Daily bump.
[gcc.git] / gcc / tree-vectorizer.h
1 /* Vectorizer
2 Copyright (C) 2003-2021 Free Software Foundation, Inc.
3 Contributed by Dorit Naishlos <dorit@il.ibm.com>
4
5 This file is part of GCC.
6
7 GCC is free software; you can redistribute it and/or modify it under
8 the terms of the GNU General Public License as published by the Free
9 Software Foundation; either version 3, or (at your option) any later
10 version.
11
12 GCC is distributed in the hope that it will be useful, but WITHOUT ANY
13 WARRANTY; without even the implied warranty of MERCHANTABILITY or
14 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
15 for more details.
16
17 You should have received a copy of the GNU General Public License
18 along with GCC; see the file COPYING3. If not see
19 <http://www.gnu.org/licenses/>. */
20
21 #ifndef GCC_TREE_VECTORIZER_H
22 #define GCC_TREE_VECTORIZER_H
23
24 typedef class _stmt_vec_info *stmt_vec_info;
25
26 #include "tree-data-ref.h"
27 #include "tree-hash-traits.h"
28 #include "target.h"
29 #include "internal-fn.h"
30
31
32 /* Used for naming of new temporaries. */
33 enum vect_var_kind {
34 vect_simple_var,
35 vect_pointer_var,
36 vect_scalar_var,
37 vect_mask_var
38 };
39
40 /* Defines type of operation. */
41 enum operation_type {
42 unary_op = 1,
43 binary_op,
44 ternary_op
45 };
46
47 /* Define type of available alignment support. */
48 enum dr_alignment_support {
49 dr_unaligned_unsupported,
50 dr_unaligned_supported,
51 dr_explicit_realign,
52 dr_explicit_realign_optimized,
53 dr_aligned
54 };
55
56 /* Define type of def-use cross-iteration cycle. */
57 enum vect_def_type {
58 vect_uninitialized_def = 0,
59 vect_constant_def = 1,
60 vect_external_def,
61 vect_internal_def,
62 vect_induction_def,
63 vect_reduction_def,
64 vect_double_reduction_def,
65 vect_nested_cycle,
66 vect_unknown_def_type
67 };
68
69 /* Define type of reduction. */
70 enum vect_reduction_type {
71 TREE_CODE_REDUCTION,
72 COND_REDUCTION,
73 INTEGER_INDUC_COND_REDUCTION,
74 CONST_COND_REDUCTION,
75
76 /* Retain a scalar phi and use a FOLD_EXTRACT_LAST within the loop
77 to implement:
78
79 for (int i = 0; i < VF; ++i)
80 res = cond[i] ? val[i] : res; */
81 EXTRACT_LAST_REDUCTION,
82
83 /* Use a folding reduction within the loop to implement:
84
85 for (int i = 0; i < VF; ++i)
86 res = res OP val[i];
87
88 (with no reassocation). */
89 FOLD_LEFT_REDUCTION
90 };
91
92 #define VECTORIZABLE_CYCLE_DEF(D) (((D) == vect_reduction_def) \
93 || ((D) == vect_double_reduction_def) \
94 || ((D) == vect_nested_cycle))
95
96 /* Structure to encapsulate information about a group of like
97 instructions to be presented to the target cost model. */
98 struct stmt_info_for_cost {
99 int count;
100 enum vect_cost_for_stmt kind;
101 enum vect_cost_model_location where;
102 stmt_vec_info stmt_info;
103 tree vectype;
104 int misalign;
105 };
106
107 typedef vec<stmt_info_for_cost> stmt_vector_for_cost;
108
109 /* Maps base addresses to an innermost_loop_behavior that gives the maximum
110 known alignment for that base. */
111 typedef hash_map<tree_operand_hash,
112 innermost_loop_behavior *> vec_base_alignments;
113
114 /************************************************************************
115 SLP
116 ************************************************************************/
117 typedef struct _slp_tree *slp_tree;
118 typedef vec<std::pair<unsigned, unsigned> > lane_permutation_t;
119 typedef vec<unsigned> load_permutation_t;
120
121 /* A computation tree of an SLP instance. Each node corresponds to a group of
122 stmts to be packed in a SIMD stmt. */
123 struct _slp_tree {
124 _slp_tree ();
125 ~_slp_tree ();
126
127 /* Nodes that contain def-stmts of this node statements operands. */
128 vec<slp_tree> children;
129
130 /* A group of scalar stmts to be vectorized together. */
131 vec<stmt_vec_info> stmts;
132 /* A group of scalar operands to be vectorized together. */
133 vec<tree> ops;
134 /* The representative that should be used for analysis and
135 code generation. */
136 stmt_vec_info representative;
137
138 /* Load permutation relative to the stores, NULL if there is no
139 permutation. */
140 load_permutation_t load_permutation;
141 /* Lane permutation of the operands scalar lanes encoded as pairs
142 of { operand number, lane number }. The number of elements
143 denotes the number of output lanes. */
144 lane_permutation_t lane_permutation;
145
146 tree vectype;
147 /* Vectorized stmt/s. */
148 vec<gimple *> vec_stmts;
149 vec<tree> vec_defs;
150 /* Number of vector stmts that are created to replace the group of scalar
151 stmts. It is calculated during the transformation phase as the number of
152 scalar elements in one scalar iteration (GROUP_SIZE) multiplied by VF
153 divided by vector size. */
154 unsigned int vec_stmts_size;
155
156 /* Reference count in the SLP graph. */
157 unsigned int refcnt;
