < exact_log2 (LOOP_VINFO_VECT_FACTOR (loop_vinfo
)))
1787 LOOP_VINFO_PEELING_FOR_NITER (loop_vinfo
) = true;
1789 else if (LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo
)
1790 || (tree_ctz (LOOP_VINFO_NITERS (loop_vinfo
))
1791 < (unsigned)exact_log2 (LOOP_VINFO_VECT_FACTOR (loop_vinfo
))
1792 /* In case of versioning, check if the maximum number of
1793 iterations is greater than th. If they are identical,
1794 the epilogue is unnecessary. */
1795 && ((!LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo
)
1796 && !LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo
))
1797 || (unsigned HOST_WIDE_INT
)max_stmt_executions_int
1798 (LOOP_VINFO_LOOP (loop_vinfo
)) > th
)))
1799 LOOP_VINFO_PEELING_FOR_NITER (loop_vinfo
) = true;
1801 /* If an epilogue loop is required make sure we can create one. */
1802 if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo
)
1803 || LOOP_VINFO_PEELING_FOR_NITER (loop_vinfo
))
1805 if (dump_enabled_p ())
1806 dump_printf_loc (MSG_NOTE
, vect_location
, "epilog loop required\n");
1807 if (!vect_can_advance_ivs_p (loop_vinfo
)
1808 || !slpeel_can_duplicate_loop_p (LOOP_VINFO_LOOP (loop_vinfo
),
1809 single_exit (LOOP_VINFO_LOOP
1812 if (dump_enabled_p ())
1813 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1814 "not vectorized: can't create required "
1823 /* Function vect_analyze_loop.
1825 Apply a set of analyses on LOOP, and create a loop_vec_info struct
1826 for it. The different analyses will record information in the
1827 loop_vec_info struct. */
1829 vect_analyze_loop (struct loop
*loop
)
1831 loop_vec_info loop_vinfo
;
1832 unsigned int vector_sizes
;
1834 /* Autodetect first vector size we try. */
1835 current_vector_size
= 0;
1836 vector_sizes
= targetm
.vectorize
.autovectorize_vector_sizes ();
1838 if (dump_enabled_p ())
1839 dump_printf_loc (MSG_NOTE
, vect_location
,
1840 "===== analyze_loop_nest =====\n");
1842 if (loop_outer (loop
)
1843 && loop_vec_info_for_loop (loop_outer (loop
))
1844 && LOOP_VINFO_VECTORIZABLE_P (loop_vec_info_for_loop (loop_outer (loop
))))
1846 if (dump_enabled_p ())
1847 dump_printf_loc (MSG_NOTE
, vect_location
,
1848 "outer-loop already vectorized.\n");
1854 /* Check the CFG characteristics of the loop (nesting, entry/exit). */
1855 loop_vinfo
= vect_analyze_loop_form (loop
);
1858 if (dump_enabled_p ())
1859 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
1860 "bad loop form.\n");
1864 if (vect_analyze_loop_2 (loop_vinfo
))
1866 LOOP_VINFO_VECTORIZABLE_P (loop_vinfo
) = 1;
1871 destroy_loop_vec_info (loop_vinfo
, true);
1873 vector_sizes
&= ~current_vector_size
;
1874 if (vector_sizes
== 0
1875 || current_vector_size
== 0)
1878 /* Try the next biggest vector size. */
1879 current_vector_size
= 1 << floor_log2 (vector_sizes
);
1880 if (dump_enabled_p ())
1881 dump_printf_loc (MSG_NOTE
, vect_location
,
1882 "***** Re-trying analysis with "
1883 "vector size %d\n", current_vector_size
);
1888 /* Function reduction_code_for_scalar_code
1891 CODE - tree_code of a reduction operations.
1894 REDUC_CODE - the corresponding tree-code to be used to reduce the
1895 vector of partial results into a single scalar result (which
1896 will also reside in a vector) or ERROR_MARK if the operation is
1897 a supported reduction operation, but does not have such tree-code.
1899 Return FALSE if CODE currently cannot be vectorized as reduction. */
1902 reduction_code_for_scalar_code (enum tree_code code
,
1903 enum tree_code
*reduc_code
)
1908 *reduc_code
= REDUC_MAX_EXPR
;
1912 *reduc_code
= REDUC_MIN_EXPR
;
1916 *reduc_code
= REDUC_PLUS_EXPR
;
1924 *reduc_code
= ERROR_MARK
;
1933 /* Error reporting helper for vect_is_simple_reduction below. GIMPLE statement
1934 STMT is printed with a message MSG. */
1937 report_vect_op (int msg_type
, gimple stmt
, const char *msg
)
1939 dump_printf_loc (msg_type
, vect_location
, "%s", msg
);
1940 dump_gimple_stmt (msg_type
, TDF_SLIM
, stmt
, 0);
1941 dump_printf (msg_type
, "\n");
1945 /* Detect SLP reduction of the form:
1955 PHI is the reduction phi node (#a1 = phi <a5, a0> above)
1956 FIRST_STMT is the first reduction stmt in the chain
1957 (a2 = operation (a1)).
1959 Return TRUE if a reduction chain was detected. */
1962 vect_is_slp_reduction (loop_vec_info loop_info
, gimple phi
, gimple first_stmt
)
1964 struct loop
*loop
= (gimple_bb (phi
))->loop_father
;
1965 struct loop
*vect_loop
= LOOP_VINFO_LOOP (loop_info
);
1966 enum tree_code code
;
1967 gimple current_stmt
= NULL
, loop_use_stmt
= NULL
, first
, next_stmt
;
1968 stmt_vec_info use_stmt_info
, current_stmt_info
;
1970 imm_use_iterator imm_iter
;
1971 use_operand_p use_p
;
1972 int nloop_uses
, size
= 0, n_out_of_loop_uses
;
1975 if (loop
!= vect_loop
)
1978 lhs
= PHI_RESULT (phi
);
1979 code
= gimple_assign_rhs_code (first_stmt
);
1983 n_out_of_loop_uses
= 0;
1984 FOR_EACH_IMM_USE_FAST (use_p
, imm_iter
, lhs
)
1986 gimple use_stmt
= USE_STMT (use_p
);
1987 if (is_gimple_debug (use_stmt
))
1990 /* Check if we got back to the reduction phi. */
1991 if (use_stmt
== phi
)
1993 loop_use_stmt
= use_stmt
;
1998 if (flow_bb_inside_loop_p (loop
, gimple_bb (use_stmt
)))
2000 if (vinfo_for_stmt (use_stmt
)
2001 && !STMT_VINFO_IN_PATTERN_P (vinfo_for_stmt (use_stmt
)))
2003 loop_use_stmt
= use_stmt
;
2008 n_out_of_loop_uses
++;
2010 /* There are can be either a single use in the loop or two uses in
2012 if (nloop_uses
> 1 || (n_out_of_loop_uses
&& nloop_uses
))
2019 /* We reached a statement with no loop uses. */
2020 if (nloop_uses
== 0)
2023 /* This is a loop exit phi, and we haven't reached the reduction phi. */
2024 if (gimple_code (loop_use_stmt
) == GIMPLE_PHI
)
2027 if (!is_gimple_assign (loop_use_stmt
)
2028 || code
!= gimple_assign_rhs_code (loop_use_stmt
)
2029 || !flow_bb_inside_loop_p (loop
, gimple_bb (loop_use_stmt
)))
2032 /* Insert USE_STMT into reduction chain. */
2033 use_stmt_info
= vinfo_for_stmt (loop_use_stmt
);
2036 current_stmt_info
= vinfo_for_stmt (current_stmt
);
2037 GROUP_NEXT_ELEMENT (current_stmt_info
) = loop_use_stmt
;
2038 GROUP_FIRST_ELEMENT (use_stmt_info
)
2039 = GROUP_FIRST_ELEMENT (current_stmt_info
);
2042 GROUP_FIRST_ELEMENT (use_stmt_info
) = loop_use_stmt
;
2044 lhs
= gimple_assign_lhs (loop_use_stmt
);
2045 current_stmt
= loop_use_stmt
;
2049 if (!found
|| loop_use_stmt
!= phi
|| size
< 2)
2052 /* Swap the operands, if needed, to make the reduction operand be the second
2054 lhs
= PHI_RESULT (phi
);
2055 next_stmt
= GROUP_FIRST_ELEMENT (vinfo_for_stmt (current_stmt
));
2058 if (gimple_assign_rhs2 (next_stmt
) == lhs
)
2060 tree op
= gimple_assign_rhs1 (next_stmt
);
2061 gimple def_stmt
= NULL
;
2063 if (TREE_CODE (op
) == SSA_NAME
)
2064 def_stmt
= SSA_NAME_DEF_STMT (op
);
2066 /* Check that the other def is either defined in the loop
2067 ("vect_internal_def"), or it's an induction (defined by a
2068 loop-header phi-node). */
2070 && gimple_bb (def_stmt
)
2071 && flow_bb_inside_loop_p (loop
, gimple_bb (def_stmt
))
2072 && (is_gimple_assign (def_stmt
)
2073 || is_gimple_call (def_stmt
)
2074 || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt
))
2075 == vect_induction_def
2076 || (gimple_code (def_stmt
) == GIMPLE_PHI
2077 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt
))
2078 == vect_internal_def
2079 && !is_loop_header_bb_p (gimple_bb (def_stmt
)))))
2081 lhs
= gimple_assign_lhs (next_stmt
);
2082 next_stmt
= GROUP_NEXT_ELEMENT (vinfo_for_stmt (next_stmt
));
2090 tree op
= gimple_assign_rhs2 (next_stmt
);
2091 gimple def_stmt
= NULL
;
2093 if (TREE_CODE (op
) == SSA_NAME
)
2094 def_stmt
= SSA_NAME_DEF_STMT (op
);
2096 /* Check that the other def is either defined in the loop
2097 ("vect_internal_def"), or it's an induction (defined by a
2098 loop-header phi-node). */
2100 && gimple_bb (def_stmt
)
2101 && flow_bb_inside_loop_p (loop
, gimple_bb (def_stmt
))
2102 && (is_gimple_assign (def_stmt
)
2103 || is_gimple_call (def_stmt
)
2104 || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt
))
2105 == vect_induction_def
2106 || (gimple_code (def_stmt
) == GIMPLE_PHI
2107 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt
))
2108 == vect_internal_def
2109 && !is_loop_header_bb_p (gimple_bb (def_stmt
)))))
2111 if (dump_enabled_p ())
2113 dump_printf_loc (MSG_NOTE
, vect_location
, "swapping oprnds: ");
2114 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, next_stmt
, 0);
2115 dump_printf (MSG_NOTE
, "\n");
2118 swap_ssa_operands (next_stmt
,
2119 gimple_assign_rhs1_ptr (next_stmt
),
2120 gimple_assign_rhs2_ptr (next_stmt
));
2121 update_stmt (next_stmt
);
2123 if (CONSTANT_CLASS_P (gimple_assign_rhs1 (next_stmt
)))
2124 LOOP_VINFO_OPERANDS_SWAPPED (loop_info
) = true;
2130 lhs
= gimple_assign_lhs (next_stmt
);
2131 next_stmt
= GROUP_NEXT_ELEMENT (vinfo_for_stmt (next_stmt
));
2134 /* Save the chain for further analysis in SLP detection. */
2135 first
= GROUP_FIRST_ELEMENT (vinfo_for_stmt (current_stmt
));
2136 LOOP_VINFO_REDUCTION_CHAINS (loop_info
).safe_push (first
);
2137 GROUP_SIZE (vinfo_for_stmt (first
)) = size
;
2143 /* Function vect_is_simple_reduction_1
2145 (1) Detect a cross-iteration def-use cycle that represents a simple
2146 reduction computation. We look for the following pattern:
2151 a2 = operation (a3, a1)
2158 a2 = operation (a3, a1)
2161 1. operation is commutative and associative and it is safe to
2162 change the order of the computation (if CHECK_REDUCTION is true)
2163 2. no uses for a2 in the loop (a2 is used out of the loop)
2164 3. no uses of a1 in the loop besides the reduction operation
2165 4. no uses of a1 outside the loop.
2167 Conditions 1,4 are tested here.
2168 Conditions 2,3 are tested in vect_mark_stmts_to_be_vectorized.
2170 (2) Detect a cross-iteration def-use cycle in nested loops, i.e.,
2171 nested cycles, if CHECK_REDUCTION is false.
2173 (3) Detect cycles of phi nodes in outer-loop vectorization, i.e., double
2177 inner loop (def of a3)
2180 If MODIFY is true it tries also to rework the code in-place to enable
2181 detection of more reduction patterns. For the time being we rewrite
2182 "res -= RHS" into "rhs += -RHS" when it seems worthwhile.
2186 vect_is_simple_reduction_1 (loop_vec_info loop_info
, gimple phi
,
2187 bool check_reduction
, bool *double_reduc
,
2190 struct loop
*loop
= (gimple_bb (phi
))->loop_father
;
2191 struct loop
*vect_loop
= LOOP_VINFO_LOOP (loop_info
);
2192 edge latch_e
= loop_latch_edge (loop
);
2193 tree loop_arg
= PHI_ARG_DEF_FROM_EDGE (phi
, latch_e
);
2194 gimple def_stmt
, def1
= NULL
, def2
= NULL
;
2195 enum tree_code orig_code
, code
;
2196 tree op1
, op2
, op3
= NULL_TREE
, op4
= NULL_TREE
;
2200 imm_use_iterator imm_iter
;
2201 use_operand_p use_p
;
2204 *double_reduc
= false;
2206 /* If CHECK_REDUCTION is true, we assume inner-most loop vectorization,
2207 otherwise, we assume outer loop vectorization. */
2208 gcc_assert ((check_reduction
&& loop
== vect_loop
)
2209 || (!check_reduction
&& flow_loop_nested_p (vect_loop
, loop
)));
2211 name
= PHI_RESULT (phi
);
2212 /* ??? If there are no uses of the PHI result the inner loop reduction
2213 won't be detected as possibly double-reduction by vectorizable_reduction
2214 because that tries to walk the PHI arg from the preheader edge which
2215 can be constant. See PR60382. */
2216 if (has_zero_uses (name
))
2219 FOR_EACH_IMM_USE_FAST (use_p
, imm_iter
, name
)
2221 gimple use_stmt
= USE_STMT (use_p
);
2222 if (is_gimple_debug (use_stmt
))
2225 if (!flow_bb_inside_loop_p (loop
, gimple_bb (use_stmt
)))
2227 if (dump_enabled_p ())
2228 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
2229 "intermediate value used outside loop.\n");
2234 if (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 (TREE_CODE (loop_arg
) != SSA_NAME
)
2248 if (dump_enabled_p ())
2250 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
2251 "reduction: not ssa_name: ");
2252 dump_generic_expr (MSG_MISSED_OPTIMIZATION
, TDF_SLIM
, loop_arg
);
2253 dump_printf (MSG_MISSED_OPTIMIZATION
, "\n");
2258 def_stmt
= SSA_NAME_DEF_STMT (loop_arg
);
2261 if (dump_enabled_p ())
2262 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
2263 "reduction: no def_stmt.\n");
2267 if (!is_gimple_assign (def_stmt
) && gimple_code (def_stmt
) != GIMPLE_PHI
)
2269 if (dump_enabled_p ())
2271 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, def_stmt
, 0);
2272 dump_printf (MSG_NOTE
, "\n");
2277 if (is_gimple_assign (def_stmt
))
2279 name
= gimple_assign_lhs (def_stmt
);
2284 name
= PHI_RESULT (def_stmt
);
2289 FOR_EACH_IMM_USE_FAST (use_p
, imm_iter
, name
)
2291 gimple use_stmt
= USE_STMT (use_p
);
2292 if (is_gimple_debug (use_stmt
))
2294 if (flow_bb_inside_loop_p (loop
, gimple_bb (use_stmt
))
2295 && vinfo_for_stmt (use_stmt
)
2296 && !is_pattern_stmt_p (vinfo_for_stmt (use_stmt
)))
2300 if (dump_enabled_p ())
2301 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
2302 "reduction used in loop.\n");
2307 /* If DEF_STMT is a phi node itself, we expect it to have a single argument
2308 defined in the inner loop. */
2311 op1
= PHI_ARG_DEF (def_stmt
, 0);
2313 if (gimple_phi_num_args (def_stmt
) != 1
2314 || TREE_CODE (op1
) != SSA_NAME
)
2316 if (dump_enabled_p ())
2317 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
2318 "unsupported phi node definition.\n");
2323 def1
= SSA_NAME_DEF_STMT (op1
);
2324 if (flow_bb_inside_loop_p (loop
, gimple_bb (def_stmt
))
2326 && flow_bb_inside_loop_p (loop
->inner
, gimple_bb (def1
))
2327 && is_gimple_assign (def1
))
2329 if (dump_enabled_p ())
2330 report_vect_op (MSG_NOTE
, def_stmt
,
2331 "detected double reduction: ");
2333 *double_reduc
= true;
2340 code
= orig_code
= gimple_assign_rhs_code (def_stmt
);
2342 /* We can handle "res -= x[i]", which is non-associative by
2343 simply rewriting this into "res += -x[i]". Avoid changing
2344 gimple instruction for the first simple tests and only do this
2345 if we're allowed to change code at all. */
2346 if (code
== MINUS_EXPR
2348 && (op1
= gimple_assign_rhs1 (def_stmt
))
2349 && TREE_CODE (op1
) == SSA_NAME
2350 && SSA_NAME_DEF_STMT (op1
) == phi
)
2354 && (!commutative_tree_code (code
) || !associative_tree_code (code
)))
2356 if (dump_enabled_p ())
2357 report_vect_op (MSG_MISSED_OPTIMIZATION
, def_stmt
,
2358 "reduction: not commutative/associative: ");
2362 if (get_gimple_rhs_class (code
) != GIMPLE_BINARY_RHS
)
2364 if (code
!= COND_EXPR
)
2366 if (dump_enabled_p ())
2367 report_vect_op (MSG_MISSED_OPTIMIZATION
, def_stmt
,
2368 "reduction: not binary operation: ");
2373 op3
= gimple_assign_rhs1 (def_stmt
);
2374 if (COMPARISON_CLASS_P (op3
))
2376 op4
= TREE_OPERAND (op3
, 1);
2377 op3
= TREE_OPERAND (op3
, 0);
2380 op1
= gimple_assign_rhs2 (def_stmt
);
2381 op2
= gimple_assign_rhs3 (def_stmt
);
2383 if (TREE_CODE (op1
) != SSA_NAME
&& TREE_CODE (op2
) != SSA_NAME
)
2385 if (dump_enabled_p ())
2386 report_vect_op (MSG_MISSED_OPTIMIZATION
, def_stmt
,
2387 "reduction: uses not ssa_names: ");
2394 op1
= gimple_assign_rhs1 (def_stmt
);
2395 op2
= gimple_assign_rhs2 (def_stmt
);
2397 if (TREE_CODE (op1
) != SSA_NAME
&& TREE_CODE (op2
) != SSA_NAME
)
2399 if (dump_enabled_p ())
2400 report_vect_op (MSG_MISSED_OPTIMIZATION
, def_stmt
,
2401 "reduction: uses not ssa_names: ");
2407 type
= TREE_TYPE (gimple_assign_lhs (def_stmt
));
2408 if ((TREE_CODE (op1
) == SSA_NAME
2409 && !types_compatible_p (type
,TREE_TYPE (op1
)))
2410 || (TREE_CODE (op2
) == SSA_NAME
2411 && !types_compatible_p (type
, TREE_TYPE (op2
)))
2412 || (op3
&& TREE_CODE (op3
) == SSA_NAME
2413 && !types_compatible_p (type
, TREE_TYPE (op3
)))
2414 || (op4
&& TREE_CODE (op4
) == SSA_NAME
2415 && !types_compatible_p (type
, TREE_TYPE (op4
))))
2417 if (dump_enabled_p ())
2419 dump_printf_loc (MSG_NOTE
, vect_location
,
2420 "reduction: multiple types: operation type: ");
2421 dump_generic_expr (MSG_NOTE
, TDF_SLIM
, type
);
2422 dump_printf (MSG_NOTE
, ", operands types: ");
2423 dump_generic_expr (MSG_NOTE
, TDF_SLIM
,
2425 dump_printf (MSG_NOTE
, ",");
2426 dump_generic_expr (MSG_NOTE
, TDF_SLIM
,
2430 dump_printf (MSG_NOTE
, ",");
2431 dump_generic_expr (MSG_NOTE
, TDF_SLIM
,
2437 dump_printf (MSG_NOTE
, ",");
2438 dump_generic_expr (MSG_NOTE
, TDF_SLIM
,
2441 dump_printf (MSG_NOTE
, "\n");
2447 /* Check that it's ok to change the order of the computation.
2448 Generally, when vectorizing a reduction we change the order of the
2449 computation. This may change the behavior of the program in some
2450 cases, so we need to check that this is ok. One exception is when
2451 vectorizing an outer-loop: the inner-loop is executed sequentially,
2452 and therefore vectorizing reductions in the inner-loop during
2453 outer-loop vectorization is safe. */
2455 /* CHECKME: check for !flag_finite_math_only too? */
2456 if (SCALAR_FLOAT_TYPE_P (type
) && !flag_associative_math
2459 /* Changing the order of operations changes the semantics. */
2460 if (dump_enabled_p ())
2461 report_vect_op (MSG_MISSED_OPTIMIZATION
, def_stmt
,
2462 "reduction: unsafe fp math optimization: ");
2465 else if (INTEGRAL_TYPE_P (type
) && TYPE_OVERFLOW_TRAPS (type
)
2468 /* Changing the order of operations changes the semantics. */
2469 if (dump_enabled_p ())
2470 report_vect_op (MSG_MISSED_OPTIMIZATION
, def_stmt
,
2471 "reduction: unsafe int math optimization: ");
2474 else if (SAT_FIXED_POINT_TYPE_P (type
) && check_reduction
)
2476 /* Changing the order of operations changes the semantics. */
2477 if (dump_enabled_p ())
2478 report_vect_op (MSG_MISSED_OPTIMIZATION
, def_stmt
,
2479 "reduction: unsafe fixed-point math optimization: ");
2483 /* If we detected "res -= x[i]" earlier, rewrite it into
2484 "res += -x[i]" now. If this turns out to be useless reassoc
2485 will clean it up again. */
2486 if (orig_code
== MINUS_EXPR
)
2488 tree rhs
= gimple_assign_rhs2 (def_stmt
);
2489 tree negrhs
= make_ssa_name (TREE_TYPE (rhs
), NULL
);
2490 gimple negate_stmt
= gimple_build_assign_with_ops (NEGATE_EXPR
, negrhs
,
2492 gimple_stmt_iterator gsi
= gsi_for_stmt (def_stmt
);
2493 set_vinfo_for_stmt (negate_stmt
, new_stmt_vec_info (negate_stmt
,
2495 gsi_insert_before (&gsi
, negate_stmt
, GSI_NEW_STMT
);
2496 gimple_assign_set_rhs2 (def_stmt
, negrhs
);
2497 gimple_assign_set_rhs_code (def_stmt
, PLUS_EXPR
);
2498 update_stmt (def_stmt
);
2501 /* Reduction is safe. We're dealing with one of the following:
2502 1) integer arithmetic and no trapv
2503 2) floating point arithmetic, and special flags permit this optimization
2504 3) nested cycle (i.e., outer loop vectorization). */
2505 if (TREE_CODE (op1
) == SSA_NAME
)
2506 def1
= SSA_NAME_DEF_STMT (op1
);
2508 if (TREE_CODE (op2
) == SSA_NAME
)
2509 def2
= SSA_NAME_DEF_STMT (op2
);
2511 if (code
!= COND_EXPR
2512 && ((!def1
|| gimple_nop_p (def1
)) && (!def2
|| gimple_nop_p (def2
))))
2514 if (dump_enabled_p ())
2515 report_vect_op (MSG_NOTE
, def_stmt
, "reduction: no defs for operands: ");
2519 /* Check that one def is the reduction def, defined by PHI,
2520 the other def is either defined in the loop ("vect_internal_def"),
2521 or it's an induction (defined by a loop-header phi-node). */
2523 if (def2
&& def2
== phi
2524 && (code
== COND_EXPR
2525 || !def1
|| gimple_nop_p (def1
)
2526 || !flow_bb_inside_loop_p (loop
, gimple_bb (def1
))
2527 || (def1
&& flow_bb_inside_loop_p (loop
, gimple_bb (def1
))
2528 && (is_gimple_assign (def1
)
2529 || is_gimple_call (def1
)
2530 || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def1
))
2531 == vect_induction_def
2532 || (gimple_code (def1
) == GIMPLE_PHI
2533 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def1
))
2534 == vect_internal_def
2535 && !is_loop_header_bb_p (gimple_bb (def1
)))))))
2537 if (dump_enabled_p ())
2538 report_vect_op (MSG_NOTE
, def_stmt
, "detected reduction: ");
2542 if (def1
&& def1
== phi
2543 && (code
== COND_EXPR
2544 || !def2
|| gimple_nop_p (def2
)
2545 || !flow_bb_inside_loop_p (loop
, gimple_bb (def2
))
2546 || (def2
&& flow_bb_inside_loop_p (loop
, gimple_bb (def2
))
2547 && (is_gimple_assign (def2
)
2548 || is_gimple_call (def2
)
2549 || STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def2
))
2550 == vect_induction_def
2551 || (gimple_code (def2
) == GIMPLE_PHI
2552 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def2
))
2553 == vect_internal_def
2554 && !is_loop_header_bb_p (gimple_bb (def2
)))))))
2556 if (check_reduction
)
2558 /* Swap operands (just for simplicity - so that the rest of the code
2559 can assume that the reduction variable is always the last (second)
2561 if (dump_enabled_p ())
2562 report_vect_op (MSG_NOTE
, def_stmt
,
2563 "detected reduction: need to swap operands: ");
2565 swap_ssa_operands (def_stmt
, gimple_assign_rhs1_ptr (def_stmt
),
2566 gimple_assign_rhs2_ptr (def_stmt
));
2568 if (CONSTANT_CLASS_P (gimple_assign_rhs1 (def_stmt
)))
2569 LOOP_VINFO_OPERANDS_SWAPPED (loop_info
) = true;
2573 if (dump_enabled_p ())
2574 report_vect_op (MSG_NOTE
, def_stmt
, "detected reduction: ");
2580 /* Try to find SLP reduction chain. */
2581 if (check_reduction
&& vect_is_slp_reduction (loop_info
, phi
, def_stmt
))
2583 if (dump_enabled_p ())
2584 report_vect_op (MSG_NOTE
, def_stmt
,
2585 "reduction: detected reduction chain: ");
2590 if (dump_enabled_p ())
2591 report_vect_op (MSG_MISSED_OPTIMIZATION
, def_stmt
,
2592 "reduction: unknown pattern: ");
2597 /* Wrapper around vect_is_simple_reduction_1, that won't modify code
2598 in-place. Arguments as there. */
2601 vect_is_simple_reduction (loop_vec_info loop_info
, gimple phi
,
2602 bool check_reduction
, bool *double_reduc
)
2604 return vect_is_simple_reduction_1 (loop_info
, phi
, check_reduction
,
2605 double_reduc
, false);
2608 /* Wrapper around vect_is_simple_reduction_1, which will modify code
2609 in-place if it enables detection of more reductions. Arguments
2613 vect_force_simple_reduction (loop_vec_info loop_info
, gimple phi
,
2614 bool check_reduction
, bool *double_reduc
)
2616 return vect_is_simple_reduction_1 (loop_info
, phi
, check_reduction
,
2617 double_reduc
, true);
2620 /* Calculate the cost of one scalar iteration of the loop. */
2622 vect_get_single_scalar_iteration_cost (loop_vec_info loop_vinfo
)
2624 struct loop
*loop
= LOOP_VINFO_LOOP (loop_vinfo
);
2625 basic_block
*bbs
= LOOP_VINFO_BBS (loop_vinfo
);
2626 int nbbs
= loop
->num_nodes
, factor
, scalar_single_iter_cost
= 0;
2627 int innerloop_iters
, i
, stmt_cost
;
2629 /* Count statements in scalar loop. Using this as scalar cost for a single
2632 TODO: Add outer loop support.
2634 TODO: Consider assigning different costs to different scalar
2638 innerloop_iters
= 1;
2640 innerloop_iters
= 50; /* FIXME */
2642 for (i
= 0; i
< nbbs
; i
++)
2644 gimple_stmt_iterator si
;
2645 basic_block bb
= bbs
[i
];
2647 if (bb
->loop_father
== loop
->inner
)
2648 factor
= innerloop_iters
;
2652 for (si
= gsi_start_bb (bb
); !gsi_end_p (si
); gsi_next (&si
))
2654 gimple stmt
= gsi_stmt (si
);
2655 stmt_vec_info stmt_info
= vinfo_for_stmt (stmt
);
2657 if (!is_gimple_assign (stmt
) && !is_gimple_call (stmt
))
2660 /* Skip stmts that are not vectorized inside the loop. */
2662 && !STMT_VINFO_RELEVANT_P (stmt_info
)
2663 && (!STMT_VINFO_LIVE_P (stmt_info
)
2664 || !VECTORIZABLE_CYCLE_DEF (STMT_VINFO_DEF_TYPE (stmt_info
)))
2665 && !STMT_VINFO_IN_PATTERN_P (stmt_info
))
2668 if (STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt
)))
2670 if (DR_IS_READ (STMT_VINFO_DATA_REF (vinfo_for_stmt (stmt
))))
2671 stmt_cost
= vect_get_stmt_cost (scalar_load
);
2673 stmt_cost
= vect_get_stmt_cost (scalar_store
);
2676 stmt_cost
= vect_get_stmt_cost (scalar_stmt
);
2678 scalar_single_iter_cost
+= stmt_cost
* factor
;
2681 return scalar_single_iter_cost
;
2684 /* Calculate cost of peeling the loop PEEL_ITERS_PROLOGUE times. */
2686 vect_get_known_peeling_cost (loop_vec_info loop_vinfo
, int peel_iters_prologue
,
2687 int *peel_iters_epilogue
,
2688 int scalar_single_iter_cost
,
2689 stmt_vector_for_cost
*prologue_cost_vec
,
2690 stmt_vector_for_cost
*epilogue_cost_vec
)
2693 int vf
= LOOP_VINFO_VECT_FACTOR (loop_vinfo
);
2695 if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo
))
2697 *peel_iters_epilogue
= vf
/2;
2698 if (dump_enabled_p ())
2699 dump_printf_loc (MSG_NOTE
, vect_location
,
2700 "cost model: epilogue peel iters set to vf/2 "
2701 "because loop iterations are unknown .\n");
2703 /* If peeled iterations are known but number of scalar loop
2704 iterations are unknown, count a taken branch per peeled loop. */
2705 retval
= record_stmt_cost (prologue_cost_vec
, 2, cond_branch_taken
,
2706 NULL
, 0, vect_prologue
);
2710 int niters
= LOOP_VINFO_INT_NITERS (loop_vinfo
);
2711 peel_iters_prologue
= niters
< peel_iters_prologue
?
2712 niters
: peel_iters_prologue
;
2713 *peel_iters_epilogue
= (niters
- peel_iters_prologue
) % vf
;
2714 /* If we need to peel for gaps, but no peeling is required, we have to
2715 peel VF iterations. */
2716 if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo
) && !*peel_iters_epilogue
)
2717 *peel_iters_epilogue
= vf
;
2720 if (peel_iters_prologue
)
2721 retval
+= record_stmt_cost (prologue_cost_vec
,
2722 peel_iters_prologue
* scalar_single_iter_cost
,
2723 scalar_stmt
, NULL
, 0, vect_prologue
);
2724 if (*peel_iters_epilogue
)
2725 retval
+= record_stmt_cost (epilogue_cost_vec
,
2726 *peel_iters_epilogue
* scalar_single_iter_cost
,
2727 scalar_stmt
, NULL
, 0, vect_epilogue
);
2731 /* Function vect_estimate_min_profitable_iters
2733 Return the number of iterations required for the vector version of the
2734 loop to be profitable relative to the cost of the scalar version of the
2738 vect_estimate_min_profitable_iters (loop_vec_info loop_vinfo
,
2739 int *ret_min_profitable_niters
,
2740 int *ret_min_profitable_estimate
)
2742 int min_profitable_iters
;
2743 int min_profitable_estimate
;
2744 int peel_iters_prologue
;
2745 int peel_iters_epilogue
;
2746 unsigned vec_inside_cost
= 0;
2747 int vec_outside_cost
= 0;
2748 unsigned vec_prologue_cost
= 0;
2749 unsigned vec_epilogue_cost
= 0;
2750 int scalar_single_iter_cost
= 0;
2751 int scalar_outside_cost
= 0;
2752 int vf
= LOOP_VINFO_VECT_FACTOR (loop_vinfo
);
2753 int npeel
= LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo
);
2754 void *target_cost_data
= LOOP_VINFO_TARGET_COST_DATA (loop_vinfo
);
2756 /* Cost model disabled. */
2757 if (unlimited_cost_model (LOOP_VINFO_LOOP (loop_vinfo
)))
2759 dump_printf_loc (MSG_NOTE
, vect_location
, "cost model disabled.\n");
2760 *ret_min_profitable_niters
= 0;
2761 *ret_min_profitable_estimate
= 0;
2765 /* Requires loop versioning tests to handle misalignment. */
2766 if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo
))
2768 /* FIXME: Make cost depend on complexity of individual check. */
2769 unsigned len
= LOOP_VINFO_MAY_MISALIGN_STMTS (loop_vinfo
).length ();
2770 (void) add_stmt_cost (target_cost_data
, len
, vector_stmt
, NULL
, 0,
2772 dump_printf (MSG_NOTE
,
2773 "cost model: Adding cost of checks for loop "
2774 "versioning to treat misalignment.\n");
2777 /* Requires loop versioning with alias checks. */
2778 if (LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo
))
2780 /* FIXME: Make cost depend on complexity of individual check. */
2781 unsigned len
= LOOP_VINFO_MAY_ALIAS_DDRS (loop_vinfo
).length ();
2782 (void) add_stmt_cost (target_cost_data
, len
, vector_stmt
, NULL
, 0,
2784 dump_printf (MSG_NOTE
,
2785 "cost model: Adding cost of checks for loop "
2786 "versioning aliasing.\n");
2789 if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo
)
2790 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo
))
2791 (void) add_stmt_cost (target_cost_data
, 1, cond_branch_taken
, NULL
, 0,
2794 /* Count statements in scalar loop. Using this as scalar cost for a single
2797 TODO: Add outer loop support.
2799 TODO: Consider assigning different costs to different scalar
2802 scalar_single_iter_cost
= vect_get_single_scalar_iteration_cost (loop_vinfo
);
2804 /* Add additional cost for the peeled instructions in prologue and epilogue
2807 FORNOW: If we don't know the value of peel_iters for prologue or epilogue
2808 at compile-time - we assume it's vf/2 (the worst would be vf-1).
2810 TODO: Build an expression that represents peel_iters for prologue and
2811 epilogue to be used in a run-time test. */
2815 peel_iters_prologue
= vf
/2;
2816 dump_printf (MSG_NOTE
, "cost model: "
2817 "prologue peel iters set to vf/2.\n");
2819 /* If peeling for alignment is unknown, loop bound of main loop becomes
2821 peel_iters_epilogue
= vf
/2;
2822 dump_printf (MSG_NOTE
, "cost model: "
2823 "epilogue peel iters set to vf/2 because "
2824 "peeling for alignment is unknown.\n");
2826 /* If peeled iterations are unknown, count a taken branch and a not taken
2827 branch per peeled loop. Even if scalar loop iterations are known,
2828 vector iterations are not known since peeled prologue iterations are
2829 not known. Hence guards remain the same. */
2830 (void) add_stmt_cost (target_cost_data
, 2, cond_branch_taken
,
2831 NULL
, 0, vect_prologue
);
2832 (void) add_stmt_cost (target_cost_data
, 2, cond_branch_not_taken
,
2833 NULL
, 0, vect_prologue
);
2834 /* FORNOW: Don't attempt to pass individual scalar instructions to
2835 the model; just assume linear cost for scalar iterations. */
2836 (void) add_stmt_cost (target_cost_data
,
2837 peel_iters_prologue
* scalar_single_iter_cost
,
2838 scalar_stmt
, NULL
, 0, vect_prologue
);
2839 (void) add_stmt_cost (target_cost_data
,
2840 peel_iters_epilogue
* scalar_single_iter_cost
,
2841 scalar_stmt
, NULL
, 0, vect_epilogue
);
2845 stmt_vector_for_cost prologue_cost_vec
, epilogue_cost_vec
;
2846 stmt_info_for_cost
*si
;
2848 void *data
= LOOP_VINFO_TARGET_COST_DATA (loop_vinfo
);
2850 prologue_cost_vec
.create (2);
2851 epilogue_cost_vec
.create (2);
2852 peel_iters_prologue
= npeel
;
2854 (void) vect_get_known_peeling_cost (loop_vinfo
, peel_iters_prologue
,
2855 &peel_iters_epilogue
,
2856 scalar_single_iter_cost
,
2858 &epilogue_cost_vec
);
2860 FOR_EACH_VEC_ELT (prologue_cost_vec
, j
, si
)
2862 struct _stmt_vec_info
*stmt_info
2863 = si
->stmt
? vinfo_for_stmt (si
->stmt
) : NULL
;
2864 (void) add_stmt_cost (data
, si
->count
, si
->kind
, stmt_info
,
2865 si
->misalign
, vect_prologue
);
2868 FOR_EACH_VEC_ELT (epilogue_cost_vec
, j
, si
)
2870 struct _stmt_vec_info
*stmt_info
2871 = si
->stmt
? vinfo_for_stmt (si
->stmt
) : NULL
;
2872 (void) add_stmt_cost (data
, si
->count
, si
->kind
, stmt_info
,
2873 si
->misalign
, vect_epilogue
);
2876 prologue_cost_vec
.release ();
2877 epilogue_cost_vec
.release ();
2880 /* FORNOW: The scalar outside cost is incremented in one of the
2883 1. The vectorizer checks for alignment and aliasing and generates
2884 a condition that allows dynamic vectorization. A cost model
2885 check is ANDED with the versioning condition. Hence scalar code
2886 path now has the added cost of the versioning check.
2888 if (cost > th & versioning_check)
2891 Hence run-time scalar is incremented by not-taken branch cost.
2893 2. The vectorizer then checks if a prologue is required. If the
2894 cost model check was not done before during versioning, it has to
2895 be done before the prologue check.
2898 prologue = scalar_iters
2903 if (prologue == num_iters)
2906 Hence the run-time scalar cost is incremented by a taken branch,
2907 plus a not-taken branch, plus a taken branch cost.
2909 3. The vectorizer then checks if an epilogue is required. If the
2910 cost model check was not done before during prologue check, it
2911 has to be done with the epilogue check.