158 /* The maximum number of vector elements for the subtree rooted
159 at this node. */
160 poly_uint64 max_nunits;
161 /* The DEF type of this node. */
162 enum vect_def_type def_type;
163 /* The number of scalar lanes produced by this node. */
164 unsigned int lanes;
165 /* The operation of this node. */
166 enum tree_code code;
167
168 int vertex;
169
170 /* Allocate from slp_tree_pool. */
171 static void *operator new (size_t);
172
173 /* Return memory to slp_tree_pool. */
174 static void operator delete (void *, size_t);
175
176 /* Linked list of nodes to release when we free the slp_tree_pool. */
177 slp_tree next_node;
178 slp_tree prev_node;
179 };
180
181 /* The enum describes the type of operations that an SLP instance
182 can perform. */
183
184 enum slp_instance_kind {
185 slp_inst_kind_store,
186 slp_inst_kind_reduc_group,
187 slp_inst_kind_reduc_chain,
188 slp_inst_kind_ctor
189 };
190
191 /* SLP instance is a sequence of stmts in a loop that can be packed into
192 SIMD stmts. */
193 typedef class _slp_instance {
194 public:
195 /* The root of SLP tree. */
196 slp_tree root;
197
198 /* For vector constructors, the constructor stmt that the SLP tree is built
199 from, NULL otherwise. */
200 stmt_vec_info root_stmt;
201
202 /* The unrolling factor required to vectorized this SLP instance. */
203 poly_uint64 unrolling_factor;
204
205 /* The group of nodes that contain loads of this SLP instance. */
206 vec<slp_tree> loads;
207
208 /* The SLP node containing the reduction PHIs. */
209 slp_tree reduc_phis;
210
211 /* Vector cost of this entry to the SLP graph. */
212 stmt_vector_for_cost cost_vec;
213
214 /* If this instance is the main entry of a subgraph the set of
215 entries into the same subgraph, including itself. */
216 vec<_slp_instance *> subgraph_entries;
217
218 /* The type of operation the SLP instance is performing. */
219 slp_instance_kind kind;
220
221 dump_user_location_t location () const;
222 } *slp_instance;
223
224
225 /* Access Functions. */
226 #define SLP_INSTANCE_TREE(S) (S)->root
227 #define SLP_INSTANCE_UNROLLING_FACTOR(S) (S)->unrolling_factor
228 #define SLP_INSTANCE_LOADS(S) (S)->loads
229 #define SLP_INSTANCE_ROOT_STMT(S) (S)->root_stmt
230 #define SLP_INSTANCE_KIND(S) (S)->kind
231
232 #define SLP_TREE_CHILDREN(S) (S)->children
233 #define SLP_TREE_SCALAR_STMTS(S) (S)->stmts
234 #define SLP_TREE_SCALAR_OPS(S) (S)->ops
235 #define SLP_TREE_REF_COUNT(S) (S)->refcnt
236 #define SLP_TREE_VEC_STMTS(S) (S)->vec_stmts
237 #define SLP_TREE_VEC_DEFS(S) (S)->vec_defs
238 #define SLP_TREE_NUMBER_OF_VEC_STMTS(S) (S)->vec_stmts_size
239 #define SLP_TREE_LOAD_PERMUTATION(S) (S)->load_permutation
240 #define SLP_TREE_LANE_PERMUTATION(S) (S)->lane_permutation
241 #define SLP_TREE_DEF_TYPE(S) (S)->def_type
242 #define SLP_TREE_VECTYPE(S) (S)->vectype
243 #define SLP_TREE_REPRESENTATIVE(S) (S)->representative
244 #define SLP_TREE_LANES(S) (S)->lanes
245 #define SLP_TREE_CODE(S) (S)->code
246
247 /* Key for map that records association between
248 scalar conditions and corresponding loop mask, and
249 is populated by vect_record_loop_mask. */
250
251 struct scalar_cond_masked_key
252 {
253 scalar_cond_masked_key (tree t, unsigned ncopies_)
254 : ncopies (ncopies_)
255 {
256 get_cond_ops_from_tree (t);
257 }
258
259 void get_cond_ops_from_tree (tree);
260
261 unsigned ncopies;
262 tree_code code;
263 tree op0;
264 tree op1;
265 };
266
267 template<>
268 struct default_hash_traits<scalar_cond_masked_key>
269 {
270 typedef scalar_cond_masked_key compare_type;
271 typedef scalar_cond_masked_key value_type;
272
273 static inline hashval_t
274 hash (value_type v)
275 {
276 inchash::hash h;
277 h.add_int (v.code);
278 inchash::add_expr (v.op0, h, 0);
279 inchash::add_expr (v.op1, h, 0);
280 h.add_int (v.ncopies);
281 return h.end ();
282 }
283
284 static inline bool
285 equal (value_type existing, value_type candidate)
286 {
287 return (existing.ncopies == candidate.ncopies
288 && existing.code == candidate.code
289 && operand_equal_p (existing.op0, candidate.op0, 0)
290 && operand_equal_p (existing.op1, candidate.op1, 0));
291 }
292
293 static const bool empty_zero_p = true;
294
295 static inline void
296 mark_empty (value_type &v)
297 {
298 v.ncopies = 0;
299 }
300
301 static inline bool
302 is_empty (value_type v)
303 {
304 return v.ncopies == 0;
305 }
306
307 static inline void mark_deleted (value_type &) {}
308
309 static inline bool is_deleted (const value_type &)
310 {
311 return false;
312 }
313
314 static inline void remove (value_type &) {}
315 };
316
317 typedef hash_set<scalar_cond_masked_key> scalar_cond_masked_set_type;
318
319 /* Describes two objects whose addresses must be unequal for the vectorized
320 loop to be valid. */
321 typedef std::pair<tree, tree> vec_object_pair;
322
323 /* Records that vectorization is only possible if abs (EXPR) >= MIN_VALUE.
324 UNSIGNED_P is true if we can assume that abs (EXPR) == EXPR. */
325 class vec_lower_bound {
326 public:
327 vec_lower_bound () {}
328 vec_lower_bound (tree e, bool u, poly_uint64 m)
329 : expr (e), unsigned_p (u), min_value (m) {}
330
331 tree expr;
332 bool unsigned_p;
333 poly_uint64 min_value;
334 };
335
336 /* Vectorizer state shared between different analyses like vector sizes
337 of the same CFG region. */
338 class vec_info_shared {
339 public:
340 vec_info_shared();
341 ~vec_info_shared();
342
343 void save_datarefs();
344 void check_datarefs();
345
346 /* All data references. Freed by free_data_refs, so not an auto_vec. */
347 vec<data_reference_p> datarefs;
348 vec<data_reference> datarefs_copy;
349
350 /* The loop nest in which the data dependences are computed. */
351 auto_vec<loop_p> loop_nest;
352
353 /* All data dependences. Freed by free_dependence_relations, so not
354 an auto_vec. */
355 vec<ddr_p> ddrs;
356 };
357
358 /* Vectorizer state common between loop and basic-block vectorization. */
359 class vec_info {
360 public:
361 typedef hash_set<int_hash<machine_mode, E_VOIDmode, E_BLKmode> > mode_set;
362 enum vec_kind { bb, loop };
363
364 vec_info (vec_kind, void *, vec_info_shared *);
365 ~vec_info ();
366
367 stmt_vec_info add_stmt (gimple *);
368 stmt_vec_info add_pattern_stmt (gimple *, stmt_vec_info);
369 stmt_vec_info lookup_stmt (gimple *);
370 stmt_vec_info lookup_def (tree);
371 stmt_vec_info lookup_single_use (tree);
372 class dr_vec_info *lookup_dr (data_reference *);
373 void move_dr (stmt_vec_info, stmt_vec_info);
374 void remove_stmt (stmt_vec_info);
375 void replace_stmt (gimple_stmt_iterator *, stmt_vec_info, gimple *);
376 void insert_on_entry (stmt_vec_info, gimple *);
377 void insert_seq_on_entry (stmt_vec_info, gimple_seq);
378
379 /* The type of vectorization. */
380 vec_kind kind;
381
382 /* Shared vectorizer state. */
383 vec_info_shared *shared;
384
385 /* The mapping of GIMPLE UID to stmt_vec_info. */
386 vec<stmt_vec_info> stmt_vec_infos;
387 /* Whether the above mapping is complete. */
388 bool stmt_vec_info_ro;
389
390 /* The SLP graph. */
391 auto_vec<slp_instance> slp_instances;
392
393 /* Maps base addresses to an innermost_loop_behavior that gives the maximum
394 known alignment for that base. */
395 vec_base_alignments base_alignments;
396
397 /* All interleaving chains of stores, represented by the first
398 stmt in the chain. */
399 auto_vec<stmt_vec_info> grouped_stores;
400
401 /* Cost data used by the target cost model. */
402 void *target_cost_data;
403
404 /* The set of vector modes used in the vectorized region. */
405 mode_set used_vector_modes;
406
407 /* The argument we should pass to related_vector_mode when looking up
408 the vector mode for a scalar mode, or VOIDmode if we haven't yet
409 made any decisions about which vector modes to use. */
410 machine_mode vector_mode;
411
412 private:
413 stmt_vec_info new_stmt_vec_info (gimple *stmt);
414 void set_vinfo_for_stmt (gimple *, stmt_vec_info, bool = true);
415 void free_stmt_vec_infos ();
416 void free_stmt_vec_info (stmt_vec_info);
417 };
418
419 class _loop_vec_info;
420 class _bb_vec_info;
421
422 template<>
423 template<>
424 inline bool
425 is_a_helper <_loop_vec_info *>::test (vec_info *i)
426 {
427 return i->kind == vec_info::loop;
428 }
429
430 template<>
431 template<>
432 inline bool
433 is_a_helper <_bb_vec_info *>::test (vec_info *i)
434 {
435 return i->kind == vec_info::bb;
436 }
437
438 /* In general, we can divide the vector statements in a vectorized loop
439 into related groups ("rgroups") and say that for each rgroup there is
440 some nS such that the rgroup operates on nS values from one scalar
441 iteration followed by nS values from the next. That is, if VF is the
442 vectorization factor of the loop, the rgroup operates on a sequence:
443
444 (1,1) (1,2) ... (1,nS) (2,1) ... (2,nS) ... (VF,1) ... (VF,nS)
445
446 where (i,j) represents a scalar value with index j in a scalar
447 iteration with index i.
448
449 [ We use the term "rgroup" to emphasise that this grouping isn't
450 necessarily the same as the grouping of statements used elsewhere.
451 For example, if we implement a group of scalar loads using gather
452 loads, we'll use a separate gather load for each scalar load, and
453 thus each gather load will belong to its own rgroup. ]
454
455 In general this sequence will occupy nV vectors concatenated
456 together. If these vectors have nL lanes each, the total number
457 of scalar values N is given by:
458
459 N = nS * VF = nV * nL
460
461 None of nS, VF, nV and nL are required to be a power of 2. nS and nV
462 are compile-time constants but VF and nL can be variable (if the target
463 supports variable-length vectors).
464
465 In classical vectorization, each iteration of the vector loop would
466 handle exactly VF iterations of the original scalar loop. However,
467 in vector loops that are able to operate on partial vectors, a
468 particular iteration of the vector loop might handle fewer than VF
469 iterations of the scalar loop. The vector lanes that correspond to
470 iterations of the scalar loop are said to be "active" and the other
471 lanes are said to be "inactive".
472
473 In such vector loops, many rgroups need to be controlled to ensure
474 that they have no effect for the inactive lanes. Conceptually, each
475 such rgroup needs a sequence of booleans in the same order as above,
476 but with each (i,j) replaced by a boolean that indicates whether
477 iteration i is active. This sequence occupies nV vector controls
478 that again have nL lanes each. Thus the control sequence as a whole
479 consists of VF independent booleans that are each repeated nS times.
480
481 Taking mask-based approach as a partially-populated vectors example.
482 We make the simplifying assumption that if a sequence of nV masks is
483 suitable for one (nS,nL) pair, we can reuse it for (nS/2,nL/2) by
484 VIEW_CONVERTing it. This holds for all current targets that support
485 fully-masked loops. For example, suppose the scalar loop is:
486
487 float *f;
488 double *d;
489 for (int i = 0; i < n; ++i)
490 {
491 f[i * 2 + 0] += 1.0f;
492 f[i * 2 + 1] += 2.0f;
493 d[i] += 3.0;
494 }
495
496 and suppose that vectors have 256 bits. The vectorized f accesses
497 will belong to one rgroup and the vectorized d access to another:
498
499 f rgroup: nS = 2, nV = 1, nL = 8
500 d rgroup: nS = 1, nV = 1, nL = 4
501 VF = 4
502
503 [ In this simple example the rgroups do correspond to the normal
504 SLP grouping scheme. ]
505
506 If only the first three lanes are active, the masks we need are:
507
508 f rgroup: 1 1 | 1 1 | 1 1 | 0 0
509 d rgroup: 1 | 1 | 1 | 0
510
511 Here we can use a mask calculated for f's rgroup for d's, but not
512 vice versa.
513
514 Thus for each value of nV, it is enough to provide nV masks, with the
515 mask being calculated based on the highest nL (or, equivalently, based
516 on the highest nS) required by any rgroup with that nV. We therefore
517 represent the entire collection of masks as a two-level table, with the
518 first level being indexed by nV - 1 (since nV == 0 doesn't exist) and
519 the second being indexed by the mask index 0 <= i < nV. */
520
521 /* The controls (like masks or lengths) needed by rgroups with nV vectors,
522 according to the description above. */
523 struct rgroup_controls {
524 /* The largest nS for all rgroups that use these controls. */
525 unsigned int max_nscalars_per_iter;
526
527 /* For the largest nS recorded above, the loop controls divide each scalar
528 into FACTOR equal-sized pieces. This is useful if we need to split
529 element-based accesses into byte-based accesses. */
530 unsigned int factor;
531
532 /* This is a vector type with MAX_NSCALARS_PER_ITER * VF / nV elements.