2917 if (prologue == num_iters)
2920 if ((cost <= th) | (scalar_iters-prologue-epilogue == 0))
2923 Hence the run-time scalar cost should be incremented by 2 taken
2926 TODO: The back end may reorder the BBS's differently and reverse
2927 conditions/branch directions. Change the estimates below to
2928 something more reasonable. */
2930 /* If the number of iterations is known and we do not do versioning, we can
2931 decide whether to vectorize at compile time. Hence the scalar version
2932 do not carry cost model guard costs. */
2933 if (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo
)
2934 || LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo
)
2935 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo
))
2937 /* Cost model check occurs at versioning. */
2938 if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo
)
2939 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo
))
2940 scalar_outside_cost
+= vect_get_stmt_cost (cond_branch_not_taken
);
2943 /* Cost model check occurs at prologue generation. */
2944 if (LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo
) < 0)
2945 scalar_outside_cost
+= 2 * vect_get_stmt_cost (cond_branch_taken
)
2946 + vect_get_stmt_cost (cond_branch_not_taken
);
2947 /* Cost model check occurs at epilogue generation. */
2949 scalar_outside_cost
+= 2 * vect_get_stmt_cost (cond_branch_taken
);
2953 /* Complete the target-specific cost calculations. */
2954 finish_cost (LOOP_VINFO_TARGET_COST_DATA (loop_vinfo
), &vec_prologue_cost
,
2955 &vec_inside_cost
, &vec_epilogue_cost
);
2957 vec_outside_cost
= (int)(vec_prologue_cost
+ vec_epilogue_cost
);
2959 /* Calculate number of iterations required to make the vector version
2960 profitable, relative to the loop bodies only. The following condition
2962 SIC * niters + SOC > VIC * ((niters-PL_ITERS-EP_ITERS)/VF) + VOC
2964 SIC = scalar iteration cost, VIC = vector iteration cost,
2965 VOC = vector outside cost, VF = vectorization factor,
2966 PL_ITERS = prologue iterations, EP_ITERS= epilogue iterations
2967 SOC = scalar outside cost for run time cost model check. */
2969 if ((scalar_single_iter_cost
* vf
) > (int) vec_inside_cost
)
2971 if (vec_outside_cost
<= 0)
2972 min_profitable_iters
= 1;
2975 min_profitable_iters
= ((vec_outside_cost
- scalar_outside_cost
) * vf
2976 - vec_inside_cost
* peel_iters_prologue
2977 - vec_inside_cost
* peel_iters_epilogue
)
2978 / ((scalar_single_iter_cost
* vf
)
2981 if ((scalar_single_iter_cost
* vf
* min_profitable_iters
)
2982 <= (((int) vec_inside_cost
* min_profitable_iters
)
2983 + (((int) vec_outside_cost
- scalar_outside_cost
) * vf
)))
2984 min_profitable_iters
++;
2987 /* vector version will never be profitable. */
2990 if (LOOP_VINFO_LOOP (loop_vinfo
)->force_vectorize
)
2991 warning_at (vect_location
, OPT_Wopenmp_simd
, "vectorization "
2992 "did not happen for a simd loop");
2994 if (dump_enabled_p ())
2995 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
2996 "cost model: the vector iteration cost = %d "
2997 "divided by the scalar iteration cost = %d "
2998 "is greater or equal to the vectorization factor = %d"
3000 vec_inside_cost
, scalar_single_iter_cost
, vf
);
3001 *ret_min_profitable_niters
= -1;
3002 *ret_min_profitable_estimate
= -1;
3006 if (dump_enabled_p ())
3008 dump_printf_loc (MSG_NOTE
, vect_location
, "Cost model analysis: \n");
3009 dump_printf (MSG_NOTE
, " Vector inside of loop cost: %d\n",
3011 dump_printf (MSG_NOTE
, " Vector prologue cost: %d\n",
3013 dump_printf (MSG_NOTE
, " Vector epilogue cost: %d\n",
3015 dump_printf (MSG_NOTE
, " Scalar iteration cost: %d\n",
3016 scalar_single_iter_cost
);
3017 dump_printf (MSG_NOTE
, " Scalar outside cost: %d\n",
3018 scalar_outside_cost
);
3019 dump_printf (MSG_NOTE
, " Vector outside cost: %d\n",
3021 dump_printf (MSG_NOTE
, " prologue iterations: %d\n",
3022 peel_iters_prologue
);
3023 dump_printf (MSG_NOTE
, " epilogue iterations: %d\n",
3024 peel_iters_epilogue
);
3025 dump_printf (MSG_NOTE
,
3026 " Calculated minimum iters for profitability: %d\n",
3027 min_profitable_iters
);
3028 dump_printf (MSG_NOTE
, "\n");
3031 min_profitable_iters
=
3032 min_profitable_iters
< vf
? vf
: min_profitable_iters
;
3034 /* Because the condition we create is:
3035 if (niters <= min_profitable_iters)
3036 then skip the vectorized loop. */
3037 min_profitable_iters
--;
3039 if (dump_enabled_p ())
3040 dump_printf_loc (MSG_NOTE
, vect_location
,
3041 " Runtime profitability threshold = %d\n",
3042 min_profitable_iters
);
3044 *ret_min_profitable_niters
= min_profitable_iters
;
3046 /* Calculate number of iterations required to make the vector version
3047 profitable, relative to the loop bodies only.
3049 Non-vectorized variant is SIC * niters and it must win over vector
3050 variant on the expected loop trip count. The following condition must hold true:
3051 SIC * niters > VIC * ((niters-PL_ITERS-EP_ITERS)/VF) + VOC + SOC */
3053 if (vec_outside_cost
<= 0)
3054 min_profitable_estimate
= 1;
3057 min_profitable_estimate
= ((vec_outside_cost
+ scalar_outside_cost
) * vf
3058 - vec_inside_cost
* peel_iters_prologue
3059 - vec_inside_cost
* peel_iters_epilogue
)
3060 / ((scalar_single_iter_cost
* vf
)
3063 min_profitable_estimate
--;
3064 min_profitable_estimate
= MAX (min_profitable_estimate
, min_profitable_iters
);
3065 if (dump_enabled_p ())
3066 dump_printf_loc (MSG_NOTE
, vect_location
,
3067 " Static estimate profitability threshold = %d\n",
3068 min_profitable_iters
);
3070 *ret_min_profitable_estimate
= min_profitable_estimate
;
3074 /* TODO: Close dependency between vect_model_*_cost and vectorizable_*
3075 functions. Design better to avoid maintenance issues. */
3077 /* Function vect_model_reduction_cost.
3079 Models cost for a reduction operation, including the vector ops
3080 generated within the strip-mine loop, the initial definition before
3081 the loop, and the epilogue code that must be generated. */
3084 vect_model_reduction_cost (stmt_vec_info stmt_info
, enum tree_code reduc_code
,
3087 int prologue_cost
= 0, epilogue_cost
= 0;
3088 enum tree_code code
;
3091 gimple stmt
, orig_stmt
;
3093 enum machine_mode mode
;
3094 loop_vec_info loop_vinfo
= STMT_VINFO_LOOP_VINFO (stmt_info
);
3095 struct loop
*loop
= LOOP_VINFO_LOOP (loop_vinfo
);
3096 void *target_cost_data
= LOOP_VINFO_TARGET_COST_DATA (loop_vinfo
);
3098 /* Cost of reduction op inside loop. */
3099 unsigned inside_cost
= add_stmt_cost (target_cost_data
, ncopies
, vector_stmt
,
3100 stmt_info
, 0, vect_body
);
3101 stmt
= STMT_VINFO_STMT (stmt_info
);
3103 switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt
)))
3105 case GIMPLE_SINGLE_RHS
:
3106 gcc_assert (TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt
)) == ternary_op
);
3107 reduction_op
= TREE_OPERAND (gimple_assign_rhs1 (stmt
), 2);
3109 case GIMPLE_UNARY_RHS
:
3110 reduction_op
= gimple_assign_rhs1 (stmt
);
3112 case GIMPLE_BINARY_RHS
:
3113 reduction_op
= gimple_assign_rhs2 (stmt
);
3115 case GIMPLE_TERNARY_RHS
:
3116 reduction_op
= gimple_assign_rhs3 (stmt
);
3122 vectype
= get_vectype_for_scalar_type (TREE_TYPE (reduction_op
));
3125 if (dump_enabled_p ())
3127 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
3128 "unsupported data-type ");
3129 dump_generic_expr (MSG_MISSED_OPTIMIZATION
, TDF_SLIM
,
3130 TREE_TYPE (reduction_op
));
3131 dump_printf (MSG_MISSED_OPTIMIZATION
, "\n");
3136 mode
= TYPE_MODE (vectype
);
3137 orig_stmt
= STMT_VINFO_RELATED_STMT (stmt_info
);
3140 orig_stmt
= STMT_VINFO_STMT (stmt_info
);
3142 code
= gimple_assign_rhs_code (orig_stmt
);
3144 /* Add in cost for initial definition. */
3145 prologue_cost
+= add_stmt_cost (target_cost_data
, 1, scalar_to_vec
,
3146 stmt_info
, 0, vect_prologue
);
3148 /* Determine cost of epilogue code.
3150 We have a reduction operator that will reduce the vector in one statement.
3151 Also requires scalar extract. */
3153 if (!nested_in_vect_loop_p (loop
, orig_stmt
))
3155 if (reduc_code
!= ERROR_MARK
)
3157 epilogue_cost
+= add_stmt_cost (target_cost_data
, 1, vector_stmt
,
3158 stmt_info
, 0, vect_epilogue
);
3159 epilogue_cost
+= add_stmt_cost (target_cost_data
, 1, vec_to_scalar
,
3160 stmt_info
, 0, vect_epilogue
);
3164 int vec_size_in_bits
= tree_to_uhwi (TYPE_SIZE (vectype
));
3166 TYPE_SIZE (TREE_TYPE (gimple_assign_lhs (orig_stmt
)));
3167 int element_bitsize
= tree_to_uhwi (bitsize
);
3168 int nelements
= vec_size_in_bits
/ element_bitsize
;
3170 optab
= optab_for_tree_code (code
, vectype
, optab_default
);
3172 /* We have a whole vector shift available. */
3173 if (VECTOR_MODE_P (mode
)
3174 && optab_handler (optab
, mode
) != CODE_FOR_nothing
3175 && optab_handler (vec_shr_optab
, mode
) != CODE_FOR_nothing
)
3177 /* Final reduction via vector shifts and the reduction operator.
3178 Also requires scalar extract. */
3179 epilogue_cost
+= add_stmt_cost (target_cost_data
,
3180 exact_log2 (nelements
) * 2,
3181 vector_stmt
, stmt_info
, 0,
3183 epilogue_cost
+= add_stmt_cost (target_cost_data
, 1,
3184 vec_to_scalar
, stmt_info
, 0,
3188 /* Use extracts and reduction op for final reduction. For N
3189 elements, we have N extracts and N-1 reduction ops. */
3190 epilogue_cost
+= add_stmt_cost (target_cost_data
,
3191 nelements
+ nelements
- 1,
3192 vector_stmt
, stmt_info
, 0,
3197 if (dump_enabled_p ())
3198 dump_printf (MSG_NOTE
,
3199 "vect_model_reduction_cost: inside_cost = %d, "
3200 "prologue_cost = %d, epilogue_cost = %d .\n", inside_cost
,
3201 prologue_cost
, epilogue_cost
);
3207 /* Function vect_model_induction_cost.
3209 Models cost for induction operations. */
3212 vect_model_induction_cost (stmt_vec_info stmt_info
, int ncopies
)
3214 loop_vec_info loop_vinfo
= STMT_VINFO_LOOP_VINFO (stmt_info
);
3215 void *target_cost_data
= LOOP_VINFO_TARGET_COST_DATA (loop_vinfo
);
3216 unsigned inside_cost
, prologue_cost
;
3218 /* loop cost for vec_loop. */
3219 inside_cost
= add_stmt_cost (target_cost_data
, ncopies
, vector_stmt
,
3220 stmt_info
, 0, vect_body
);
3222 /* prologue cost for vec_init and vec_step. */
3223 prologue_cost
= add_stmt_cost (target_cost_data
, 2, scalar_to_vec
,
3224 stmt_info
, 0, vect_prologue
);
3226 if (dump_enabled_p ())
3227 dump_printf_loc (MSG_NOTE
, vect_location
,
3228 "vect_model_induction_cost: inside_cost = %d, "
3229 "prologue_cost = %d .\n", inside_cost
, prologue_cost
);
3233 /* Function get_initial_def_for_induction
3236 STMT - a stmt that performs an induction operation in the loop.
3237 IV_PHI - the initial value of the induction variable
3240 Return a vector variable, initialized with the first VF values of
3241 the induction variable. E.g., for an iv with IV_PHI='X' and
3242 evolution S, for a vector of 4 units, we want to return:
3243 [X, X + S, X + 2*S, X + 3*S]. */
3246 get_initial_def_for_induction (gimple iv_phi
)
3248 stmt_vec_info stmt_vinfo
= vinfo_for_stmt (iv_phi
);
3249 loop_vec_info loop_vinfo
= STMT_VINFO_LOOP_VINFO (stmt_vinfo
);
3250 struct loop
*loop
= LOOP_VINFO_LOOP (loop_vinfo
);
3253 edge pe
= loop_preheader_edge (loop
);
3254 struct loop
*iv_loop
;
3256 tree new_vec
, vec_init
, vec_step
, t
;
3259 gimple init_stmt
, induction_phi
, new_stmt
;
3260 tree induc_def
, vec_def
, vec_dest
;
3261 tree init_expr
, step_expr
;
3262 int vf
= LOOP_VINFO_VECT_FACTOR (loop_vinfo
);
3266 stmt_vec_info phi_info
= vinfo_for_stmt (iv_phi
);
3267 bool nested_in_vect_loop
= false;
3268 gimple_seq stmts
= NULL
;
3269 imm_use_iterator imm_iter
;
3270 use_operand_p use_p
;
3274 gimple_stmt_iterator si
;
3275 basic_block bb
= gimple_bb (iv_phi
);
3279 /* Is phi in an inner-loop, while vectorizing an enclosing outer-loop? */
3280 if (nested_in_vect_loop_p (loop
, iv_phi
))
3282 nested_in_vect_loop
= true;
3283 iv_loop
= loop
->inner
;
3287 gcc_assert (iv_loop
== (gimple_bb (iv_phi
))->loop_father
);
3289 latch_e
= loop_latch_edge (iv_loop
);
3290 loop_arg
= PHI_ARG_DEF_FROM_EDGE (iv_phi
, latch_e
);
3292 step_expr
= STMT_VINFO_LOOP_PHI_EVOLUTION_PART (phi_info
);
3293 gcc_assert (step_expr
!= NULL_TREE
);
3295 pe
= loop_preheader_edge (iv_loop
);
3296 init_expr
= PHI_ARG_DEF_FROM_EDGE (iv_phi
,
3297 loop_preheader_edge (iv_loop
));
3299 vectype
= get_vectype_for_scalar_type (TREE_TYPE (init_expr
));
3300 resvectype
= get_vectype_for_scalar_type (TREE_TYPE (PHI_RESULT (iv_phi
)));
3301 gcc_assert (vectype
);
3302 nunits
= TYPE_VECTOR_SUBPARTS (vectype
);
3303 ncopies
= vf
/ nunits
;
3305 gcc_assert (phi_info
);
3306 gcc_assert (ncopies
>= 1);
3308 /* Convert the step to the desired type. */
3309 step_expr
= force_gimple_operand (fold_convert (TREE_TYPE (vectype
),
3311 &stmts
, true, NULL_TREE
);
3314 new_bb
= gsi_insert_seq_on_edge_immediate (pe
, stmts
);
3315 gcc_assert (!new_bb
);
3318 /* Find the first insertion point in the BB. */
3319 si
= gsi_after_labels (bb
);
3321 /* Create the vector that holds the initial_value of the induction. */
3322 if (nested_in_vect_loop
)
3324 /* iv_loop is nested in the loop to be vectorized. init_expr had already
3325 been created during vectorization of previous stmts. We obtain it
3326 from the STMT_VINFO_VEC_STMT of the defining stmt. */
3327 vec_init
= vect_get_vec_def_for_operand (init_expr
, iv_phi
, NULL
);
3328 /* If the initial value is not of proper type, convert it. */
3329 if (!useless_type_conversion_p (vectype
, TREE_TYPE (vec_init
)))
3331 new_stmt
= gimple_build_assign_with_ops
3333 vect_get_new_vect_var (vectype
, vect_simple_var
, "vec_iv_"),
3334 build1 (VIEW_CONVERT_EXPR
, vectype
, vec_init
), NULL_TREE
);
3335 vec_init
= make_ssa_name (gimple_assign_lhs (new_stmt
), new_stmt
);
3336 gimple_assign_set_lhs (new_stmt
, vec_init
);
3337 new_bb
= gsi_insert_on_edge_immediate (loop_preheader_edge (iv_loop
),
3339 gcc_assert (!new_bb
);
3340 set_vinfo_for_stmt (new_stmt
,
3341 new_stmt_vec_info (new_stmt
, loop_vinfo
, NULL
));
3346 vec
<constructor_elt
, va_gc
> *v
;
3348 /* iv_loop is the loop to be vectorized. Create:
3349 vec_init = [X, X+S, X+2*S, X+3*S] (S = step_expr, X = init_expr) */
3350 new_var
= vect_get_new_vect_var (TREE_TYPE (vectype
),
3351 vect_scalar_var
, "var_");
3352 new_name
= force_gimple_operand (fold_convert (TREE_TYPE (vectype
),
3354 &stmts
, false, new_var
);
3357 new_bb
= gsi_insert_seq_on_edge_immediate (pe
, stmts
);
3358 gcc_assert (!new_bb
);
3361 vec_alloc (v
, nunits
);
3362 bool constant_p
= is_gimple_min_invariant (new_name
);
3363 CONSTRUCTOR_APPEND_ELT (v
, NULL_TREE
, new_name
);
3364 for (i
= 1; i
< nunits
; i
++)
3366 /* Create: new_name_i = new_name + step_expr */
3367 new_name
= fold_build2 (PLUS_EXPR
, TREE_TYPE (new_name
),
3368 new_name
, step_expr
);
3369 if (!is_gimple_min_invariant (new_name
))
3371 init_stmt
= gimple_build_assign (new_var
, new_name
);
3372 new_name
= make_ssa_name (new_var
, init_stmt
);
3373 gimple_assign_set_lhs (init_stmt
, new_name
);
3374 new_bb
= gsi_insert_on_edge_immediate (pe
, init_stmt
);
3375 gcc_assert (!new_bb
);
3376 if (dump_enabled_p ())
3378 dump_printf_loc (MSG_NOTE
, vect_location
,
3379 "created new init_stmt: ");
3380 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, init_stmt
, 0);
3381 dump_printf (MSG_NOTE
, "\n");
3385 CONSTRUCTOR_APPEND_ELT (v
, NULL_TREE
, new_name
);
3387 /* Create a vector from [new_name_0, new_name_1, ..., new_name_nunits-1] */
3389 new_vec
= build_vector_from_ctor (vectype
, v
);
3391 new_vec
= build_constructor (vectype
, v
);
3392 vec_init
= vect_init_vector (iv_phi
, new_vec
, vectype
, NULL
);
3396 /* Create the vector that holds the step of the induction. */
3397 if (nested_in_vect_loop
)
3398 /* iv_loop is nested in the loop to be vectorized. Generate:
3399 vec_step = [S, S, S, S] */
3400 new_name
= step_expr
;
3403 /* iv_loop is the loop to be vectorized. Generate:
3404 vec_step = [VF*S, VF*S, VF*S, VF*S] */
3405 if (SCALAR_FLOAT_TYPE_P (TREE_TYPE (step_expr
)))
3407 expr
= build_int_cst (integer_type_node
, vf
);
3408 expr
= fold_convert (TREE_TYPE (step_expr
), expr
);
3411 expr
= build_int_cst (TREE_TYPE (step_expr
), vf
);
3412 new_name
= fold_build2 (MULT_EXPR
, TREE_TYPE (step_expr
),
3414 if (TREE_CODE (step_expr
) == SSA_NAME
)
3415 new_name
= vect_init_vector (iv_phi
, new_name
,
3416 TREE_TYPE (step_expr
), NULL
);
3419 t
= unshare_expr (new_name
);
3420 gcc_assert (CONSTANT_CLASS_P (new_name
)
3421 || TREE_CODE (new_name
) == SSA_NAME
);
3422 stepvectype
= get_vectype_for_scalar_type (TREE_TYPE (new_name
));
3423 gcc_assert (stepvectype
);
3424 new_vec
= build_vector_from_val (stepvectype
, t
);
3425 vec_step
= vect_init_vector (iv_phi
, new_vec
, stepvectype
, NULL
);
3428 /* Create the following def-use cycle:
3433 vec_iv = PHI <vec_init, vec_loop>
3437 vec_loop = vec_iv + vec_step; */
3439 /* Create the induction-phi that defines the induction-operand. */