533 For mask-based controls, it is the type of the masks in CONTROLS.
534 For length-based controls, it can be any vector type that has the
535 specified number of elements; the type of the elements doesn't matter. */
536 tree type;
537
538 /* A vector of nV controls, in iteration order. */
539 vec<tree> controls;
540 };
541
542 typedef auto_vec<rgroup_controls> vec_loop_masks;
543
544 typedef auto_vec<rgroup_controls> vec_loop_lens;
545
546 typedef auto_vec<std::pair<data_reference*, tree> > drs_init_vec;
547
548 /*-----------------------------------------------------------------*/
549 /* Info on vectorized loops. */
550 /*-----------------------------------------------------------------*/
551 typedef class _loop_vec_info : public vec_info {
552 public:
553 _loop_vec_info (class loop *, vec_info_shared *);
554 ~_loop_vec_info ();
555
556 /* The loop to which this info struct refers to. */
557 class loop *loop;
558
559 /* The loop basic blocks. */
560 basic_block *bbs;
561
562 /* Number of latch executions. */
563 tree num_itersm1;
564 /* Number of iterations. */
565 tree num_iters;
566 /* Number of iterations of the original loop. */
567 tree num_iters_unchanged;
568 /* Condition under which this loop is analyzed and versioned. */
569 tree num_iters_assumptions;
570
571 /* Threshold of number of iterations below which vectorization will not be
572 performed. It is calculated from MIN_PROFITABLE_ITERS and
573 param_min_vect_loop_bound. */
574 unsigned int th;
575
576 /* When applying loop versioning, the vector form should only be used
577 if the number of scalar iterations is >= this value, on top of all
578 the other requirements. Ignored when loop versioning is not being
579 used. */
580 poly_uint64 versioning_threshold;
581
582 /* Unrolling factor */
583 poly_uint64 vectorization_factor;
584
585 /* Maximum runtime vectorization factor, or MAX_VECTORIZATION_FACTOR
586 if there is no particular limit. */
587 unsigned HOST_WIDE_INT max_vectorization_factor;
588
589 /* The masks that a fully-masked loop should use to avoid operating
590 on inactive scalars. */
591 vec_loop_masks masks;
592
593 /* The lengths that a loop with length should use to avoid operating
594 on inactive scalars. */
595 vec_loop_lens lens;
596
597 /* Set of scalar conditions that have loop mask applied. */
598 scalar_cond_masked_set_type scalar_cond_masked_set;
599
600 /* If we are using a loop mask to align memory addresses, this variable
601 contains the number of vector elements that we should skip in the
602 first iteration of the vector loop (i.e. the number of leading
603 elements that should be false in the first mask). */
604 tree mask_skip_niters;
605
606 /* The type that the loop control IV should be converted to before
607 testing which of the VF scalars are active and inactive.
608 Only meaningful if LOOP_VINFO_USING_PARTIAL_VECTORS_P. */
609 tree rgroup_compare_type;
610
611 /* For #pragma omp simd if (x) loops the x expression. If constant 0,
612 the loop should not be vectorized, if constant non-zero, simd_if_cond
613 shouldn't be set and loop vectorized normally, if SSA_NAME, the loop
614 should be versioned on that condition, using scalar loop if the condition
615 is false and vectorized loop otherwise. */
616 tree simd_if_cond;
617
618 /* The type that the vector loop control IV should have when
619 LOOP_VINFO_USING_PARTIAL_VECTORS_P is true. */
620 tree rgroup_iv_type;
621
622 /* Unknown DRs according to which loop was peeled. */
623 class dr_vec_info *unaligned_dr;
624
625 /* peeling_for_alignment indicates whether peeling for alignment will take
626 place, and what the peeling factor should be:
627 peeling_for_alignment = X means:
628 If X=0: Peeling for alignment will not be applied.
629 If X>0: Peel first X iterations.
630 If X=-1: Generate a runtime test to calculate the number of iterations
631 to be peeled, using the dataref recorded in the field
632 unaligned_dr. */
633 int peeling_for_alignment;
634
635 /* The mask used to check the alignment of pointers or arrays. */
636 int ptr_mask;
637
638 /* Data Dependence Relations defining address ranges that are candidates
639 for a run-time aliasing check. */
640 auto_vec<ddr_p> may_alias_ddrs;
641
642 /* Data Dependence Relations defining address ranges together with segment
643 lengths from which the run-time aliasing check is built. */
644 auto_vec<dr_with_seg_len_pair_t> comp_alias_ddrs;
645
646 /* Check that the addresses of each pair of objects is unequal. */
647 auto_vec<vec_object_pair> check_unequal_addrs;
648
649 /* List of values that are required to be nonzero. This is used to check
650 whether things like "x[i * n] += 1;" are safe and eventually gets added
651 to the checks for lower bounds below. */
652 auto_vec<tree> check_nonzero;
653
654 /* List of values that need to be checked for a minimum value. */
655 auto_vec<vec_lower_bound> lower_bounds;
656
657 /* Statements in the loop that have data references that are candidates for a
658 runtime (loop versioning) misalignment check. */
659 auto_vec<stmt_vec_info> may_misalign_stmts;
660
661 /* Reduction cycles detected in the loop. Used in loop-aware SLP. */
662 auto_vec<stmt_vec_info> reductions;
663
664 /* All reduction chains in the loop, represented by the first
665 stmt in the chain. */
666 auto_vec<stmt_vec_info> reduction_chains;
667
668 /* Cost vector for a single scalar iteration. */
669 auto_vec<stmt_info_for_cost> scalar_cost_vec;
670
671 /* Map of IV base/step expressions to inserted name in the preheader. */
672 hash_map<tree_operand_hash, tree> *ivexpr_map;
673
674 /* Map of OpenMP "omp simd array" scan variables to corresponding
675 rhs of the store of the initializer. */
676 hash_map<tree, tree> *scan_map;
677
678 /* The unrolling factor needed to SLP the loop. In case of that pure SLP is
679 applied to the loop, i.e., no unrolling is needed, this is 1. */
680 poly_uint64 slp_unrolling_factor;
681
682 /* Cost of a single scalar iteration. */
683 int single_scalar_iteration_cost;
684
685 /* The cost of the vector prologue and epilogue, including peeled
686 iterations and set-up code. */
687 int vec_outside_cost;
688
689 /* The cost of the vector loop body. */
690 int vec_inside_cost;
691
692 /* Is the loop vectorizable? */
693 bool vectorizable;
694
695 /* Records whether we still have the option of vectorizing this loop
696 using partially-populated vectors; in other words, whether it is
697 still possible for one iteration of the vector loop to handle
698 fewer than VF scalars. */
699 bool can_use_partial_vectors_p;
700
701 /* True if we've decided to use partially-populated vectors, so that
702 the vector loop can handle fewer than VF scalars. */
703 bool using_partial_vectors_p;
704
705 /* True if we've decided to use partially-populated vectors for the
706 epilogue of loop. */
707 bool epil_using_partial_vectors_p;
708
709 /* When we have grouped data accesses with gaps, we may introduce invalid
710 memory accesses. We peel the last iteration of the loop to prevent
711 this. */
712 bool peeling_for_gaps;
713
714 /* When the number of iterations is not a multiple of the vector size
715 we need to peel off iterations at the end to form an epilogue loop. */
716 bool peeling_for_niter;
717
718 /* True if there are no loop carried data dependencies in the loop.