3440 vec_dest
= vect_get_new_vect_var (vectype
, vect_simple_var
, "vec_iv_");
3441 induction_phi
= create_phi_node (vec_dest
, iv_loop
->header
);
3442 set_vinfo_for_stmt (induction_phi
,
3443 new_stmt_vec_info (induction_phi
, loop_vinfo
, NULL
));
3444 induc_def
= PHI_RESULT (induction_phi
);
3446 /* Create the iv update inside the loop */
3447 new_stmt
= gimple_build_assign_with_ops (PLUS_EXPR
, vec_dest
,
3448 induc_def
, vec_step
);
3449 vec_def
= make_ssa_name (vec_dest
, new_stmt
);
3450 gimple_assign_set_lhs (new_stmt
, vec_def
);
3451 gsi_insert_before (&si
, new_stmt
, GSI_SAME_STMT
);
3452 set_vinfo_for_stmt (new_stmt
, new_stmt_vec_info (new_stmt
, loop_vinfo
,
3455 /* Set the arguments of the phi node: */
3456 add_phi_arg (induction_phi
, vec_init
, pe
, UNKNOWN_LOCATION
);
3457 add_phi_arg (induction_phi
, vec_def
, loop_latch_edge (iv_loop
),
3461 /* In case that vectorization factor (VF) is bigger than the number
3462 of elements that we can fit in a vectype (nunits), we have to generate
3463 more than one vector stmt - i.e - we need to "unroll" the
3464 vector stmt by a factor VF/nunits. For more details see documentation
3465 in vectorizable_operation. */
3469 stmt_vec_info prev_stmt_vinfo
;
3470 /* FORNOW. This restriction should be relaxed. */
3471 gcc_assert (!nested_in_vect_loop
);
3473 /* Create the vector that holds the step of the induction. */
3474 if (SCALAR_FLOAT_TYPE_P (TREE_TYPE (step_expr
)))
3476 expr
= build_int_cst (integer_type_node
, nunits
);
3477 expr
= fold_convert (TREE_TYPE (step_expr
), expr
);
3480 expr
= build_int_cst (TREE_TYPE (step_expr
), nunits
);
3481 new_name
= fold_build2 (MULT_EXPR
, TREE_TYPE (step_expr
),
3483 if (TREE_CODE (step_expr
) == SSA_NAME
)
3484 new_name
= vect_init_vector (iv_phi
, new_name
,
3485 TREE_TYPE (step_expr
), NULL
);
3486 t
= unshare_expr (new_name
);
3487 gcc_assert (CONSTANT_CLASS_P (new_name
)
3488 || TREE_CODE (new_name
) == SSA_NAME
);
3489 new_vec
= build_vector_from_val (stepvectype
, t
);
3490 vec_step
= vect_init_vector (iv_phi
, new_vec
, stepvectype
, NULL
);
3492 vec_def
= induc_def
;
3493 prev_stmt_vinfo
= vinfo_for_stmt (induction_phi
);
3494 for (i
= 1; i
< ncopies
; i
++)
3496 /* vec_i = vec_prev + vec_step */
3497 new_stmt
= gimple_build_assign_with_ops (PLUS_EXPR
, vec_dest
,
3499 vec_def
= make_ssa_name (vec_dest
, new_stmt
);
3500 gimple_assign_set_lhs (new_stmt
, vec_def
);
3502 gsi_insert_before (&si
, new_stmt
, GSI_SAME_STMT
);
3503 if (!useless_type_conversion_p (resvectype
, vectype
))
3505 new_stmt
= gimple_build_assign_with_ops
3507 vect_get_new_vect_var (resvectype
, vect_simple_var
,
3509 build1 (VIEW_CONVERT_EXPR
, resvectype
,
3510 gimple_assign_lhs (new_stmt
)), NULL_TREE
);
3511 gimple_assign_set_lhs (new_stmt
,
3513 (gimple_assign_lhs (new_stmt
), new_stmt
));
3514 gsi_insert_before (&si
, new_stmt
, GSI_SAME_STMT
);
3516 set_vinfo_for_stmt (new_stmt
,
3517 new_stmt_vec_info (new_stmt
, loop_vinfo
, NULL
));
3518 STMT_VINFO_RELATED_STMT (prev_stmt_vinfo
) = new_stmt
;
3519 prev_stmt_vinfo
= vinfo_for_stmt (new_stmt
);
3523 if (nested_in_vect_loop
)
3525 /* Find the loop-closed exit-phi of the induction, and record
3526 the final vector of induction results: */
3528 FOR_EACH_IMM_USE_FAST (use_p
, imm_iter
, loop_arg
)
3530 gimple use_stmt
= USE_STMT (use_p
);
3531 if (is_gimple_debug (use_stmt
))
3534 if (!flow_bb_inside_loop_p (iv_loop
, gimple_bb (use_stmt
)))
3536 exit_phi
= use_stmt
;
3542 stmt_vec_info stmt_vinfo
= vinfo_for_stmt (exit_phi
);
3543 /* FORNOW. Currently not supporting the case that an inner-loop induction
3544 is not used in the outer-loop (i.e. only outside the outer-loop). */
3545 gcc_assert (STMT_VINFO_RELEVANT_P (stmt_vinfo
)
3546 && !STMT_VINFO_LIVE_P (stmt_vinfo
));
3548 STMT_VINFO_VEC_STMT (stmt_vinfo
) = new_stmt
;
3549 if (dump_enabled_p ())
3551 dump_printf_loc (MSG_NOTE
, vect_location
,
3552 "vector of inductions after inner-loop:");
3553 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, new_stmt
, 0);
3554 dump_printf (MSG_NOTE
, "\n");
3560 if (dump_enabled_p ())
3562 dump_printf_loc (MSG_NOTE
, vect_location
,
3563 "transform induction: created def-use cycle: ");
3564 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, induction_phi
, 0);
3565 dump_printf (MSG_NOTE
, "\n");
3566 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
,
3567 SSA_NAME_DEF_STMT (vec_def
), 0);
3568 dump_printf (MSG_NOTE
, "\n");
3571 STMT_VINFO_VEC_STMT (phi_info
) = induction_phi
;
3572 if (!useless_type_conversion_p (resvectype
, vectype
))
3574 new_stmt
= gimple_build_assign_with_ops
3576 vect_get_new_vect_var (resvectype
, vect_simple_var
, "vec_iv_"),
3577 build1 (VIEW_CONVERT_EXPR
, resvectype
, induc_def
), NULL_TREE
);
3578 induc_def
= make_ssa_name (gimple_assign_lhs (new_stmt
), new_stmt
);
3579 gimple_assign_set_lhs (new_stmt
, induc_def
);
3580 si
= gsi_after_labels (bb
);
3581 gsi_insert_before (&si
, new_stmt
, GSI_SAME_STMT
);
3582 set_vinfo_for_stmt (new_stmt
,
3583 new_stmt_vec_info (new_stmt
, loop_vinfo
, NULL
));
3584 STMT_VINFO_RELATED_STMT (vinfo_for_stmt (new_stmt
))
3585 = STMT_VINFO_RELATED_STMT (vinfo_for_stmt (induction_phi
));
3592 /* Function get_initial_def_for_reduction
3595 STMT - a stmt that performs a reduction operation in the loop.
3596 INIT_VAL - the initial value of the reduction variable
3599 ADJUSTMENT_DEF - a tree that holds a value to be added to the final result
3600 of the reduction (used for adjusting the epilog - see below).
3601 Return a vector variable, initialized according to the operation that STMT
3602 performs. This vector will be used as the initial value of the
3603 vector of partial results.
3605 Option1 (adjust in epilog): Initialize the vector as follows:
3606 add/bit or/xor: [0,0,...,0,0]
3607 mult/bit and: [1,1,...,1,1]
3608 min/max/cond_expr: [init_val,init_val,..,init_val,init_val]
3609 and when necessary (e.g. add/mult case) let the caller know
3610 that it needs to adjust the result by init_val.
3612 Option2: Initialize the vector as follows:
3613 add/bit or/xor: [init_val,0,0,...,0]
3614 mult/bit and: [init_val,1,1,...,1]
3615 min/max/cond_expr: [init_val,init_val,...,init_val]
3616 and no adjustments are needed.
3618 For example, for the following code:
3624 STMT is 's = s + a[i]', and the reduction variable is 's'.
3625 For a vector of 4 units, we want to return either [0,0,0,init_val],
3626 or [0,0,0,0] and let the caller know that it needs to adjust
3627 the result at the end by 'init_val'.
3629 FORNOW, we are using the 'adjust in epilog' scheme, because this way the
3630 initialization vector is simpler (same element in all entries), if
3631 ADJUSTMENT_DEF is not NULL, and Option2 otherwise.
3633 A cost model should help decide between these two schemes. */
3636 get_initial_def_for_reduction (gimple stmt
, tree init_val
,
3637 tree
*adjustment_def
)
3639 stmt_vec_info stmt_vinfo
= vinfo_for_stmt (stmt
);
3640 loop_vec_info loop_vinfo
= STMT_VINFO_LOOP_VINFO (stmt_vinfo
);
3641 struct loop
*loop
= LOOP_VINFO_LOOP (loop_vinfo
);
3642 tree scalar_type
= TREE_TYPE (init_val
);
3643 tree vectype
= get_vectype_for_scalar_type (scalar_type
);
3645 enum tree_code code
= gimple_assign_rhs_code (stmt
);
3650 bool nested_in_vect_loop
= false;
3652 REAL_VALUE_TYPE real_init_val
= dconst0
;
3653 int int_init_val
= 0;
3654 gimple def_stmt
= NULL
;
3656 gcc_assert (vectype
);
3657 nunits
= TYPE_VECTOR_SUBPARTS (vectype
);
3659 gcc_assert (POINTER_TYPE_P (scalar_type
) || INTEGRAL_TYPE_P (scalar_type
)
3660 || SCALAR_FLOAT_TYPE_P (scalar_type
));
3662 if (nested_in_vect_loop_p (loop
, stmt
))
3663 nested_in_vect_loop
= true;
3665 gcc_assert (loop
== (gimple_bb (stmt
))->loop_father
);
3667 /* In case of double reduction we only create a vector variable to be put
3668 in the reduction phi node. The actual statement creation is done in
3669 vect_create_epilog_for_reduction. */
3670 if (adjustment_def
&& nested_in_vect_loop
3671 && TREE_CODE (init_val
) == SSA_NAME
3672 && (def_stmt
= SSA_NAME_DEF_STMT (init_val
))
3673 && gimple_code (def_stmt
) == GIMPLE_PHI
3674 && flow_bb_inside_loop_p (loop
, gimple_bb (def_stmt
))
3675 && vinfo_for_stmt (def_stmt
)
3676 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_stmt
))
3677 == vect_double_reduction_def
)
3679 *adjustment_def
= NULL
;
3680 return vect_create_destination_var (init_val
, vectype
);
3683 if (TREE_CONSTANT (init_val
))
3685 if (SCALAR_FLOAT_TYPE_P (scalar_type
))
3686 init_value
= build_real (scalar_type
, TREE_REAL_CST (init_val
));
3688 init_value
= build_int_cst (scalar_type
, TREE_INT_CST_LOW (init_val
));
3691 init_value
= init_val
;
3695 case WIDEN_SUM_EXPR
:
3703 /* ADJUSMENT_DEF is NULL when called from
3704 vect_create_epilog_for_reduction to vectorize double reduction. */
3707 if (nested_in_vect_loop
)
3708 *adjustment_def
= vect_get_vec_def_for_operand (init_val
, stmt
,
3711 *adjustment_def
= init_val
;
3714 if (code
== MULT_EXPR
)
3716 real_init_val
= dconst1
;
3720 if (code
== BIT_AND_EXPR
)
3723 if (SCALAR_FLOAT_TYPE_P (scalar_type
))
3724 def_for_init
= build_real (scalar_type
, real_init_val
);
3726 def_for_init
= build_int_cst (scalar_type
, int_init_val
);
3728 /* Create a vector of '0' or '1' except the first element. */
3729 elts
= XALLOCAVEC (tree
, nunits
);
3730 for (i
= nunits
- 2; i
>= 0; --i
)
3731 elts
[i
+ 1] = def_for_init
;
3733 /* Option1: the first element is '0' or '1' as well. */
3736 elts
[0] = def_for_init
;
3737 init_def
= build_vector (vectype
, elts
);
3741 /* Option2: the first element is INIT_VAL. */
3743 if (TREE_CONSTANT (init_val
))
3744 init_def
= build_vector (vectype
, elts
);
3747 vec
<constructor_elt
, va_gc
> *v
;
3748 vec_alloc (v
, nunits
);
3749 CONSTRUCTOR_APPEND_ELT (v
, NULL_TREE
, init_val
);
3750 for (i
= 1; i
< nunits
; ++i
)
3751 CONSTRUCTOR_APPEND_ELT (v
, NULL_TREE
, elts
[i
]);
3752 init_def
= build_constructor (vectype
, v
);
3762 *adjustment_def
= NULL_TREE
;
3763 init_def
= vect_get_vec_def_for_operand (init_val
, stmt
, NULL
);
3767 init_def
= build_vector_from_val (vectype
, init_value
);
3778 /* Function vect_create_epilog_for_reduction
3780 Create code at the loop-epilog to finalize the result of a reduction
3783 VECT_DEFS is list of vector of partial results, i.e., the lhs's of vector
3784 reduction statements.
3785 STMT is the scalar reduction stmt that is being vectorized.
3786 NCOPIES is > 1 in case the vectorization factor (VF) is bigger than the
3787 number of elements that we can fit in a vectype (nunits). In this case
3788 we have to generate more than one vector stmt - i.e - we need to "unroll"
3789 the vector stmt by a factor VF/nunits. For more details see documentation
3790 in vectorizable_operation.
3791 REDUC_CODE is the tree-code for the epilog reduction.
3792 REDUCTION_PHIS is a list of the phi-nodes that carry the reduction
3794 REDUC_INDEX is the index of the operand in the right hand side of the
3795 statement that is defined by REDUCTION_PHI.
3796 DOUBLE_REDUC is TRUE if double reduction phi nodes should be handled.
3797 SLP_NODE is an SLP node containing a group of reduction statements. The
3798 first one in this group is STMT.
3801 1. Creates the reduction def-use cycles: sets the arguments for
3803 The loop-entry argument is the vectorized initial-value of the reduction.
3804 The loop-latch argument is taken from VECT_DEFS - the vector of partial
3806 2. "Reduces" each vector of partial results VECT_DEFS into a single result,
3807 by applying the operation specified by REDUC_CODE if available, or by
3808 other means (whole-vector shifts or a scalar loop).
3809 The function also creates a new phi node at the loop exit to preserve
3810 loop-closed form, as illustrated below.
3812 The flow at the entry to this function:
3815 vec_def = phi <null, null> # REDUCTION_PHI
3816 VECT_DEF = vector_stmt # vectorized form of STMT
3817 s_loop = scalar_stmt # (scalar) STMT
3819 s_out0 = phi <s_loop> # (scalar) EXIT_PHI
3823 The above is transformed by this function into:
3826 vec_def = phi <vec_init, VECT_DEF> # REDUCTION_PHI
3827 VECT_DEF = vector_stmt # vectorized form of STMT
3828 s_loop = scalar_stmt # (scalar) STMT
3830 s_out0 = phi <s_loop> # (scalar) EXIT_PHI
3831 v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
3832 v_out2 = reduce <v_out1>
3833 s_out3 = extract_field <v_out2, 0>
3834 s_out4 = adjust_result <s_out3>
3840 vect_create_epilog_for_reduction (vec
<tree
> vect_defs
, gimple stmt
,
3841 int ncopies
, enum tree_code reduc_code
,
3842 vec
<gimple
> reduction_phis
,
3843 int reduc_index
, bool double_reduc
,
3846 stmt_vec_info stmt_info
= vinfo_for_stmt (stmt
);
3847 stmt_vec_info prev_phi_info
;
3849 enum machine_mode mode
;
3850 loop_vec_info loop_vinfo
= STMT_VINFO_LOOP_VINFO (stmt_info
);
3851 struct loop
*loop
= LOOP_VINFO_LOOP (loop_vinfo
), *outer_loop
= NULL
;
3852 basic_block exit_bb
;
3855 gimple new_phi
= NULL
, phi
;
3856 gimple_stmt_iterator exit_gsi
;
3858 tree new_temp
= NULL_TREE
, new_dest
, new_name
, new_scalar_dest
;
3859 gimple epilog_stmt
= NULL
;
3860 enum tree_code code
= gimple_assign_rhs_code (stmt
);
3862 tree bitsize
, bitpos
;
3863 tree adjustment_def
= NULL
;
3864 tree vec_initial_def
= NULL
;
3865 tree reduction_op
, expr
, def
;
3866 tree orig_name
, scalar_result
;
3867 imm_use_iterator imm_iter
, phi_imm_iter
;
3868 use_operand_p use_p
, phi_use_p
;
3869 bool extract_scalar_result
= false;
3870 gimple use_stmt
, orig_stmt
, reduction_phi
= NULL
;
3871 bool nested_in_vect_loop
= false;
3872 auto_vec
<gimple
> new_phis
;
3873 auto_vec
<gimple
> inner_phis
;
3874 enum vect_def_type dt
= vect_unknown_def_type
;
3876 auto_vec
<tree
> scalar_results
;
3877 unsigned int group_size
= 1, k
, ratio
;
3878 auto_vec
<tree
> vec_initial_defs
;
3879 auto_vec
<gimple
> phis
;
3880 bool slp_reduc
= false;
3881 tree new_phi_result
;
3882 gimple inner_phi
= NULL
;
3885 group_size
= SLP_TREE_SCALAR_STMTS (slp_node
).length ();
3887 if (nested_in_vect_loop_p (loop
, stmt
))
3891 nested_in_vect_loop
= true;
3892 gcc_assert (!slp_node
);
3895 switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt
)))
3897 case GIMPLE_SINGLE_RHS
:
3898 gcc_assert (TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt
))
3900 reduction_op
= TREE_OPERAND (gimple_assign_rhs1 (stmt
), reduc_index
);
3902 case GIMPLE_UNARY_RHS
:
3903 reduction_op
= gimple_assign_rhs1 (stmt
);
3905 case GIMPLE_BINARY_RHS
:
3906 reduction_op
= reduc_index
?
3907 gimple_assign_rhs2 (stmt
) : gimple_assign_rhs1 (stmt
);
3909 case GIMPLE_TERNARY_RHS
:
3910 reduction_op
= gimple_op (stmt
, reduc_index
+ 1);
3916 vectype
= get_vectype_for_scalar_type (TREE_TYPE (reduction_op
));
3917 gcc_assert (vectype
);
3918 mode
= TYPE_MODE (vectype
);
3920 /* 1. Create the reduction def-use cycle:
3921 Set the arguments of REDUCTION_PHIS, i.e., transform
3924 vec_def = phi <null, null> # REDUCTION_PHI
3925 VECT_DEF = vector_stmt # vectorized form of STMT
3931 vec_def = phi <vec_init, VECT_DEF> # REDUCTION_PHI
3932 VECT_DEF = vector_stmt # vectorized form of STMT
3935 (in case of SLP, do it for all the phis). */
3937 /* Get the loop-entry arguments. */
3939 vect_get_vec_defs (reduction_op
, NULL_TREE
, stmt
, &vec_initial_defs
,
3940 NULL
, slp_node
, reduc_index
);
3943 vec_initial_defs
.create (1);
3944 /* For the case of reduction, vect_get_vec_def_for_operand returns
3945 the scalar def before the loop, that defines the initial value
3946 of the reduction variable. */
3947 vec_initial_def
= vect_get_vec_def_for_operand (reduction_op
, stmt
,
3949 vec_initial_defs
.quick_push (vec_initial_def
);
3952 /* Set phi nodes arguments. */
3953 FOR_EACH_VEC_ELT (reduction_phis
, i
, phi
)
3955 tree vec_init_def
, def
;
3957 vec_init_def
= force_gimple_operand (vec_initial_defs
[i
], &stmts
,
3959 gsi_insert_seq_on_edge_immediate (loop_preheader_edge (loop
), stmts
);
3961 for (j
= 0; j
< ncopies
; j
++)
3963 /* Set the loop-entry arg of the reduction-phi. */
3964 add_phi_arg (phi
, vec_init_def
, loop_preheader_edge (loop
),
3967 /* Set the loop-latch arg for the reduction-phi. */
3969 def
= vect_get_vec_def_for_stmt_copy (vect_unknown_def_type
, def
);
3971 add_phi_arg (phi
, def
, loop_latch_edge (loop
), UNKNOWN_LOCATION
);
3973 if (dump_enabled_p ())
3975 dump_printf_loc (MSG_NOTE
, vect_location
,
3976 "transform reduction: created def-use cycle: ");
3977 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, phi
, 0);
3978 dump_printf (MSG_NOTE
, "\n");
3979 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, SSA_NAME_DEF_STMT (def
), 0);
3980 dump_printf (MSG_NOTE
, "\n");
3983 phi
= STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi
));
3987 /* 2. Create epilog code.
3988 The reduction epilog code operates across the elements of the vector
3989 of partial results computed by the vectorized loop.
3990 The reduction epilog code consists of:
3992 step 1: compute the scalar result in a vector (v_out2)
3993 step 2: extract the scalar result (s_out3) from the vector (v_out2)
3994 step 3: adjust the scalar result (s_out3) if needed.
3996 Step 1 can be accomplished using one the following three schemes:
3997 (scheme 1) using reduc_code, if available.
3998 (scheme 2) using whole-vector shifts, if available.
3999 (scheme 3) using a scalar loop. In this case steps 1+2 above are
4002 The overall epilog code looks like this:
4004 s_out0 = phi <s_loop> # original EXIT_PHI
4005 v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
4006 v_out2 = reduce <v_out1> # step 1
4007 s_out3 = extract_field <v_out2, 0> # step 2
4008 s_out4 = adjust_result <s_out3> # step 3
4010 (step 3 is optional, and steps 1 and 2 may be combined).
4011 Lastly, the uses of s_out0 are replaced by s_out4. */
4014 /* 2.1 Create new loop-exit-phis to preserve loop-closed form:
4015 v_out1 = phi <VECT_DEF>
4016 Store them in NEW_PHIS. */
4018 exit_bb
= single_exit (loop
)->dest
;
4019 prev_phi_info
= NULL
;
4020 new_phis
.create (vect_defs
.length ());
4021 FOR_EACH_VEC_ELT (vect_defs
, i
, def
)
4023 for (j
= 0; j
< ncopies
; j
++)
4025 tree new_def
= copy_ssa_name (def
, NULL
);
4026 phi
= create_phi_node (new_def
, exit_bb
);
4027 set_vinfo_for_stmt (phi
, new_stmt_vec_info (phi
, loop_vinfo
, NULL
));
4029 new_phis
.quick_push (phi
);
4032 def
= vect_get_vec_def_for_stmt_copy (dt
, def
);
4033 STMT_VINFO_RELATED_STMT (prev_phi_info
) = phi
;
4036 SET_PHI_ARG_DEF (phi
, single_exit (loop
)->dest_idx
, def
);
4037 prev_phi_info
= vinfo_for_stmt (phi
);
4041 /* The epilogue is created for the outer-loop, i.e., for the loop being
4042 vectorized. Create exit phis for the outer loop. */
4046 exit_bb
= single_exit (loop
)->dest
;
4047 inner_phis
.create (vect_defs
.length ());
4048 FOR_EACH_VEC_ELT (new_phis
, i
, phi
)
4050 tree new_result
= copy_ssa_name (PHI_RESULT (phi
), NULL
);
4051 gimple outer_phi
= create_phi_node (new_result
, exit_bb
);
4052 SET_PHI_ARG_DEF (outer_phi
, single_exit (loop
)->dest_idx
,
4054 set_vinfo_for_stmt (outer_phi
, new_stmt_vec_info (outer_phi
,
4056 inner_phis
.quick_push (phi
);
4057 new_phis
[i
] = outer_phi
;
4058 prev_phi_info
= vinfo_for_stmt (outer_phi
);
4059 while (STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi
)))
4061 phi
= STMT_VINFO_RELATED_STMT (vinfo_for_stmt (phi
));
4062 new_result
= copy_ssa_name (PHI_RESULT (phi
), NULL
);
4063 outer_phi
= create_phi_node (new_result
, exit_bb
);
4064 SET_PHI_ARG_DEF (outer_phi
, single_exit (loop
)->dest_idx
,
4066 set_vinfo_for_stmt (outer_phi
, new_stmt_vec_info (outer_phi
,
4068 STMT_VINFO_RELATED_STMT (prev_phi_info
) = outer_phi
;
4069 prev_phi_info
= vinfo_for_stmt (outer_phi
);
4074 exit_gsi
= gsi_after_labels (exit_bb
);
4076 /* 2.2 Get the relevant tree-code to use in the epilog for schemes 2,3
4077 (i.e. when reduc_code is not available) and in the final adjustment
4078 code (if needed). Also get the original scalar reduction variable as
4079 defined in the loop. In case STMT is a "pattern-stmt" (i.e. - it
4080 represents a reduction pattern), the tree-code and scalar-def are
4081 taken from the original stmt that the pattern-stmt (STMT) replaces.
4082 Otherwise (it is a regular reduction) - the tree-code and scalar-def
4083 are taken from STMT. */
4085 orig_stmt
= STMT_VINFO_RELATED_STMT (stmt_info
);
4088 /* Regular reduction */
4093 /* Reduction pattern */
4094 stmt_vec_info stmt_vinfo
= vinfo_for_stmt (orig_stmt
);
4095 gcc_assert (STMT_VINFO_IN_PATTERN_P (stmt_vinfo
));
4096 gcc_assert (STMT_VINFO_RELATED_STMT (stmt_vinfo
) == stmt
);
4099 code
= gimple_assign_rhs_code (orig_stmt
);
4100 /* For MINUS_EXPR the initial vector is [init_val,0,...,0], therefore,
4101 partial results are added and not subtracted. */
4102 if (code
== MINUS_EXPR
)
4105 scalar_dest
= gimple_assign_lhs (orig_stmt
);
4106 scalar_type
= TREE_TYPE (scalar_dest
);
4107 scalar_results
.create (group_size
);
4108 new_scalar_dest
= vect_create_destination_var (scalar_dest
, NULL
);
4109 bitsize
= TYPE_SIZE (scalar_type
);
4111 /* In case this is a reduction in an inner-loop while vectorizing an outer
4112 loop - we don't need to extract a single scalar result at the end of the
4113 inner-loop (unless it is double reduction, i.e., the use of reduction is
4114 outside the outer-loop). The final vector of partial results will be used
4115 in the vectorized outer-loop, or reduced to a scalar result at the end of
4117 if (nested_in_vect_loop
&& !double_reduc
)
4118 goto vect_finalize_reduction
;
4120 /* SLP reduction without reduction chain, e.g.,
4124 b2 = operation (b1) */
4125 slp_reduc
= (slp_node
&& !GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt
)));
4127 /* In case of reduction chain, e.g.,
4130 a3 = operation (a2),
4132 we may end up with more than one vector result. Here we reduce them to
4134 if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt
)))
4136 tree first_vect
= PHI_RESULT (new_phis
[0]);
4138 gimple new_vec_stmt
= NULL
;
4140 vec_dest
= vect_create_destination_var (scalar_dest
, vectype
);
4141 for (k
= 1; k
< new_phis
.length (); k
++)
4143 gimple next_phi
= new_phis
[k
];
4144 tree second_vect
= PHI_RESULT (next_phi
);
4146 tmp
= build2 (code
, vectype
, first_vect
, second_vect
);
4147 new_vec_stmt
= gimple_build_assign (vec_dest
, tmp
);
4148 first_vect
= make_ssa_name (vec_dest
, new_vec_stmt
);
4149 gimple_assign_set_lhs (new_vec_stmt
, first_vect
);
4150 gsi_insert_before (&exit_gsi
, new_vec_stmt
, GSI_SAME_STMT
);
4153 new_phi_result
= first_vect
;
4156 new_phis
.truncate (0);
4157 new_phis
.safe_push (new_vec_stmt
);
4161 new_phi_result
= PHI_RESULT (new_phis
[0]);
4163 /* 2.3 Create the reduction code, using one of the three schemes described
4164 above. In SLP we simply need to extract all the elements from the
4165 vector (without reducing them), so we use scalar shifts. */
4166 if (reduc_code
!= ERROR_MARK
&& !slp_reduc
)
4170 /*** Case 1: Create:
4171 v_out2 = reduc_expr <v_out1> */
4173 if (dump_enabled_p ())
4174 dump_printf_loc (MSG_NOTE
, vect_location
,
4175 "Reduce using direct vector reduction.\n");
4177 vec_dest
= vect_create_destination_var (scalar_dest
, vectype
);
4178 tmp
= build1 (reduc_code
, vectype
, new_phi_result
);
4179 epilog_stmt
= gimple_build_assign (vec_dest
, tmp
);
4180 new_temp
= make_ssa_name (vec_dest
, epilog_stmt
);
4181 gimple_assign_set_lhs (epilog_stmt
, new_temp
);
4182 gsi_insert_before (&exit_gsi
, epilog_stmt
, GSI_SAME_STMT
);
4184 extract_scalar_result
= true;
4188 enum tree_code shift_code
= ERROR_MARK
;
4189 bool have_whole_vector_shift
= true;
4191 int element_bitsize
= tree_to_uhwi (bitsize
);
4192 int vec_size_in_bits
= tree_to_uhwi (TYPE_SIZE (vectype
));
4195 if (optab_handler (vec_shr_optab
, mode
) != CODE_FOR_nothing
)
4196 shift_code
= VEC_RSHIFT_EXPR
;
4198 have_whole_vector_shift
= false;
4200 /* Regardless of whether we have a whole vector shift, if we're
4201 emulating the operation via tree-vect-generic, we don't want
4202 to use it. Only the first round of the reduction is likely
4203 to still be profitable via emulation. */
4204 /* ??? It might be better to emit a reduction tree code here, so that
4205 tree-vect-generic can expand the first round via bit tricks. */
4206 if (!VECTOR_MODE_P (mode
))
4207 have_whole_vector_shift
= false;
4210 optab optab
= optab_for_tree_code (code
, vectype
, optab_default
);
4211 if (optab_handler (optab
, mode
) == CODE_FOR_nothing
)
4212 have_whole_vector_shift
= false;
4215 if (have_whole_vector_shift
&& !slp_reduc
)
4217 /*** Case 2: Create:
4218 for (offset = VS/2; offset >= element_size; offset/=2)
4220 Create: va' = vec_shift <va, offset>
4221 Create: va = vop <va, va'>
4224 if (dump_enabled_p ())
4225 dump_printf_loc (MSG_NOTE
, vect_location
,
4226 "Reduce using vector shifts\n");
4228 vec_dest
= vect_create_destination_var (scalar_dest
, vectype
);
4229 new_temp
= new_phi_result
;
4230 for (bit_offset
= vec_size_in_bits
/2;
4231 bit_offset
>= element_bitsize
;
4234 tree bitpos
= size_int (bit_offset
);
4236 epilog_stmt
= gimple_build_assign_with_ops (shift_code
,
4237 vec_dest
, new_temp
, bitpos
);
4238 new_name
= make_ssa_name (vec_dest
, epilog_stmt
);
4239 gimple_assign_set_lhs (epilog_stmt
, new_name
);
4240 gsi_insert_before (&exit_gsi
, epilog_stmt
, GSI_SAME_STMT
);
4242 epilog_stmt
= gimple_build_assign_with_ops (code
, vec_dest
,
4243 new_name
, new_temp
);
4244 new_temp
= make_ssa_name (vec_dest
, epilog_stmt
);
4245 gimple_assign_set_lhs (epilog_stmt
, new_temp
);
4246 gsi_insert_before (&exit_gsi
, epilog_stmt
, GSI_SAME_STMT
);
4249 extract_scalar_result
= true;
4255 /*** Case 3: Create:
4256 s = extract_field <v_out2, 0>
4257 for (offset = element_size;
4258 offset < vector_size;
4259 offset += element_size;)
4261 Create: s' = extract_field <v_out2, offset>
4262 Create: s = op <s, s'> // For non SLP cases
4265 if (dump_enabled_p ())
4266 dump_printf_loc (MSG_NOTE
, vect_location
,
4267 "Reduce using scalar code.\n");
4269 vec_size_in_bits
= tree_to_uhwi (TYPE_SIZE (vectype
));
4270 FOR_EACH_VEC_ELT (new_phis
, i
, new_phi
)
4272 if (gimple_code (new_phi
) == GIMPLE_PHI
)
4273 vec_temp
= PHI_RESULT (new_phi
);
4275 vec_temp
= gimple_assign_lhs (new_phi
);
4276 rhs
= build3 (BIT_FIELD_REF
, scalar_type
, vec_temp
, bitsize
,
4278 epilog_stmt
= gimple_build_assign (new_scalar_dest
, rhs
);
4279 new_temp
= make_ssa_name (new_scalar_dest
, epilog_stmt
);
4280 gimple_assign_set_lhs (epilog_stmt
, new_temp
);
4281 gsi_insert_before (&exit_gsi
, epilog_stmt
, GSI_SAME_STMT
);
4283 /* In SLP we don't need to apply reduction operation, so we just
4284 collect s' values in SCALAR_RESULTS. */
4286 scalar_results
.safe_push (new_temp
);
4288 for (bit_offset
= element_bitsize
;
4289 bit_offset
< vec_size_in_bits
;
4290 bit_offset
+= element_bitsize
)
4292 tree bitpos
= bitsize_int (bit_offset
);
4293 tree rhs
= build3 (BIT_FIELD_REF
, scalar_type
, vec_temp
,
4296 epilog_stmt
= gimple_build_assign (new_scalar_dest
, rhs
);
4297 new_name
= make_ssa_name (new_scalar_dest
, epilog_stmt
);
4298 gimple_assign_set_lhs (epilog_stmt
, new_name
);
4299 gsi_insert_before (&exit_gsi
, epilog_stmt
, GSI_SAME_STMT
);
4303 /* In SLP we don't need to apply reduction operation, so
4304 we just collect s' values in SCALAR_RESULTS. */
4305 new_temp
= new_name
;
4306 scalar_results
.safe_push (new_name
);
4310 epilog_stmt
= gimple_build_assign_with_ops (code
,
4311 new_scalar_dest
, new_name
, new_temp
);
4312 new_temp
= make_ssa_name (new_scalar_dest
, epilog_stmt
);
4313 gimple_assign_set_lhs (epilog_stmt
, new_temp
);
4314 gsi_insert_before (&exit_gsi
, epilog_stmt
, GSI_SAME_STMT
);
4319 /* The only case where we need to reduce scalar results in SLP, is
4320 unrolling. If the size of SCALAR_RESULTS is greater than
4321 GROUP_SIZE, we reduce them combining elements modulo
4325 tree res
, first_res
, new_res
;
4328 /* Reduce multiple scalar results in case of SLP unrolling. */
4329 for (j
= group_size
; scalar_results
.iterate (j
, &res
);
4332 first_res
= scalar_results
[j
% group_size
];
4333 new_stmt
= gimple_build_assign_with_ops (code
,
4334 new_scalar_dest
, first_res
, res
);
4335 new_res
= make_ssa_name (new_scalar_dest
, new_stmt
);
4336 gimple_assign_set_lhs (new_stmt
, new_res
);
4337 gsi_insert_before (&exit_gsi
, new_stmt
, GSI_SAME_STMT
);
4338 scalar_results
[j
% group_size
] = new_res
;
4342 /* Not SLP - we have one scalar to keep in SCALAR_RESULTS. */
4343 scalar_results
.safe_push (new_temp
);
4345 extract_scalar_result
= false;
4349 /* 2.4 Extract the final scalar result. Create:
4350 s_out3 = extract_field <v_out2, bitpos> */
4352 if (extract_scalar_result
)
4356 if (dump_enabled_p ())
4357 dump_printf_loc (MSG_NOTE
, vect_location
,
4358 "extract scalar result\n");
4360 if (BYTES_BIG_ENDIAN
)
4361 bitpos
= size_binop (MULT_EXPR
,
4362 bitsize_int (TYPE_VECTOR_SUBPARTS (vectype
) - 1),
4363 TYPE_SIZE (scalar_type
));
4365 bitpos
= bitsize_zero_node
;
4367 rhs
= build3 (BIT_FIELD_REF
, scalar_type
, new_temp
, bitsize
, bitpos
);
4368 epilog_stmt
= gimple_build_assign (new_scalar_dest
, rhs
);
4369 new_temp
= make_ssa_name (new_scalar_dest
, epilog_stmt
);
4370 gimple_assign_set_lhs (epilog_stmt
, new_temp
);
4371 gsi_insert_before (&exit_gsi
, epilog_stmt
, GSI_SAME_STMT
);
4372 scalar_results
.safe_push (new_temp
);
4375 vect_finalize_reduction
:
4380 /* 2.5 Adjust the final result by the initial value of the reduction
4381 variable. (When such adjustment is not needed, then
4382 'adjustment_def' is zero). For example, if code is PLUS we create:
4383 new_temp = loop_exit_def + adjustment_def */
4387 gcc_assert (!slp_reduc
);
4388 if (nested_in_vect_loop
)
4390 new_phi
= new_phis
[0];
4391 gcc_assert (TREE_CODE (TREE_TYPE (adjustment_def
)) == VECTOR_TYPE
);
4392 expr
= build2 (code
, vectype
, PHI_RESULT (new_phi
), adjustment_def
);
4393 new_dest
= vect_create_destination_var (scalar_dest
, vectype
);
4397 new_temp
= scalar_results
[0];
4398 gcc_assert (TREE_CODE (TREE_TYPE (adjustment_def
)) != VECTOR_TYPE
);
4399 expr
= build2 (code
, scalar_type
, new_temp
, adjustment_def
);
4400 new_dest
= vect_create_destination_var (scalar_dest
, scalar_type
);
4403 epilog_stmt
= gimple_build_assign (new_dest
, expr
);
4404 new_temp
= make_ssa_name (new_dest
, epilog_stmt
);
4405 gimple_assign_set_lhs (epilog_stmt
, new_temp
);
4406 gsi_insert_before (&exit_gsi
, epilog_stmt
, GSI_SAME_STMT
);
4407 if (nested_in_vect_loop
)
4409 set_vinfo_for_stmt (epilog_stmt
,
4410 new_stmt_vec_info (epilog_stmt
, loop_vinfo
,
4412 STMT_VINFO_RELATED_STMT (vinfo_for_stmt (epilog_stmt
)) =
4413 STMT_VINFO_RELATED_STMT (vinfo_for_stmt (new_phi
));
4416 scalar_results
.quick_push (new_temp
);
4418 scalar_results
[0] = new_temp
;
4421 scalar_results
[0] = new_temp
;
4423 new_phis
[0] = epilog_stmt
;
4426 /* 2.6 Handle the loop-exit phis. Replace the uses of scalar loop-exit
4427 phis with new adjusted scalar results, i.e., replace use <s_out0>
4432 s_out0 = phi <s_loop> # (scalar) EXIT_PHI
4433 v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
4434 v_out2 = reduce <v_out1>
4435 s_out3 = extract_field <v_out2, 0>
4436 s_out4 = adjust_result <s_out3>
4443 s_out0 = phi <s_loop> # (scalar) EXIT_PHI
4444 v_out1 = phi <VECT_DEF> # NEW_EXIT_PHI
4445 v_out2 = reduce <v_out1>
4446 s_out3 = extract_field <v_out2, 0>
4447 s_out4 = adjust_result <s_out3>
4452 /* In SLP reduction chain we reduce vector results into one vector if
4453 necessary, hence we set here GROUP_SIZE to 1. SCALAR_DEST is the LHS of
4454 the last stmt in the reduction chain, since we are looking for the loop
4456 if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt
)))
4458 scalar_dest
= gimple_assign_lhs (
4459 SLP_TREE_SCALAR_STMTS (slp_node
)[group_size
- 1]);
4463 /* In SLP we may have several statements in NEW_PHIS and REDUCTION_PHIS (in
4464 case that GROUP_SIZE is greater than vectorization factor). Therefore, we
4465 need to match SCALAR_RESULTS with corresponding statements. The first
4466 (GROUP_SIZE / number of new vector stmts) scalar results correspond to
4467 the first vector stmt, etc.