719 If loop->safelen <= 1, then this is always true, either the loop
720 didn't have any loop carried data dependencies, or the loop is being
721 vectorized guarded with some runtime alias checks, or couldn't
722 be vectorized at all, but then this field shouldn't be used.
723 For loop->safelen >= 2, the user has asserted that there are no
724 backward dependencies, but there still could be loop carried forward
725 dependencies in such loops. This flag will be false if normal
726 vectorizer data dependency analysis would fail or require versioning
727 for alias, but because of loop->safelen >= 2 it has been vectorized
728 even without versioning for alias. E.g. in:
729 #pragma omp simd
730 for (int i = 0; i < m; i++)
731 a[i] = a[i + k] * c;
732 (or #pragma simd or #pragma ivdep) we can vectorize this and it will
733 DTRT even for k > 0 && k < m, but without safelen we would not
734 vectorize this, so this field would be false. */
735 bool no_data_dependencies;
736
737 /* Mark loops having masked stores. */
738 bool has_mask_store;
739
740 /* Queued scaling factor for the scalar loop. */
741 profile_probability scalar_loop_scaling;
742
743 /* If if-conversion versioned this loop before conversion, this is the
744 loop version without if-conversion. */
745 class loop *scalar_loop;
746
747 /* For loops being epilogues of already vectorized loops
748 this points to the original vectorized loop. Otherwise NULL. */
749 _loop_vec_info *orig_loop_info;
750
751 /* Used to store loop_vec_infos of epilogues of this loop during
752 analysis. */
753 vec<_loop_vec_info *> epilogue_vinfos;
754
755 } *loop_vec_info;
756
757 /* Access Functions. */
758 #define LOOP_VINFO_LOOP(L) (L)->loop
759 #define LOOP_VINFO_BBS(L) (L)->bbs
760 #define LOOP_VINFO_NITERSM1(L) (L)->num_itersm1
761 #define LOOP_VINFO_NITERS(L) (L)->num_iters
762 /* Since LOOP_VINFO_NITERS and LOOP_VINFO_NITERSM1 can change after
763 prologue peeling retain total unchanged scalar loop iterations for
764 cost model. */
765 #define LOOP_VINFO_NITERS_UNCHANGED(L) (L)->num_iters_unchanged
766 #define LOOP_VINFO_NITERS_ASSUMPTIONS(L) (L)->num_iters_assumptions
767 #define LOOP_VINFO_COST_MODEL_THRESHOLD(L) (L)->th
768 #define LOOP_VINFO_VERSIONING_THRESHOLD(L) (L)->versioning_threshold
769 #define LOOP_VINFO_VECTORIZABLE_P(L) (L)->vectorizable
770 #define LOOP_VINFO_CAN_USE_PARTIAL_VECTORS_P(L) (L)->can_use_partial_vectors_p
771 #define LOOP_VINFO_USING_PARTIAL_VECTORS_P(L) (L)->using_partial_vectors_p
772 #define LOOP_VINFO_EPIL_USING_PARTIAL_VECTORS_P(L) \
773 (L)->epil_using_partial_vectors_p
774 #define LOOP_VINFO_VECT_FACTOR(L) (L)->vectorization_factor
775 #define LOOP_VINFO_MAX_VECT_FACTOR(L) (L)->max_vectorization_factor
776 #define LOOP_VINFO_MASKS(L) (L)->masks
777 #define LOOP_VINFO_LENS(L) (L)->lens
778 #define LOOP_VINFO_MASK_SKIP_NITERS(L) (L)->mask_skip_niters
779 #define LOOP_VINFO_RGROUP_COMPARE_TYPE(L) (L)->rgroup_compare_type
780 #define LOOP_VINFO_RGROUP_IV_TYPE(L) (L)->rgroup_iv_type
781 #define LOOP_VINFO_PTR_MASK(L) (L)->ptr_mask
782 #define LOOP_VINFO_LOOP_NEST(L) (L)->shared->loop_nest
783 #define LOOP_VINFO_DATAREFS(L) (L)->shared->datarefs
784 #define LOOP_VINFO_DDRS(L) (L)->shared->ddrs
785 #define LOOP_VINFO_INT_NITERS(L) (TREE_INT_CST_LOW ((L)->num_iters))
786 #define LOOP_VINFO_PEELING_FOR_ALIGNMENT(L) (L)->peeling_for_alignment
787 #define LOOP_VINFO_UNALIGNED_DR(L) (L)->unaligned_dr
788 #define LOOP_VINFO_MAY_MISALIGN_STMTS(L) (L)->may_misalign_stmts
789 #define LOOP_VINFO_MAY_ALIAS_DDRS(L) (L)->may_alias_ddrs
790 #define LOOP_VINFO_COMP_ALIAS_DDRS(L) (L)->comp_alias_ddrs
791 #define LOOP_VINFO_CHECK_UNEQUAL_ADDRS(L) (L)->check_unequal_addrs
792 #define LOOP_VINFO_CHECK_NONZERO(L) (L)->check_nonzero
793 #define LOOP_VINFO_LOWER_BOUNDS(L) (L)->lower_bounds
794 #define LOOP_VINFO_GROUPED_STORES(L) (L)->grouped_stores
795 #define LOOP_VINFO_SLP_INSTANCES(L) (L)->slp_instances
796 #define LOOP_VINFO_SLP_UNROLLING_FACTOR(L) (L)->slp_unrolling_factor
797 #define LOOP_VINFO_REDUCTIONS(L) (L)->reductions
798 #define LOOP_VINFO_REDUCTION_CHAINS(L) (L)->reduction_chains
799 #define LOOP_VINFO_TARGET_COST_DATA(L) (L)->target_cost_data
800 #define LOOP_VINFO_PEELING_FOR_GAPS(L) (L)->peeling_for_gaps
801 #define LOOP_VINFO_PEELING_FOR_NITER(L) (L)->peeling_for_niter
802 #define LOOP_VINFO_NO_DATA_DEPENDENCIES(L) (L)->no_data_dependencies
803 #define LOOP_VINFO_SCALAR_LOOP(L) (L)->scalar_loop
804 #define LOOP_VINFO_SCALAR_LOOP_SCALING(L) (L)->scalar_loop_scaling
805 #define LOOP_VINFO_HAS_MASK_STORE(L) (L)->has_mask_store
806 #define LOOP_VINFO_SCALAR_ITERATION_COST(L) (L)->scalar_cost_vec
807 #define LOOP_VINFO_SINGLE_SCALAR_ITERATION_COST(L) (L)->single_scalar_iteration_cost
808 #define LOOP_VINFO_ORIG_LOOP_INFO(L) (L)->orig_loop_info
809 #define LOOP_VINFO_SIMD_IF_COND(L) (L)->simd_if_cond
810
811 #define LOOP_VINFO_FULLY_MASKED_P(L) \
812 (LOOP_VINFO_USING_PARTIAL_VECTORS_P (L) \
813 && !LOOP_VINFO_MASKS (L).is_empty ())
814
815 #define LOOP_VINFO_FULLY_WITH_LENGTH_P(L) \
816 (LOOP_VINFO_USING_PARTIAL_VECTORS_P (L) \
817 && !LOOP_VINFO_LENS (L).is_empty ())
818
819 #define LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT(L) \
820 ((L)->may_misalign_stmts.length () > 0)
821 #define LOOP_REQUIRES_VERSIONING_FOR_ALIAS(L) \
822 ((L)->comp_alias_ddrs.length () > 0 \
823 || (L)->check_unequal_addrs.length () > 0 \
824 || (L)->lower_bounds.length () > 0)
825 #define LOOP_REQUIRES_VERSIONING_FOR_NITERS(L) \
826 (LOOP_VINFO_NITERS_ASSUMPTIONS (L))
827 #define LOOP_REQUIRES_VERSIONING_FOR_SIMD_IF_COND(L) \
828 (LOOP_VINFO_SIMD_IF_COND (L))
829 #define LOOP_REQUIRES_VERSIONING(L) \
830 (LOOP_REQUIRES_VERSIONING_FOR_ALIGNMENT (L) \
831 || LOOP_REQUIRES_VERSIONING_FOR_ALIAS (L) \
832 || LOOP_REQUIRES_VERSIONING_FOR_NITERS (L) \
833 || LOOP_REQUIRES_VERSIONING_FOR_SIMD_IF_COND (L))
834
835 #define LOOP_VINFO_NITERS_KNOWN_P(L) \
836 (tree_fits_shwi_p ((L)->num_iters) && tree_to_shwi ((L)->num_iters) > 0)
837
838 #define LOOP_VINFO_EPILOGUE_P(L) \
839 (LOOP_VINFO_ORIG_LOOP_INFO (L) != NULL)
840
841 #define LOOP_VINFO_ORIG_MAX_VECT_FACTOR(L) \
842 (LOOP_VINFO_MAX_VECT_FACTOR (LOOP_VINFO_ORIG_LOOP_INFO (L)))
843
844 /* Wrapper for loop_vec_info, for tracking success/failure, where a non-NULL
845 value signifies success, and a NULL value signifies failure, supporting
846 propagating an opt_problem * describing the failure back up the call
847 stack. */
848 typedef opt_pointer_wrapper <loop_vec_info> opt_loop_vec_info;
849
850 static inline loop_vec_info
851 loop_vec_info_for_loop (class loop *loop)
852 {
853 return (loop_vec_info) loop->aux;
854 }
855
856 struct slp_root
857 {
858 slp_root (slp_instance_kind kind_, vec<stmt_vec_info> stmts_,
859 stmt_vec_info root_)
860 : kind(kind_), stmts(stmts_), root(root_) {}
861 slp_instance_kind kind;
862 vec<stmt_vec_info> stmts;
863 stmt_vec_info root;
864 };
865
866 typedef class _bb_vec_info : public vec_info
867 {
868 public:
869 _bb_vec_info (vec<basic_block> bbs, vec_info_shared *);
870 ~_bb_vec_info ();
871
872 /* The region we are operating on. bbs[0] is the entry, excluding
873 its PHI nodes. In the future we might want to track an explicit
874 entry edge to cover bbs[0] PHI nodes and have a region entry
875 insert location. */
876 vec<basic_block> bbs;
877
878 vec<slp_root> roots;
879 } *bb_vec_info;
880
881 #define BB_VINFO_BB(B) (B)->bb
882 #define BB_VINFO_GROUPED_STORES(B) (B)->grouped_stores
883 #define BB_VINFO_SLP_INSTANCES(B) (B)->slp_instances
884 #define BB_VINFO_DATAREFS(B) (B)->shared->datarefs
885 #define BB_VINFO_DDRS(B) (B)->shared->ddrs
886
887 static inline bb_vec_info
888 vec_info_for_bb (basic_block bb)
889 {
890 return (bb_vec_info) bb->aux;
891 }
892
893 /*-----------------------------------------------------------------*/
894 /* Info on vectorized defs. */
895 /*-----------------------------------------------------------------*/
896 enum stmt_vec_info_type {
897 undef_vec_info_type = 0,
898 load_vec_info_type,
899 store_vec_info_type,
900 shift_vec_info_type,
901 op_vec_info_type,
902 call_vec_info_type,
903 call_simd_clone_vec_info_type,
904 assignment_vec_info_type,
905 condition_vec_info_type,
906 comparison_vec_info_type,
907 reduc_vec_info_type,
908 induc_vec_info_type,
909 type_promotion_vec_info_type,
910 type_demotion_vec_info_type,
911 type_conversion_vec_info_type,
912 cycle_phi_info_type,
913 lc_phi_info_type,
914 phi_info_type,
915 loop_exit_ctrl_vec_info_type
916 };
917
918 /* Indicates whether/how a variable is used in the scope of loop/basic
919 block. */
920 enum vect_relevant {
921 vect_unused_in_scope = 0,
922
923 /* The def is only used outside the loop. */
924 vect_used_only_live,
925 /* The def is in the inner loop, and the use is in the outer loop, and the
926 use is a reduction stmt. */
927 vect_used_in_outer_by_reduction,
928 /* The def is in the inner loop, and the use is in the outer loop (and is
929 not part of reduction). */
930 vect_used_in_outer,
931
932 /* defs that feed computations that end up (only) in a reduction. These
933 defs may be used by non-reduction stmts, but eventually, any
934 computations/values that are affected by these defs are used to compute
935 a reduction (i.e. don't get stored to memory, for example). We use this
936 to identify computations that we can change the order in which they are
937 computed. */
938 vect_used_by_reduction,
939
940 vect_used_in_scope
941 };
942
943 /* The type of vectorization that can be applied to the stmt: regular loop-based
944 vectorization; pure SLP - the stmt is a part of SLP instances and does not
945 have uses outside SLP instances; or hybrid SLP and loop-based - the stmt is
946 a part of SLP instance and also must be loop-based vectorized, since it has
947 uses outside SLP sequences.