4468 (RATIO is equal to (GROUP_SIZE / number of new vector stmts)). */
4469 if (group_size
> new_phis
.length ())
4471 ratio
= group_size
/ new_phis
.length ();
4472 gcc_assert (!(group_size
% new_phis
.length ()));
4477 for (k
= 0; k
< group_size
; k
++)
4481 epilog_stmt
= new_phis
[k
/ ratio
];
4482 reduction_phi
= reduction_phis
[k
/ ratio
];
4484 inner_phi
= inner_phis
[k
/ ratio
];
4489 gimple current_stmt
= SLP_TREE_SCALAR_STMTS (slp_node
)[k
];
4491 orig_stmt
= STMT_VINFO_RELATED_STMT (vinfo_for_stmt (current_stmt
));
4492 /* SLP statements can't participate in patterns. */
4493 gcc_assert (!orig_stmt
);
4494 scalar_dest
= gimple_assign_lhs (current_stmt
);
4498 /* Find the loop-closed-use at the loop exit of the original scalar
4499 result. (The reduction result is expected to have two immediate uses -
4500 one at the latch block, and one at the loop exit). */
4501 FOR_EACH_IMM_USE_FAST (use_p
, imm_iter
, scalar_dest
)
4502 if (!flow_bb_inside_loop_p (loop
, gimple_bb (USE_STMT (use_p
)))
4503 && !is_gimple_debug (USE_STMT (use_p
)))
4504 phis
.safe_push (USE_STMT (use_p
));
4506 /* While we expect to have found an exit_phi because of loop-closed-ssa
4507 form we can end up without one if the scalar cycle is dead. */
4509 FOR_EACH_VEC_ELT (phis
, i
, exit_phi
)
4513 stmt_vec_info exit_phi_vinfo
= vinfo_for_stmt (exit_phi
);
4516 /* FORNOW. Currently not supporting the case that an inner-loop
4517 reduction is not used in the outer-loop (but only outside the
4518 outer-loop), unless it is double reduction. */
4519 gcc_assert ((STMT_VINFO_RELEVANT_P (exit_phi_vinfo
)
4520 && !STMT_VINFO_LIVE_P (exit_phi_vinfo
))
4523 STMT_VINFO_VEC_STMT (exit_phi_vinfo
) = epilog_stmt
;
4525 || STMT_VINFO_DEF_TYPE (exit_phi_vinfo
)
4526 != vect_double_reduction_def
)
4529 /* Handle double reduction:
4531 stmt1: s1 = phi <s0, s2> - double reduction phi (outer loop)
4532 stmt2: s3 = phi <s1, s4> - (regular) reduc phi (inner loop)
4533 stmt3: s4 = use (s3) - (regular) reduc stmt (inner loop)
4534 stmt4: s2 = phi <s4> - double reduction stmt (outer loop)
4536 At that point the regular reduction (stmt2 and stmt3) is
4537 already vectorized, as well as the exit phi node, stmt4.
4538 Here we vectorize the phi node of double reduction, stmt1, and
4539 update all relevant statements. */
4541 /* Go through all the uses of s2 to find double reduction phi
4542 node, i.e., stmt1 above. */
4543 orig_name
= PHI_RESULT (exit_phi
);
4544 FOR_EACH_IMM_USE_STMT (use_stmt
, imm_iter
, orig_name
)
4546 stmt_vec_info use_stmt_vinfo
;
4547 stmt_vec_info new_phi_vinfo
;
4548 tree vect_phi_init
, preheader_arg
, vect_phi_res
, init_def
;
4549 basic_block bb
= gimple_bb (use_stmt
);
4552 /* Check that USE_STMT is really double reduction phi
4554 if (gimple_code (use_stmt
) != GIMPLE_PHI
4555 || gimple_phi_num_args (use_stmt
) != 2
4556 || bb
->loop_father
!= outer_loop
)
4558 use_stmt_vinfo
= vinfo_for_stmt (use_stmt
);
4560 || STMT_VINFO_DEF_TYPE (use_stmt_vinfo
)
4561 != vect_double_reduction_def
)
4564 /* Create vector phi node for double reduction:
4565 vs1 = phi <vs0, vs2>
4566 vs1 was created previously in this function by a call to
4567 vect_get_vec_def_for_operand and is stored in
4569 vs2 is defined by INNER_PHI, the vectorized EXIT_PHI;
4570 vs0 is created here. */
4572 /* Create vector phi node. */
4573 vect_phi
= create_phi_node (vec_initial_def
, bb
);
4574 new_phi_vinfo
= new_stmt_vec_info (vect_phi
,
4575 loop_vec_info_for_loop (outer_loop
), NULL
);
4576 set_vinfo_for_stmt (vect_phi
, new_phi_vinfo
);
4578 /* Create vs0 - initial def of the double reduction phi. */
4579 preheader_arg
= PHI_ARG_DEF_FROM_EDGE (use_stmt
,
4580 loop_preheader_edge (outer_loop
));
4581 init_def
= get_initial_def_for_reduction (stmt
,
4582 preheader_arg
, NULL
);
4583 vect_phi_init
= vect_init_vector (use_stmt
, init_def
,
4586 /* Update phi node arguments with vs0 and vs2. */
4587 add_phi_arg (vect_phi
, vect_phi_init
,
4588 loop_preheader_edge (outer_loop
),
4590 add_phi_arg (vect_phi
, PHI_RESULT (inner_phi
),
4591 loop_latch_edge (outer_loop
), UNKNOWN_LOCATION
);
4592 if (dump_enabled_p ())
4594 dump_printf_loc (MSG_NOTE
, vect_location
,
4595 "created double reduction phi node: ");
4596 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, vect_phi
, 0);
4597 dump_printf (MSG_NOTE
, "\n");
4600 vect_phi_res
= PHI_RESULT (vect_phi
);
4602 /* Replace the use, i.e., set the correct vs1 in the regular
4603 reduction phi node. FORNOW, NCOPIES is always 1, so the
4604 loop is redundant. */
4605 use
= reduction_phi
;
4606 for (j
= 0; j
< ncopies
; j
++)
4608 edge pr_edge
= loop_preheader_edge (loop
);
4609 SET_PHI_ARG_DEF (use
, pr_edge
->dest_idx
, vect_phi_res
);
4610 use
= STMT_VINFO_RELATED_STMT (vinfo_for_stmt (use
));
4617 if (nested_in_vect_loop
)
4626 /* Find the loop-closed-use at the loop exit of the original scalar
4627 result. (The reduction result is expected to have two immediate uses,
4628 one at the latch block, and one at the loop exit). For double
4629 reductions we are looking for exit phis of the outer loop. */
4630 FOR_EACH_IMM_USE_FAST (use_p
, imm_iter
, scalar_dest
)
4632 if (!flow_bb_inside_loop_p (loop
, gimple_bb (USE_STMT (use_p
))))
4634 if (!is_gimple_debug (USE_STMT (use_p
)))
4635 phis
.safe_push (USE_STMT (use_p
));
4639 if (double_reduc
&& gimple_code (USE_STMT (use_p
)) == GIMPLE_PHI
)
4641 tree phi_res
= PHI_RESULT (USE_STMT (use_p
));
4643 FOR_EACH_IMM_USE_FAST (phi_use_p
, phi_imm_iter
, phi_res
)
4645 if (!flow_bb_inside_loop_p (loop
,
4646 gimple_bb (USE_STMT (phi_use_p
)))
4647 && !is_gimple_debug (USE_STMT (phi_use_p
)))
4648 phis
.safe_push (USE_STMT (phi_use_p
));
4654 FOR_EACH_VEC_ELT (phis
, i
, exit_phi
)
4656 /* Replace the uses: */
4657 orig_name
= PHI_RESULT (exit_phi
);
4658 scalar_result
= scalar_results
[k
];
4659 FOR_EACH_IMM_USE_STMT (use_stmt
, imm_iter
, orig_name
)
4660 FOR_EACH_IMM_USE_ON_STMT (use_p
, imm_iter
)
4661 SET_USE (use_p
, scalar_result
);
4669 /* Function vectorizable_reduction.
4671 Check if STMT performs a reduction operation that can be vectorized.
4672 If VEC_STMT is also passed, vectorize the STMT: create a vectorized
4673 stmt to replace it, put it in VEC_STMT, and insert it at GSI.
4674 Return FALSE if not a vectorizable STMT, TRUE otherwise.
4676 This function also handles reduction idioms (patterns) that have been
4677 recognized in advance during vect_pattern_recog. In this case, STMT may be
4679 X = pattern_expr (arg0, arg1, ..., X)
4680 and it's STMT_VINFO_RELATED_STMT points to the last stmt in the original
4681 sequence that had been detected and replaced by the pattern-stmt (STMT).
4683 In some cases of reduction patterns, the type of the reduction variable X is
4684 different than the type of the other arguments of STMT.
4685 In such cases, the vectype that is used when transforming STMT into a vector
4686 stmt is different than the vectype that is used to determine the
4687 vectorization factor, because it consists of a different number of elements
4688 than the actual number of elements that are being operated upon in parallel.
4690 For example, consider an accumulation of shorts into an int accumulator.
4691 On some targets it's possible to vectorize this pattern operating on 8
4692 shorts at a time (hence, the vectype for purposes of determining the
4693 vectorization factor should be V8HI); on the other hand, the vectype that
4694 is used to create the vector form is actually V4SI (the type of the result).
4696 Upon entry to this function, STMT_VINFO_VECTYPE records the vectype that
4697 indicates what is the actual level of parallelism (V8HI in the example), so
4698 that the right vectorization factor would be derived. This vectype
4699 corresponds to the type of arguments to the reduction stmt, and should *NOT*
4700 be used to create the vectorized stmt. The right vectype for the vectorized
4701 stmt is obtained from the type of the result X:
4702 get_vectype_for_scalar_type (TREE_TYPE (X))
4704 This means that, contrary to "regular" reductions (or "regular" stmts in
4705 general), the following equation:
4706 STMT_VINFO_VECTYPE == get_vectype_for_scalar_type (TREE_TYPE (X))
4707 does *NOT* necessarily hold for reduction patterns. */
4710 vectorizable_reduction (gimple stmt
, gimple_stmt_iterator
*gsi
,
4711 gimple
*vec_stmt
, slp_tree slp_node
)
4715 tree loop_vec_def0
= NULL_TREE
, loop_vec_def1
= NULL_TREE
;
4716 stmt_vec_info stmt_info
= vinfo_for_stmt (stmt
);
4717 tree vectype_out
= STMT_VINFO_VECTYPE (stmt_info
);
4718 tree vectype_in
= NULL_TREE
;
4719 loop_vec_info loop_vinfo
= STMT_VINFO_LOOP_VINFO (stmt_info
);
4720 struct loop
*loop
= LOOP_VINFO_LOOP (loop_vinfo
);
4721 enum tree_code code
, orig_code
, epilog_reduc_code
;
4722 enum machine_mode vec_mode
;
4724 optab optab
, reduc_optab
;
4725 tree new_temp
= NULL_TREE
;
4728 enum vect_def_type dt
;
4729 gimple new_phi
= NULL
;
4733 stmt_vec_info orig_stmt_info
;
4734 tree expr
= NULL_TREE
;
4738 stmt_vec_info prev_stmt_info
, prev_phi_info
;
4739 bool single_defuse_cycle
= false;
4740 tree reduc_def
= NULL_TREE
;
4741 gimple new_stmt
= NULL
;
4744 bool nested_cycle
= false, found_nested_cycle_def
= false;
4745 gimple reduc_def_stmt
= NULL
;
4746 /* The default is that the reduction variable is the last in statement. */
4747 int reduc_index
= 2;
4748 bool double_reduc
= false, dummy
;
4750 struct loop
* def_stmt_loop
, *outer_loop
= NULL
;
4752 gimple def_arg_stmt
;
4753 auto_vec
<tree
> vec_oprnds0
;
4754 auto_vec
<tree
> vec_oprnds1
;
4755 auto_vec
<tree
> vect_defs
;
4756 auto_vec
<gimple
> phis
;
4758 tree def0
, def1
, tem
, op0
, op1
= NULL_TREE
;
4760 /* In case of reduction chain we switch to the first stmt in the chain, but
4761 we don't update STMT_INFO, since only the last stmt is marked as reduction
4762 and has reduction properties. */
4763 if (GROUP_FIRST_ELEMENT (vinfo_for_stmt (stmt
)))
4764 stmt
= GROUP_FIRST_ELEMENT (stmt_info
);
4766 if (nested_in_vect_loop_p (loop
, stmt
))
4770 nested_cycle
= true;
4773 /* 1. Is vectorizable reduction? */
4774 /* Not supportable if the reduction variable is used in the loop, unless
4775 it's a reduction chain. */
4776 if (STMT_VINFO_RELEVANT (stmt_info
) > vect_used_in_outer
4777 && !GROUP_FIRST_ELEMENT (stmt_info
))
4780 /* Reductions that are not used even in an enclosing outer-loop,
4781 are expected to be "live" (used out of the loop). */
4782 if (STMT_VINFO_RELEVANT (stmt_info
) == vect_unused_in_scope
4783 && !STMT_VINFO_LIVE_P (stmt_info
))
4786 /* Make sure it was already recognized as a reduction computation. */
4787 if (STMT_VINFO_DEF_TYPE (stmt_info
) != vect_reduction_def
4788 && STMT_VINFO_DEF_TYPE (stmt_info
) != vect_nested_cycle
)
4791 /* 2. Has this been recognized as a reduction pattern?
4793 Check if STMT represents a pattern that has been recognized
4794 in earlier analysis stages. For stmts that represent a pattern,
4795 the STMT_VINFO_RELATED_STMT field records the last stmt in
4796 the original sequence that constitutes the pattern. */
4798 orig_stmt
= STMT_VINFO_RELATED_STMT (stmt_info
);
4801 orig_stmt_info
= vinfo_for_stmt (orig_stmt
);
4802 gcc_assert (STMT_VINFO_IN_PATTERN_P (orig_stmt_info
));
4803 gcc_assert (!STMT_VINFO_IN_PATTERN_P (stmt_info
));
4806 /* 3. Check the operands of the operation. The first operands are defined
4807 inside the loop body. The last operand is the reduction variable,
4808 which is defined by the loop-header-phi. */
4810 gcc_assert (is_gimple_assign (stmt
));
4813 switch (get_gimple_rhs_class (gimple_assign_rhs_code (stmt
)))
4815 case GIMPLE_SINGLE_RHS
:
4816 op_type
= TREE_OPERAND_LENGTH (gimple_assign_rhs1 (stmt
));
4817 if (op_type
== ternary_op
)
4819 tree rhs
= gimple_assign_rhs1 (stmt
);
4820 ops
[0] = TREE_OPERAND (rhs
, 0);
4821 ops
[1] = TREE_OPERAND (rhs
, 1);
4822 ops
[2] = TREE_OPERAND (rhs
, 2);
4823 code
= TREE_CODE (rhs
);
4829 case GIMPLE_BINARY_RHS
:
4830 code
= gimple_assign_rhs_code (stmt
);
4831 op_type
= TREE_CODE_LENGTH (code
);
4832 gcc_assert (op_type
== binary_op
);
4833 ops
[0] = gimple_assign_rhs1 (stmt
);
4834 ops
[1] = gimple_assign_rhs2 (stmt
);
4837 case GIMPLE_TERNARY_RHS
:
4838 code
= gimple_assign_rhs_code (stmt
);
4839 op_type
= TREE_CODE_LENGTH (code
);
4840 gcc_assert (op_type
== ternary_op
);
4841 ops
[0] = gimple_assign_rhs1 (stmt
);
4842 ops
[1] = gimple_assign_rhs2 (stmt
);
4843 ops
[2] = gimple_assign_rhs3 (stmt
);
4846 case GIMPLE_UNARY_RHS
:
4853 if (code
== COND_EXPR
&& slp_node
)
4856 scalar_dest
= gimple_assign_lhs (stmt
);
4857 scalar_type
= TREE_TYPE (scalar_dest
);
4858 if (!POINTER_TYPE_P (scalar_type
) && !INTEGRAL_TYPE_P (scalar_type
)
4859 && !SCALAR_FLOAT_TYPE_P (scalar_type
))
4862 /* Do not try to vectorize bit-precision reductions. */
4863 if ((TYPE_PRECISION (scalar_type
)
4864 != GET_MODE_PRECISION (TYPE_MODE (scalar_type
))))
4867 /* All uses but the last are expected to be defined in the loop.
4868 The last use is the reduction variable. In case of nested cycle this
4869 assumption is not true: we use reduc_index to record the index of the
4870 reduction variable. */
4871 for (i
= 0; i
< op_type
- 1; i
++)
4873 /* The condition of COND_EXPR is checked in vectorizable_condition(). */
4874 if (i
== 0 && code
== COND_EXPR
)
4877 is_simple_use
= vect_is_simple_use_1 (ops
[i
], stmt
, loop_vinfo
, NULL
,
4878 &def_stmt
, &def
, &dt
, &tem
);
4881 gcc_assert (is_simple_use
);
4883 if (dt
!= vect_internal_def
4884 && dt
!= vect_external_def
4885 && dt
!= vect_constant_def
4886 && dt
!= vect_induction_def
4887 && !(dt
== vect_nested_cycle
&& nested_cycle
))
4890 if (dt
== vect_nested_cycle
)
4892 found_nested_cycle_def
= true;
4893 reduc_def_stmt
= def_stmt
;
4898 is_simple_use
= vect_is_simple_use_1 (ops
[i
], stmt
, loop_vinfo
, NULL
,
4899 &def_stmt
, &def
, &dt
, &tem
);
4902 gcc_assert (is_simple_use
);
4903 if (!(dt
== vect_reduction_def
4904 || dt
== vect_nested_cycle
4905 || ((dt
== vect_internal_def
|| dt
== vect_external_def
4906 || dt
== vect_constant_def
|| dt
== vect_induction_def
)
4907 && nested_cycle
&& found_nested_cycle_def
)))
4909 /* For pattern recognized stmts, orig_stmt might be a reduction,
4910 but some helper statements for the pattern might not, or
4911 might be COND_EXPRs with reduction uses in the condition. */
4912 gcc_assert (orig_stmt
);
4915 if (!found_nested_cycle_def
)
4916 reduc_def_stmt
= def_stmt
;
4918 gcc_assert (gimple_code (reduc_def_stmt
) == GIMPLE_PHI
);
4920 gcc_assert (orig_stmt
== vect_is_simple_reduction (loop_vinfo
,
4926 gimple tmp
= vect_is_simple_reduction (loop_vinfo
, reduc_def_stmt
,
4927 !nested_cycle
, &dummy
);
4928 /* We changed STMT to be the first stmt in reduction chain, hence we
4929 check that in this case the first element in the chain is STMT. */
4930 gcc_assert (stmt
== tmp
4931 || GROUP_FIRST_ELEMENT (vinfo_for_stmt (tmp
)) == stmt
);
4934 if (STMT_VINFO_LIVE_P (vinfo_for_stmt (reduc_def_stmt
)))
4937 if (slp_node
|| PURE_SLP_STMT (stmt_info
))
4940 ncopies
= (LOOP_VINFO_VECT_FACTOR (loop_vinfo
)
4941 / TYPE_VECTOR_SUBPARTS (vectype_in
));
4943 gcc_assert (ncopies
>= 1);
4945 vec_mode
= TYPE_MODE (vectype_in
);
4947 if (code
== COND_EXPR
)
4949 if (!vectorizable_condition (stmt
, gsi
, NULL
, ops
[reduc_index
], 0, NULL
))
4951 if (dump_enabled_p ())
4952 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
4953 "unsupported condition in reduction\n");
4960 /* 4. Supportable by target? */
4962 if (code
== LSHIFT_EXPR
|| code
== RSHIFT_EXPR
4963 || code
== LROTATE_EXPR
|| code
== RROTATE_EXPR
)
4965 /* Shifts and rotates are only supported by vectorizable_shifts,
4966 not vectorizable_reduction. */
4967 if (dump_enabled_p ())
4968 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
4969 "unsupported shift or rotation.\n");
4973 /* 4.1. check support for the operation in the loop */
4974 optab
= optab_for_tree_code (code
, vectype_in
, optab_default
);
4977 if (dump_enabled_p ())
4978 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
4984 if (optab_handler (optab
, vec_mode
) == CODE_FOR_nothing
)
4986 if (dump_enabled_p ())
4987 dump_printf (MSG_NOTE
, "op not supported by target.\n");
4989 if (GET_MODE_SIZE (vec_mode
) != UNITS_PER_WORD
4990 || LOOP_VINFO_VECT_FACTOR (loop_vinfo
)
4991 < vect_min_worthwhile_factor (code
))
4994 if (dump_enabled_p ())
4995 dump_printf (MSG_NOTE
, "proceeding using word mode.\n");
4998 /* Worthwhile without SIMD support? */
4999 if (!VECTOR_MODE_P (TYPE_MODE (vectype_in
))
5000 && LOOP_VINFO_VECT_FACTOR (loop_vinfo
)
5001 < vect_min_worthwhile_factor (code
))
5003 if (dump_enabled_p ())
5004 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
5005 "not worthwhile without SIMD support.\n");
5011 /* 4.2. Check support for the epilog operation.
5013 If STMT represents a reduction pattern, then the type of the
5014 reduction variable may be different than the type of the rest
5015 of the arguments. For example, consider the case of accumulation
5016 of shorts into an int accumulator; The original code:
5017 S1: int_a = (int) short_a;
5018 orig_stmt-> S2: int_acc = plus <int_a ,int_acc>;
5021 STMT: int_acc = widen_sum <short_a, int_acc>
5024 1. The tree-code that is used to create the vector operation in the
5025 epilog code (that reduces the partial results) is not the
5026 tree-code of STMT, but is rather the tree-code of the original
5027 stmt from the pattern that STMT is replacing. I.e, in the example
5028 above we want to use 'widen_sum' in the loop, but 'plus' in the
5030 2. The type (mode) we use to check available target support
5031 for the vector operation to be created in the *epilog*, is
5032 determined by the type of the reduction variable (in the example
5033 above we'd check this: optab_handler (plus_optab, vect_int_mode])).
5034 However the type (mode) we use to check available target support
5035 for the vector operation to be created *inside the loop*, is
5036 determined by the type of the other arguments to STMT (in the
5037 example we'd check this: optab_handler (widen_sum_optab,
5040 This is contrary to "regular" reductions, in which the types of all
5041 the arguments are the same as the type of the reduction variable.
5042 For "regular" reductions we can therefore use the same vector type
5043 (and also the same tree-code) when generating the epilog code and
5044 when generating the code inside the loop. */
5048 /* This is a reduction pattern: get the vectype from the type of the
5049 reduction variable, and get the tree-code from orig_stmt. */
5050 orig_code
= gimple_assign_rhs_code (orig_stmt
);
5051 gcc_assert (vectype_out
);
5052 vec_mode
= TYPE_MODE (vectype_out
);
5056 /* Regular reduction: use the same vectype and tree-code as used for
5057 the vector code inside the loop can be used for the epilog code. */
5063 def_bb
= gimple_bb (reduc_def_stmt
);
5064 def_stmt_loop
= def_bb
->loop_father
;
5065 def_arg
= PHI_ARG_DEF_FROM_EDGE (reduc_def_stmt
,
5066 loop_preheader_edge (def_stmt_loop
));
5067 if (TREE_CODE (def_arg
) == SSA_NAME
5068 && (def_arg_stmt
= SSA_NAME_DEF_STMT (def_arg
))
5069 && gimple_code (def_arg_stmt
) == GIMPLE_PHI
5070 && flow_bb_inside_loop_p (outer_loop
, gimple_bb (def_arg_stmt
))
5071 && vinfo_for_stmt (def_arg_stmt
)
5072 && STMT_VINFO_DEF_TYPE (vinfo_for_stmt (def_arg_stmt
))
5073 == vect_double_reduction_def
)
5074 double_reduc
= true;
5077 epilog_reduc_code
= ERROR_MARK
;
5078 if (reduction_code_for_scalar_code (orig_code
, &epilog_reduc_code
))
5080 reduc_optab
= optab_for_tree_code (epilog_reduc_code
, vectype_out
,
5084 if (dump_enabled_p ())
5085 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
5086 "no optab for reduction.\n");
5088 epilog_reduc_code
= ERROR_MARK
;
5092 && optab_handler (reduc_optab
, vec_mode
) == CODE_FOR_nothing
)
5094 if (dump_enabled_p ())
5095 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
5096 "reduc op not supported by target.\n");
5098 epilog_reduc_code
= ERROR_MARK
;
5103 if (!nested_cycle
|| double_reduc
)
5105 if (dump_enabled_p ())
5106 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
5107 "no reduc code for scalar code.\n");
5113 if (double_reduc
&& ncopies
> 1)
5115 if (dump_enabled_p ())
5116 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
5117 "multiple types in double reduction\n");
5122 /* In case of widenning multiplication by a constant, we update the type
5123 of the constant to be the type of the other operand. We check that the
5124 constant fits the type in the pattern recognition pass. */
5125 if (code
== DOT_PROD_EXPR
5126 && !types_compatible_p (TREE_TYPE (ops
[0]), TREE_TYPE (ops
[1])))
5128 if (TREE_CODE (ops
[0]) == INTEGER_CST
)
5129 ops
[0] = fold_convert (TREE_TYPE (ops
[1]), ops
[0]);
5130 else if (TREE_CODE (ops
[1]) == INTEGER_CST
)
5131 ops
[1] = fold_convert (TREE_TYPE (ops
[0]), ops
[1]);
5134 if (dump_enabled_p ())
5135 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
5136 "invalid types in dot-prod\n");
5142 if (!vec_stmt
) /* transformation not required. */
5144 if (!vect_model_reduction_cost (stmt_info
, epilog_reduc_code
, ncopies
))
5146 STMT_VINFO_TYPE (stmt_info
) = reduc_vec_info_type
;
5152 if (dump_enabled_p ())
5153 dump_printf_loc (MSG_NOTE
, vect_location
, "transform reduction.\n");
5155 /* FORNOW: Multiple types are not supported for condition. */
5156 if (code
== COND_EXPR
)
5157 gcc_assert (ncopies
== 1);
5159 /* Create the destination vector */
5160 vec_dest
= vect_create_destination_var (scalar_dest
, vectype_out
);
5162 /* In case the vectorization factor (VF) is bigger than the number
5163 of elements that we can fit in a vectype (nunits), we have to generate
5164 more than one vector stmt - i.e - we need to "unroll" the
5165 vector stmt by a factor VF/nunits. For more details see documentation
5166 in vectorizable_operation. */
5168 /* If the reduction is used in an outer loop we need to generate
5169 VF intermediate results, like so (e.g. for ncopies=2):
5174 (i.e. we generate VF results in 2 registers).
5175 In this case we have a separate def-use cycle for each copy, and therefore
5176 for each copy we get the vector def for the reduction variable from the
5177 respective phi node created for this copy.
5179 Otherwise (the reduction is unused in the loop nest), we can combine
5180 together intermediate results, like so (e.g. for ncopies=2):
5184 (i.e. we generate VF/2 results in a single register).
5185 In this case for each copy we get the vector def for the reduction variable
5186 from the vectorized reduction operation generated in the previous iteration.
5189 if (STMT_VINFO_RELEVANT (stmt_info
) == vect_unused_in_scope
)
5191 single_defuse_cycle
= true;
5195 epilog_copies
= ncopies
;
5197 prev_stmt_info
= NULL
;
5198 prev_phi_info
= NULL
;
5201 vec_num
= SLP_TREE_NUMBER_OF_VEC_STMTS (slp_node
);
5202 gcc_assert (TYPE_VECTOR_SUBPARTS (vectype_out
)
5203 == TYPE_VECTOR_SUBPARTS (vectype_in
));
5208 vec_oprnds0
.create (1);
5209 if (op_type
== ternary_op
)
5210 vec_oprnds1
.create (1);
5213 phis
.create (vec_num
);
5214 vect_defs
.create (vec_num
);
5216 vect_defs
.quick_push (NULL_TREE
);
5218 for (j
= 0; j
< ncopies
; j
++)
5220 if (j
== 0 || !single_defuse_cycle
)
5222 for (i
= 0; i
< vec_num
; i
++)
5224 /* Create the reduction-phi that defines the reduction
5226 new_phi
= create_phi_node (vec_dest
, loop
->header
);
5227 set_vinfo_for_stmt (new_phi
,
5228 new_stmt_vec_info (new_phi
, loop_vinfo
,
5230 if (j
== 0 || slp_node
)
5231 phis
.quick_push (new_phi
);
5235 if (code
== COND_EXPR
)
5237 gcc_assert (!slp_node
);
5238 vectorizable_condition (stmt
, gsi
, vec_stmt
,
5239 PHI_RESULT (phis
[0]),
5241 /* Multiple types are not supported for condition. */
5248 op0
= ops
[!reduc_index
];
5249 if (op_type
== ternary_op
)
5251 if (reduc_index
== 0)
5258 vect_get_vec_defs (op0
, op1
, stmt
, &vec_oprnds0
, &vec_oprnds1
,
5262 loop_vec_def0
= vect_get_vec_def_for_operand (ops
[!reduc_index
],
5264 vec_oprnds0
.quick_push (loop_vec_def0
);
5265 if (op_type
== ternary_op
)
5267 loop_vec_def1
= vect_get_vec_def_for_operand (op1
, stmt
,
5269 vec_oprnds1
.quick_push (loop_vec_def1
);
5277 enum vect_def_type dt
;
5281 vect_is_simple_use (ops
[!reduc_index
], stmt
, loop_vinfo
, NULL
,
5282 &dummy_stmt
, &dummy
, &dt
);
5283 loop_vec_def0
= vect_get_vec_def_for_stmt_copy (dt
,
5285 vec_oprnds0
[0] = loop_vec_def0
;
5286 if (op_type
== ternary_op
)
5288 vect_is_simple_use (op1
, stmt
, loop_vinfo
, NULL
, &dummy_stmt
,
5290 loop_vec_def1
= vect_get_vec_def_for_stmt_copy (dt
,
5292 vec_oprnds1
[0] = loop_vec_def1
;
5296 if (single_defuse_cycle
)
5297 reduc_def
= gimple_assign_lhs (new_stmt
);
5299 STMT_VINFO_RELATED_STMT (prev_phi_info
) = new_phi
;
5302 FOR_EACH_VEC_ELT (vec_oprnds0
, i
, def0
)
5305 reduc_def
= PHI_RESULT (phis
[i
]);
5308 if (!single_defuse_cycle
|| j
== 0)
5309 reduc_def
= PHI_RESULT (new_phi
);
5312 def1
= ((op_type
== ternary_op
)
5313 ? vec_oprnds1
[i
] : NULL
);
5314 if (op_type
== binary_op
)
5316 if (reduc_index
== 0)
5317 expr
= build2 (code
, vectype_out
, reduc_def
, def0
);
5319 expr
= build2 (code
, vectype_out
, def0
, reduc_def
);
5323 if (reduc_index
== 0)
5324 expr
= build3 (code
, vectype_out
, reduc_def
, def0
, def1
);
5327 if (reduc_index
== 1)
5328 expr
= build3 (code
, vectype_out
, def0
, reduc_def
, def1
);
5330 expr
= build3 (code
, vectype_out
, def0
, def1
, reduc_def
);
5334 new_stmt
= gimple_build_assign (vec_dest
, expr
);
5335 new_temp
= make_ssa_name (vec_dest
, new_stmt
);
5336 gimple_assign_set_lhs (new_stmt
, new_temp
);
5337 vect_finish_stmt_generation (stmt
, new_stmt
, gsi
);
5341 SLP_TREE_VEC_STMTS (slp_node
).quick_push (new_stmt
);
5342 vect_defs
.quick_push (new_temp
);
5345 vect_defs
[0] = new_temp
;
5352 STMT_VINFO_VEC_STMT (stmt_info
) = *vec_stmt
= new_stmt
;
5354 STMT_VINFO_RELATED_STMT (prev_stmt_info
) = new_stmt
;
5356 prev_stmt_info
= vinfo_for_stmt (new_stmt
);
5357 prev_phi_info
= vinfo_for_stmt (new_phi
);
5360 /* Finalize the reduction-phi (set its arguments) and create the
5361 epilog reduction code. */
5362 if ((!single_defuse_cycle
|| code
== COND_EXPR
) && !slp_node
)
5364 new_temp
= gimple_assign_lhs (*vec_stmt
);
5365 vect_defs
[0] = new_temp
;
5368 vect_create_epilog_for_reduction (vect_defs
, stmt
, epilog_copies
,
5369 epilog_reduc_code
, phis
, reduc_index
,
5370 double_reduc
, slp_node
);
5375 /* Function vect_min_worthwhile_factor.
5377 For a loop where we could vectorize the operation indicated by CODE,
5378 return the minimum vectorization factor that makes it worthwhile
5379 to use generic vectors. */
5381 vect_min_worthwhile_factor (enum tree_code code
)
5402 /* Function vectorizable_induction
5404 Check if PHI performs an induction computation that can be vectorized.
5405 If VEC_STMT is also passed, vectorize the induction PHI: create a vectorized
5406 phi to replace it, put it in VEC_STMT, and add it to the same basic block.
5407 Return FALSE if not a vectorizable STMT, TRUE otherwise. */
5410 vectorizable_induction (gimple phi
, gimple_stmt_iterator
*gsi ATTRIBUTE_UNUSED
,
5413 stmt_vec_info stmt_info
= vinfo_for_stmt (phi
);
5414 tree vectype
= STMT_VINFO_VECTYPE (stmt_info
);
5415 loop_vec_info loop_vinfo
= STMT_VINFO_LOOP_VINFO (stmt_info
);
5416 struct loop
*loop
= LOOP_VINFO_LOOP (loop_vinfo
);
5417 int nunits
= TYPE_VECTOR_SUBPARTS (vectype
);
5418 int ncopies
= LOOP_VINFO_VECT_FACTOR (loop_vinfo
) / nunits
;
5421 gcc_assert (ncopies
>= 1);
5422 /* FORNOW. These restrictions should be relaxed. */
5423 if (nested_in_vect_loop_p (loop
, phi
))
5425 imm_use_iterator imm_iter
;
5426 use_operand_p use_p
;
5433 if (dump_enabled_p ())
5434 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
5435 "multiple types in nested loop.\n");
5440 latch_e
= loop_latch_edge (loop
->inner
);
5441 loop_arg
= PHI_ARG_DEF_FROM_EDGE (phi
, latch_e
);
5442 FOR_EACH_IMM_USE_FAST (use_p
, imm_iter
, loop_arg
)
5444 gimple use_stmt
= USE_STMT (use_p
);
5445 if (is_gimple_debug (use_stmt
))
5448 if (!flow_bb_inside_loop_p (loop
->inner
, gimple_bb (use_stmt
)))
5450 exit_phi
= use_stmt
;
5456 stmt_vec_info exit_phi_vinfo
= vinfo_for_stmt (exit_phi
);
5457 if (!(STMT_VINFO_RELEVANT_P (exit_phi_vinfo
)
5458 && !STMT_VINFO_LIVE_P (exit_phi_vinfo
)))
5460 if (dump_enabled_p ())
5461 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
5462 "inner-loop induction only used outside "
5463 "of the outer vectorized loop.\n");
5469 if (!STMT_VINFO_RELEVANT_P (stmt_info
))
5472 /* FORNOW: SLP not supported. */
5473 if (STMT_SLP_TYPE (stmt_info
))
5476 gcc_assert (STMT_VINFO_DEF_TYPE (stmt_info
) == vect_induction_def
);
5478 if (gimple_code (phi
) != GIMPLE_PHI
)
5481 if (!vec_stmt
) /* transformation not required. */
5483 STMT_VINFO_TYPE (stmt_info
) = induc_vec_info_type
;
5484 if (dump_enabled_p ())
5485 dump_printf_loc (MSG_NOTE
, vect_location
,
5486 "=== vectorizable_induction ===\n");
5487 vect_model_induction_cost (stmt_info
, ncopies
);
5493 if (dump_enabled_p ())
5494 dump_printf_loc (MSG_NOTE
, vect_location
, "transform induction phi.\n");
5496 vec_def
= get_initial_def_for_induction (phi
);
5497 *vec_stmt
= SSA_NAME_DEF_STMT (vec_def
);
5501 /* Function vectorizable_live_operation.
5503 STMT computes a value that is used outside the loop. Check if
5504 it can be supported. */
5507 vectorizable_live_operation (gimple stmt
,
5508 gimple_stmt_iterator
*gsi ATTRIBUTE_UNUSED
,
5511 stmt_vec_info stmt_info
= vinfo_for_stmt (stmt
);
5512 loop_vec_info loop_vinfo
= STMT_VINFO_LOOP_VINFO (stmt_info
);
5513 struct loop
*loop
= LOOP_VINFO_LOOP (loop_vinfo
);
5519 enum vect_def_type dt
;
5520 enum tree_code code
;
5521 enum gimple_rhs_class rhs_class
;
5523 gcc_assert (STMT_VINFO_LIVE_P (stmt_info
));
5525 if (STMT_VINFO_DEF_TYPE (stmt_info
) == vect_reduction_def
)
5528 if (!is_gimple_assign (stmt
))
5530 if (gimple_call_internal_p (stmt
)
5531 && gimple_call_internal_fn (stmt
) == IFN_GOMP_SIMD_LANE
5532 && gimple_call_lhs (stmt
)
5534 && TREE_CODE (gimple_call_arg (stmt
, 0)) == SSA_NAME
5536 == SSA_NAME_VAR (gimple_call_arg (stmt
, 0)))
5538 edge e
= single_exit (loop
);
5539 basic_block merge_bb
= e
->dest
;
5540 imm_use_iterator imm_iter
;
5541 use_operand_p use_p
;
5542 tree lhs
= gimple_call_lhs (stmt
);
5544 FOR_EACH_IMM_USE_FAST (use_p
, imm_iter
, lhs
)
5546 gimple use_stmt
= USE_STMT (use_p
);
5547 if (gimple_code (use_stmt
) == GIMPLE_PHI
5548 && gimple_bb (use_stmt
) == merge_bb
)
5553 = build_int_cst (unsigned_type_node
,
5554 loop_vinfo
->vectorization_factor
- 1);
5555 SET_PHI_ARG_DEF (use_stmt
, e
->dest_idx
, vfm1
);
5565 if (TREE_CODE (gimple_assign_lhs (stmt
)) != SSA_NAME
)
5568 /* FORNOW. CHECKME. */
5569 if (nested_in_vect_loop_p (loop
, stmt
))
5572 code
= gimple_assign_rhs_code (stmt
);
5573 op_type
= TREE_CODE_LENGTH (code
);
5574 rhs_class
= get_gimple_rhs_class (code
);
5575 gcc_assert (rhs_class
!= GIMPLE_UNARY_RHS
|| op_type
== unary_op
);
5576 gcc_assert (rhs_class
!= GIMPLE_BINARY_RHS
|| op_type
== binary_op
);
5578 /* FORNOW: support only if all uses are invariant. This means
5579 that the scalar operations can remain in place, unvectorized.