948
949 In the loop context the meanings of pure and hybrid SLP are slightly
950 different. By saying that pure SLP is applied to the loop, we mean that we
951 exploit only intra-iteration parallelism in the loop; i.e., the loop can be
952 vectorized without doing any conceptual unrolling, cause we don't pack
953 together stmts from different iterations, only within a single iteration.
954 Loop hybrid SLP means that we exploit both intra-iteration and
955 inter-iteration parallelism (e.g., number of elements in the vector is 4
956 and the slp-group-size is 2, in which case we don't have enough parallelism
957 within an iteration, so we obtain the rest of the parallelism from subsequent
958 iterations by unrolling the loop by 2). */
959 enum slp_vect_type {
960 loop_vect = 0,
961 pure_slp,
962 hybrid
963 };
964
965 /* Says whether a statement is a load, a store of a vectorized statement
966 result, or a store of an invariant value. */
967 enum vec_load_store_type {
968 VLS_LOAD,
969 VLS_STORE,
970 VLS_STORE_INVARIANT
971 };
972
973 /* Describes how we're going to vectorize an individual load or store,
974 or a group of loads or stores. */
975 enum vect_memory_access_type {
976 /* An access to an invariant address. This is used only for loads. */
977 VMAT_INVARIANT,
978
979 /* A simple contiguous access. */
980 VMAT_CONTIGUOUS,
981
982 /* A contiguous access that goes down in memory rather than up,
983 with no additional permutation. This is used only for stores
984 of invariants. */
985 VMAT_CONTIGUOUS_DOWN,
986
987 /* A simple contiguous access in which the elements need to be permuted
988 after loading or before storing. Only used for loop vectorization;
989 SLP uses separate permutes. */
990 VMAT_CONTIGUOUS_PERMUTE,
991
992 /* A simple contiguous access in which the elements need to be reversed
993 after loading or before storing. */
994 VMAT_CONTIGUOUS_REVERSE,
995
996 /* An access that uses IFN_LOAD_LANES or IFN_STORE_LANES. */
997 VMAT_LOAD_STORE_LANES,
998
999 /* An access in which each scalar element is loaded or stored
1000 individually. */
1001 VMAT_ELEMENTWISE,
1002
1003 /* A hybrid of VMAT_CONTIGUOUS and VMAT_ELEMENTWISE, used for grouped
1004 SLP accesses. Each unrolled iteration uses a contiguous load
1005 or store for the whole group, but the groups from separate iterations
1006 are combined in the same way as for VMAT_ELEMENTWISE. */
1007 VMAT_STRIDED_SLP,
1008
1009 /* The access uses gather loads or scatter stores. */
1010 VMAT_GATHER_SCATTER
1011 };
1012
1013 class dr_vec_info {
1014 public:
1015 /* The data reference itself. */
1016 data_reference *dr;
1017 /* The statement that contains the data reference. */
1018 stmt_vec_info stmt;
1019 /* The misalignment in bytes of the reference, or -1 if not known. */
1020 int misalignment;
1021 /* The byte alignment that we'd ideally like the reference to have,
1022 and the value that misalignment is measured against. */
1023 poly_uint64 target_alignment;
1024 /* If true the alignment of base_decl needs to be increased. */
1025 bool base_misaligned;
1026 tree base_decl;
1027
1028 /* Stores current vectorized loop's offset. To be added to the DR's
1029 offset to calculate current offset of data reference. */
1030 tree offset;
1031 };
1032
1033 typedef struct data_reference *dr_p;
1034
1035 class _stmt_vec_info {
1036 public:
1037
1038 enum stmt_vec_info_type type;
1039
1040 /* Indicates whether this stmts is part of a computation whose result is
1041 used outside the loop. */
1042 bool live;
1043
1044 /* Stmt is part of some pattern (computation idiom) */
1045 bool in_pattern_p;
1046
1047 /* True if the statement was created during pattern recognition as
1048 part of the replacement for RELATED_STMT. This implies that the
1049 statement isn't part of any basic block, although for convenience
1050 its gimple_bb is the same as for RELATED_STMT. */
1051 bool pattern_stmt_p;
1052
1053 /* Is this statement vectorizable or should it be skipped in (partial)
1054 vectorization. */
1055 bool vectorizable;
1056
1057 /* The stmt to which this info struct refers to. */
1058 gimple *stmt;
1059
1060 /* The vector type to be used for the LHS of this statement. */
1061 tree vectype;
1062
1063 /* The vectorized stmts. */
1064 vec<gimple *> vec_stmts;
1065
1066 /* The following is relevant only for stmts that contain a non-scalar
1067 data-ref (array/pointer/struct access). A GIMPLE stmt is expected to have
1068 at most one such data-ref. */
1069
1070 dr_vec_info dr_aux;
1071
1072 /* Information about the data-ref relative to this loop
1073 nest (the loop that is being considered for vectorization). */
1074 innermost_loop_behavior dr_wrt_vec_loop;
1075
1076 /* For loop PHI nodes, the base and evolution part of it. This makes sure
1077 this information is still available in vect_update_ivs_after_vectorizer
1078 where we may not be able to re-analyze the PHI nodes evolution as
1079 peeling for the prologue loop can make it unanalyzable. The evolution
1080 part is still correct after peeling, but the base may have changed from
1081 the version here. */
1082 tree loop_phi_evolution_base_unchanged;
1083 tree loop_phi_evolution_part;
1084
1085 /* Used for various bookkeeping purposes, generally holding a pointer to
1086 some other stmt S that is in some way "related" to this stmt.
1087 Current use of this field is:
1088 If this stmt is part of a pattern (i.e. the field 'in_pattern_p' is
1089 true): S is the "pattern stmt" that represents (and replaces) the
1090 sequence of stmts that constitutes the pattern. Similarly, the
1091 related_stmt of the "pattern stmt" points back to this stmt (which is
1092 the last stmt in the original sequence of stmts that constitutes the
1093 pattern). */
1094 stmt_vec_info related_stmt;
1095
1096 /* Used to keep a sequence of def stmts of a pattern stmt if such exists.