5580 The original last scalar value that they compute will be used. */
5582 for (i
= 0; i
< op_type
; i
++)
5584 if (rhs_class
== GIMPLE_SINGLE_RHS
)
5585 op
= TREE_OPERAND (gimple_op (stmt
, 1), i
);
5587 op
= gimple_op (stmt
, i
+ 1);
5589 && !vect_is_simple_use (op
, stmt
, loop_vinfo
, NULL
, &def_stmt
, &def
,
5592 if (dump_enabled_p ())
5593 dump_printf_loc (MSG_MISSED_OPTIMIZATION
, vect_location
,
5594 "use not simple.\n");
5598 if (dt
!= vect_external_def
&& dt
!= vect_constant_def
)
5602 /* No transformation is required for the cases we currently support. */
5606 /* Kill any debug uses outside LOOP of SSA names defined in STMT. */
5609 vect_loop_kill_debug_uses (struct loop
*loop
, gimple stmt
)
5611 ssa_op_iter op_iter
;
5612 imm_use_iterator imm_iter
;
5613 def_operand_p def_p
;
5616 FOR_EACH_PHI_OR_STMT_DEF (def_p
, stmt
, op_iter
, SSA_OP_DEF
)
5618 FOR_EACH_IMM_USE_STMT (ustmt
, imm_iter
, DEF_FROM_PTR (def_p
))
5622 if (!is_gimple_debug (ustmt
))
5625 bb
= gimple_bb (ustmt
);
5627 if (!flow_bb_inside_loop_p (loop
, bb
))
5629 if (gimple_debug_bind_p (ustmt
))
5631 if (dump_enabled_p ())
5632 dump_printf_loc (MSG_NOTE
, vect_location
,
5633 "killing debug use\n");
5635 gimple_debug_bind_reset_value (ustmt
);
5636 update_stmt (ustmt
);
5646 /* This function builds ni_name = number of iterations. Statements
5647 are emitted on the loop preheader edge. */
5650 vect_build_loop_niters (loop_vec_info loop_vinfo
)
5652 tree ni
= unshare_expr (LOOP_VINFO_NITERS (loop_vinfo
));
5653 if (TREE_CODE (ni
) == INTEGER_CST
)
5658 gimple_seq stmts
= NULL
;
5659 edge pe
= loop_preheader_edge (LOOP_VINFO_LOOP (loop_vinfo
));
5661 var
= create_tmp_var (TREE_TYPE (ni
), "niters");
5662 ni_name
= force_gimple_operand (ni
, &stmts
, false, var
);
5664 gsi_insert_seq_on_edge_immediate (pe
, stmts
);
5671 /* This function generates the following statements:
5673 ni_name = number of iterations loop executes
5674 ratio = ni_name / vf
5675 ratio_mult_vf_name = ratio * vf
5677 and places them on the loop preheader edge. */
5680 vect_generate_tmps_on_preheader (loop_vec_info loop_vinfo
,
5682 tree
*ratio_mult_vf_name_ptr
,
5683 tree
*ratio_name_ptr
)
5685 tree ni_minus_gap_name
;
5688 tree ratio_mult_vf_name
;
5689 int vf
= LOOP_VINFO_VECT_FACTOR (loop_vinfo
);
5690 edge pe
= loop_preheader_edge (LOOP_VINFO_LOOP (loop_vinfo
));
5693 log_vf
= build_int_cst (TREE_TYPE (ni_name
), exact_log2 (vf
));
5695 /* If epilogue loop is required because of data accesses with gaps, we
5696 subtract one iteration from the total number of iterations here for
5697 correct calculation of RATIO. */
5698 if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo
))
5700 ni_minus_gap_name
= fold_build2 (MINUS_EXPR
, TREE_TYPE (ni_name
),
5702 build_one_cst (TREE_TYPE (ni_name
)));
5703 if (!is_gimple_val (ni_minus_gap_name
))
5705 var
= create_tmp_var (TREE_TYPE (ni_name
), "ni_gap");
5706 gimple stmts
= NULL
;
5707 ni_minus_gap_name
= force_gimple_operand (ni_minus_gap_name
, &stmts
,
5709 gsi_insert_seq_on_edge_immediate (pe
, stmts
);
5713 ni_minus_gap_name
= ni_name
;
5715 /* Create: ratio = ni >> log2(vf) */
5716 /* ??? As we have ni == number of latch executions + 1, ni could
5717 have overflown to zero. So avoid computing ratio based on ni
5718 but compute it using the fact that we know ratio will be at least
5719 one, thus via (ni - vf) >> log2(vf) + 1. */
5721 = fold_build2 (PLUS_EXPR
, TREE_TYPE (ni_name
),
5722 fold_build2 (RSHIFT_EXPR
, TREE_TYPE (ni_name
),
5723 fold_build2 (MINUS_EXPR
, TREE_TYPE (ni_name
),
5726 (TREE_TYPE (ni_name
), vf
)),
5728 build_int_cst (TREE_TYPE (ni_name
), 1));
5729 if (!is_gimple_val (ratio_name
))
5731 var
= create_tmp_var (TREE_TYPE (ni_name
), "bnd");
5732 gimple stmts
= NULL
;
5733 ratio_name
= force_gimple_operand (ratio_name
, &stmts
, true, var
);
5734 gsi_insert_seq_on_edge_immediate (pe
, stmts
);
5736 *ratio_name_ptr
= ratio_name
;
5738 /* Create: ratio_mult_vf = ratio << log2 (vf). */
5740 if (ratio_mult_vf_name_ptr
)
5742 ratio_mult_vf_name
= fold_build2 (LSHIFT_EXPR
, TREE_TYPE (ratio_name
),
5743 ratio_name
, log_vf
);
5744 if (!is_gimple_val (ratio_mult_vf_name
))
5746 var
= create_tmp_var (TREE_TYPE (ni_name
), "ratio_mult_vf");
5747 gimple stmts
= NULL
;
5748 ratio_mult_vf_name
= force_gimple_operand (ratio_mult_vf_name
, &stmts
,
5750 gsi_insert_seq_on_edge_immediate (pe
, stmts
);
5752 *ratio_mult_vf_name_ptr
= ratio_mult_vf_name
;
5759 /* Function vect_transform_loop.
5761 The analysis phase has determined that the loop is vectorizable.
5762 Vectorize the loop - created vectorized stmts to replace the scalar
5763 stmts in the loop, and update the loop exit condition. */
5766 vect_transform_loop (loop_vec_info loop_vinfo
)
5768 struct loop
*loop
= LOOP_VINFO_LOOP (loop_vinfo
);
5769 basic_block
*bbs
= LOOP_VINFO_BBS (loop_vinfo
);
5770 int nbbs
= loop
->num_nodes
;
5771 gimple_stmt_iterator si
;
5774 int vectorization_factor
= LOOP_VINFO_VECT_FACTOR (loop_vinfo
);
5776 bool slp_scheduled
= false;
5777 gimple stmt
, pattern_stmt
;
5778 gimple_seq pattern_def_seq
= NULL
;
5779 gimple_stmt_iterator pattern_def_si
= gsi_none ();
5780 bool transform_pattern_stmt
= false;
5781 bool check_profitability
= false;
5783 /* Record number of iterations before we started tampering with the profile. */
5784 gcov_type expected_iterations
= expected_loop_iterations_unbounded (loop
);
5786 if (dump_enabled_p ())
5787 dump_printf_loc (MSG_NOTE
, vect_location
, "=== vec_transform_loop ===\n");
5789 /* If profile is inprecise, we have chance to fix it up. */
5790 if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo
))
5791 expected_iterations
= LOOP_VINFO_INT_NITERS (loop_vinfo
);
5793 /* Use the more conservative vectorization threshold. If the number
5794 of iterations is constant assume the cost check has been performed
5795 by our caller. If the threshold makes all loops profitable that
5796 run at least the vectorization factor number of times checking
5797 is pointless, too. */
5798 th
= LOOP_VINFO_COST_MODEL_THRESHOLD (loop_vinfo
);
5799 if (th
>= LOOP_VINFO_VECT_FACTOR (loop_vinfo
) - 1
5800 && !LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo
))
5802 if (dump_enabled_p ())
5803 dump_printf_loc (MSG_NOTE
, vect_location
,
5804 "Profitability threshold is %d loop iterations.\n",
5806 check_profitability
= true;
5809 /* Version the loop first, if required, so the profitability check
5812 if (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (loop_vinfo
)
5813 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (loop_vinfo
))
5815 vect_loop_versioning (loop_vinfo
, th
, check_profitability
);
5816 check_profitability
= false;
5819 tree ni_name
= vect_build_loop_niters (loop_vinfo
);
5820 LOOP_VINFO_NITERS_UNCHANGED (loop_vinfo
) = ni_name
;
5822 /* Peel the loop if there are data refs with unknown alignment.
5823 Only one data ref with unknown store is allowed. */
5825 if (LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo
))
5827 vect_do_peeling_for_alignment (loop_vinfo
, ni_name
,
5828 th
, check_profitability
);
5829 check_profitability
= false;
5830 /* The above adjusts LOOP_VINFO_NITERS, so cause ni_name to
5832 ni_name
= NULL_TREE
;
5835 /* If the loop has a symbolic number of iterations 'n' (i.e. it's not a
5836 compile time constant), or it is a constant that doesn't divide by the
5837 vectorization factor, then an epilog loop needs to be created.
5838 We therefore duplicate the loop: the original loop will be vectorized,
5839 and will compute the first (n/VF) iterations. The second copy of the loop
5840 will remain scalar and will compute the remaining (n%VF) iterations.
5841 (VF is the vectorization factor). */
5843 if (LOOP_VINFO_PEELING_FOR_NITER (loop_vinfo
)
5844 || LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo
))
5848 ni_name
= vect_build_loop_niters (loop_vinfo
);
5849 vect_generate_tmps_on_preheader (loop_vinfo
, ni_name
, &ratio_mult_vf
,
5851 vect_do_peeling_for_loop_bound (loop_vinfo
, ni_name
, ratio_mult_vf
,
5852 th
, check_profitability
);
5854 else if (LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo
))
5855 ratio
= build_int_cst (TREE_TYPE (LOOP_VINFO_NITERS (loop_vinfo
)),
5856 LOOP_VINFO_INT_NITERS (loop_vinfo
) / vectorization_factor
);
5860 ni_name
= vect_build_loop_niters (loop_vinfo
);
5861 vect_generate_tmps_on_preheader (loop_vinfo
, ni_name
, NULL
, &ratio
);
5864 /* 1) Make sure the loop header has exactly two entries
5865 2) Make sure we have a preheader basic block. */
5867 gcc_assert (EDGE_COUNT (loop
->header
->preds
) == 2);
5869 split_edge (loop_preheader_edge (loop
));
5871 /* FORNOW: the vectorizer supports only loops which body consist
5872 of one basic block (header + empty latch). When the vectorizer will
5873 support more involved loop forms, the order by which the BBs are
5874 traversed need to be reconsidered. */
5876 for (i
= 0; i
< nbbs
; i
++)
5878 basic_block bb
= bbs
[i
];
5879 stmt_vec_info stmt_info
;
5882 for (si
= gsi_start_phis (bb
); !gsi_end_p (si
); gsi_next (&si
))
5884 phi
= gsi_stmt (si
);
5885 if (dump_enabled_p ())
5887 dump_printf_loc (MSG_NOTE
, vect_location
,
5888 "------>vectorizing phi: ");
5889 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, phi
, 0);
5890 dump_printf (MSG_NOTE
, "\n");
5892 stmt_info
= vinfo_for_stmt (phi
);
5896 if (MAY_HAVE_DEBUG_STMTS
&& !STMT_VINFO_LIVE_P (stmt_info
))
5897 vect_loop_kill_debug_uses (loop
, phi
);
5899 if (!STMT_VINFO_RELEVANT_P (stmt_info
)
5900 && !STMT_VINFO_LIVE_P (stmt_info
))
5903 if (STMT_VINFO_VECTYPE (stmt_info
)
5904 && (TYPE_VECTOR_SUBPARTS (STMT_VINFO_VECTYPE (stmt_info
))
5905 != (unsigned HOST_WIDE_INT
) vectorization_factor
)
5906 && dump_enabled_p ())
5907 dump_printf_loc (MSG_NOTE
, vect_location
, "multiple-types.\n");
5909 if (STMT_VINFO_DEF_TYPE (stmt_info
) == vect_induction_def
)
5911 if (dump_enabled_p ())
5912 dump_printf_loc (MSG_NOTE
, vect_location
, "transform phi.\n");
5913 vect_transform_stmt (phi
, NULL
, NULL
, NULL
, NULL
);
5917 pattern_stmt
= NULL
;
5918 for (si
= gsi_start_bb (bb
); !gsi_end_p (si
) || transform_pattern_stmt
;)
5922 if (transform_pattern_stmt
)
5923 stmt
= pattern_stmt
;
5926 stmt
= gsi_stmt (si
);
5927 /* During vectorization remove existing clobber stmts. */
5928 if (gimple_clobber_p (stmt
))
5930 unlink_stmt_vdef (stmt
);
5931 gsi_remove (&si
, true);
5932 release_defs (stmt
);
5937 if (dump_enabled_p ())
5939 dump_printf_loc (MSG_NOTE
, vect_location
,
5940 "------>vectorizing statement: ");
5941 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
, stmt
, 0);
5942 dump_printf (MSG_NOTE
, "\n");
5945 stmt_info
= vinfo_for_stmt (stmt
);
5947 /* vector stmts created in the outer-loop during vectorization of
5948 stmts in an inner-loop may not have a stmt_info, and do not
5949 need to be vectorized. */
5956 if (MAY_HAVE_DEBUG_STMTS
&& !STMT_VINFO_LIVE_P (stmt_info
))
5957 vect_loop_kill_debug_uses (loop
, stmt
);
5959 if (!STMT_VINFO_RELEVANT_P (stmt_info
)
5960 && !STMT_VINFO_LIVE_P (stmt_info
))
5962 if (STMT_VINFO_IN_PATTERN_P (stmt_info
)
5963 && (pattern_stmt
= STMT_VINFO_RELATED_STMT (stmt_info
))
5964 && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt
))
5965 || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt
))))
5967 stmt
= pattern_stmt
;
5968 stmt_info
= vinfo_for_stmt (stmt
);
5976 else if (STMT_VINFO_IN_PATTERN_P (stmt_info
)
5977 && (pattern_stmt
= STMT_VINFO_RELATED_STMT (stmt_info
))
5978 && (STMT_VINFO_RELEVANT_P (vinfo_for_stmt (pattern_stmt
))
5979 || STMT_VINFO_LIVE_P (vinfo_for_stmt (pattern_stmt
))))
5980 transform_pattern_stmt
= true;
5982 /* If pattern statement has def stmts, vectorize them too. */
5983 if (is_pattern_stmt_p (stmt_info
))
5985 if (pattern_def_seq
== NULL
)
5987 pattern_def_seq
= STMT_VINFO_PATTERN_DEF_SEQ (stmt_info
);
5988 pattern_def_si
= gsi_start (pattern_def_seq
);
5990 else if (!gsi_end_p (pattern_def_si
))
5991 gsi_next (&pattern_def_si
);
5992 if (pattern_def_seq
!= NULL
)
5994 gimple pattern_def_stmt
= NULL
;
5995 stmt_vec_info pattern_def_stmt_info
= NULL
;
5997 while (!gsi_end_p (pattern_def_si
))
5999 pattern_def_stmt
= gsi_stmt (pattern_def_si
);
6000 pattern_def_stmt_info
6001 = vinfo_for_stmt (pattern_def_stmt
);
6002 if (STMT_VINFO_RELEVANT_P (pattern_def_stmt_info
)
6003 || STMT_VINFO_LIVE_P (pattern_def_stmt_info
))
6005 gsi_next (&pattern_def_si
);
6008 if (!gsi_end_p (pattern_def_si
))
6010 if (dump_enabled_p ())
6012 dump_printf_loc (MSG_NOTE
, vect_location
,
6013 "==> vectorizing pattern def "
6015 dump_gimple_stmt (MSG_NOTE
, TDF_SLIM
,
6016 pattern_def_stmt
, 0);
6017 dump_printf (MSG_NOTE
, "\n");
6020 stmt
= pattern_def_stmt
;
6021 stmt_info
= pattern_def_stmt_info
;
6025 pattern_def_si
= gsi_none ();
6026 transform_pattern_stmt
= false;
6030 transform_pattern_stmt
= false;
6033 if (STMT_VINFO_VECTYPE (stmt_info
))
6037 TYPE_VECTOR_SUBPARTS (STMT_VINFO_VECTYPE (stmt_info
));
6038 if (!STMT_SLP_TYPE (stmt_info
)
6039 && nunits
!= (unsigned int) vectorization_factor
6040 && dump_enabled_p ())
6041 /* For SLP VF is set according to unrolling factor, and not
6042 to vector size, hence for SLP this print is not valid. */
6043 dump_printf_loc (MSG_NOTE
, vect_location
, "multiple-types.\n");
6046 /* SLP. Schedule all the SLP instances when the first SLP stmt is
6048 if (STMT_SLP_TYPE (stmt_info
))
6052 slp_scheduled
= true;
6054 if (dump_enabled_p ())
6055 dump_printf_loc (MSG_NOTE
, vect_location
,
6056 "=== scheduling SLP instances ===\n");
6058 vect_schedule_slp (loop_vinfo
, NULL
);
6061 /* Hybrid SLP stmts must be vectorized in addition to SLP. */
6062 if (!vinfo_for_stmt (stmt
) || PURE_SLP_STMT (stmt_info
))
6064 if (!transform_pattern_stmt
&& gsi_end_p (pattern_def_si
))
6066 pattern_def_seq
= NULL
;
6073 /* -------- vectorize statement ------------ */
6074 if (dump_enabled_p ())
6075 dump_printf_loc (MSG_NOTE
, vect_location
, "transform statement.\n");
6077 grouped_store
= false;
6078 is_store
= vect_transform_stmt (stmt
, &si
, &grouped_store
, NULL
, NULL
);
6081 if (STMT_VINFO_GROUPED_ACCESS (stmt_info
))
6083 /* Interleaving. If IS_STORE is TRUE, the vectorization of the
6084 interleaving chain was completed - free all the stores in
6087 vect_remove_stores (GROUP_FIRST_ELEMENT (stmt_info
));
6091 /* Free the attached stmt_vec_info and remove the stmt. */
6092 gimple store
= gsi_stmt (si
);
6093 free_stmt_vec_info (store
);
6094 unlink_stmt_vdef (store
);
6095 gsi_remove (&si
, true);
6096 release_defs (store
);
6099 /* Stores can only appear at the end of pattern statements. */
6100 gcc_assert (!transform_pattern_stmt
);
6101 pattern_def_seq
= NULL
;
6103 else if (!transform_pattern_stmt
&& gsi_end_p (pattern_def_si
))
6105 pattern_def_seq
= NULL
;
6111 slpeel_make_loop_iterate_ntimes (loop
, ratio
);
6113 /* Reduce loop iterations by the vectorization factor. */
6114 scale_loop_profile (loop
, GCOV_COMPUTE_SCALE (1, vectorization_factor
),
6115 expected_iterations
/ vectorization_factor
);
6116 loop
->nb_iterations_upper_bound
6117 = loop
->nb_iterations_upper_bound
.udiv (double_int::from_uhwi (vectorization_factor
),
6119 if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo
)
6120 && loop
->nb_iterations_upper_bound
!= double_int_zero
)
6121 loop
->nb_iterations_upper_bound
= loop
->nb_iterations_upper_bound
- double_int_one
;
6122 if (loop
->any_estimate
)
6124 loop
->nb_iterations_estimate
6125 = loop
->nb_iterations_estimate
.udiv (double_int::from_uhwi (vectorization_factor
),
6127 if (LOOP_VINFO_PEELING_FOR_GAPS (loop_vinfo
)
6128 && loop
->nb_iterations_estimate
!= double_int_zero
)
6129 loop
->nb_iterations_estimate
= loop
->nb_iterations_estimate
- double_int_one
;
6132 if (dump_enabled_p ())
6134 dump_printf_loc (MSG_NOTE
, vect_location
,
6135 "LOOP VECTORIZED\n");
6137 dump_printf_loc (MSG_NOTE
, vect_location
,
6138 "OUTER LOOP VECTORIZED\n");
6139 dump_printf (MSG_NOTE
, "\n");