1097 The sequence is attached to the original statement rather than the
1098 pattern statement. */
1099 gimple_seq pattern_def_seq;
1100
1101 /* Selected SIMD clone's function info. First vector element
1102 is SIMD clone's function decl, followed by a pair of trees (base + step)
1103 for linear arguments (pair of NULLs for other arguments). */
1104 vec<tree> simd_clone_info;
1105
1106 /* Classify the def of this stmt. */
1107 enum vect_def_type def_type;
1108
1109 /* Whether the stmt is SLPed, loop-based vectorized, or both. */
1110 enum slp_vect_type slp_type;
1111
1112 /* Interleaving and reduction chains info. */
1113 /* First element in the group. */
1114 stmt_vec_info first_element;
1115 /* Pointer to the next element in the group. */
1116 stmt_vec_info next_element;
1117 /* The size of the group. */
1118 unsigned int size;
1119 /* For stores, number of stores from this group seen. We vectorize the last
1120 one. */
1121 unsigned int store_count;
1122 /* For loads only, the gap from the previous load. For consecutive loads, GAP
1123 is 1. */
1124 unsigned int gap;
1125
1126 /* The minimum negative dependence distance this stmt participates in
1127 or zero if none. */
1128 unsigned int min_neg_dist;
1129
1130 /* Not all stmts in the loop need to be vectorized. e.g, the increment
1131 of the loop induction variable and computation of array indexes. relevant
1132 indicates whether the stmt needs to be vectorized. */
1133 enum vect_relevant relevant;
1134
1135 /* For loads if this is a gather, for stores if this is a scatter. */
1136 bool gather_scatter_p;
1137
1138 /* True if this is an access with loop-invariant stride. */
1139 bool strided_p;
1140
1141 /* For both loads and stores. */
1142 unsigned simd_lane_access_p : 3;
1143
1144 /* Classifies how the load or store is going to be implemented
1145 for loop vectorization. */
1146 vect_memory_access_type memory_access_type;
1147
1148 /* For INTEGER_INDUC_COND_REDUCTION, the initial value to be used. */
1149 tree induc_cond_initial_val;
1150
1151 /* If not NULL the value to be added to compute final reduction value. */
1152 tree reduc_epilogue_adjustment;
1153
1154 /* On a reduction PHI the reduction type as detected by
1155 vect_is_simple_reduction and vectorizable_reduction. */
1156 enum vect_reduction_type reduc_type;
1157
1158 /* The original reduction code, to be used in the epilogue. */
1159 enum tree_code reduc_code;
1160 /* An internal function we should use in the epilogue. */
1161 internal_fn reduc_fn;
1162
1163 /* On a stmt participating in the reduction the index of the operand
1164 on the reduction SSA cycle. */
1165 int reduc_idx;
1166
1167 /* On a reduction PHI the def returned by vect_force_simple_reduction.
1168 On the def returned by vect_force_simple_reduction the
1169 corresponding PHI. */
1170 stmt_vec_info reduc_def;
1171
1172 /* The vector input type relevant for reduction vectorization. */
1173 tree reduc_vectype_in;
1174
1175 /* The vector type for performing the actual reduction. */
1176 tree reduc_vectype;
1177
1178 /* Whether we force a single cycle PHI during reduction vectorization. */
1179 bool force_single_cycle;
1180
1181 /* Whether on this stmt reduction meta is recorded. */
1182 bool is_reduc_info;
1183
1184 /* If nonzero, the lhs of the statement could be truncated to this
1185 many bits without affecting any users of the result. */
1186 unsigned int min_output_precision;
1187
1188 /* If nonzero, all non-boolean input operands have the same precision,
1189 and they could each be truncated to this many bits without changing
1190 the result. */
1191 unsigned int min_input_precision;
1192
1193 /* If OPERATION_BITS is nonzero, the statement could be performed on
1194 an integer with the sign and number of bits given by OPERATION_SIGN
1195 and OPERATION_BITS without changing the result. */
1196 unsigned int operation_precision;
1197 signop operation_sign;
1198
1199 /* If the statement produces a boolean result, this value describes
1200 how we should choose the associated vector type. The possible
1201 values are:
1202
1203 - an integer precision N if we should use the vector mask type
1204 associated with N-bit integers. This is only used if all relevant
1205 input booleans also want the vector mask type for N-bit integers,
1206 or if we can convert them into that form by pattern-matching.
1207
1208 - ~0U if we considered choosing a vector mask type but decided
1209 to treat the boolean as a normal integer type instead.
1210
1211 - 0 otherwise. This means either that the operation isn't one that
1212 could have a vector mask type (and so should have a normal vector
1213 type instead) or that we simply haven't made a choice either way. */
1214 unsigned int mask_precision;
1215
1216 /* True if this is only suitable for SLP vectorization. */
1217 bool slp_vect_only_p;
1218 };
1219
1220 /* Information about a gather/scatter call. */
1221 struct gather_scatter_info {
1222 /* The internal function to use for the gather/scatter operation,
1223 or IFN_LAST if a built-in function should be used instead. */
1224 internal_fn ifn;
1225
1226 /* The FUNCTION_DECL for the built-in gather/scatter function,
1227 or null if an internal function should be used instead. */
1228 tree decl;
1229
1230 /* The loop-invariant base value. */
1231 tree base;
1232
1233 /* The original scalar offset, which is a non-loop-invariant SSA_NAME. */
1234 tree offset;
1235
1236 /* Each offset element should be multiplied by this amount before
1237 being added to the base. */
1238 int scale;
1239
1240 /* The definition type for the vectorized offset. */
1241 enum vect_def_type offset_dt;
1242
1243 /* The type of the vectorized offset. */
1244 tree offset_vectype;
1245
1246 /* The type of the scalar elements after loading or before storing. */
1247 tree element_type;
1248
1249 /* The type of the scalar elements being loaded or stored. */
1250 tree memory_type;
1251 };
1252
1253 /* Access Functions. */
1254 #define STMT_VINFO_TYPE(S) (S)->type
1255 #define STMT_VINFO_STMT(S) (S)->stmt
1256 #define STMT_VINFO_RELEVANT(S) (S)->relevant
1257 #define STMT_VINFO_LIVE_P(S) (S)->live
1258 #define STMT_VINFO_VECTYPE(S) (S)->vectype
1259 #define STMT_VINFO_VEC_STMTS(S) (S)->vec_stmts
1260 #define STMT_VINFO_VECTORIZABLE(S) (S)->vectorizable
1261 #define STMT_VINFO_DATA_REF(S) ((S)->dr_aux.dr + 0)
1262 #define STMT_VINFO_GATHER_SCATTER_P(S) (S)->gather_scatter_p
1263 #define STMT_VINFO_STRIDED_P(S) (S)->strided_p
1264 #define STMT_VINFO_MEMORY_ACCESS_TYPE(S) (S)->memory_access_type
1265 #define STMT_VINFO_SIMD_LANE_ACCESS_P(S) (S)->simd_lane_access_p
1266 #define STMT_VINFO_VEC_INDUC_COND_INITIAL_VAL(S) (S)->induc_cond_initial_val
1267 #define STMT_VINFO_REDUC_EPILOGUE_ADJUSTMENT(S) (S)->reduc_epilogue_adjustment
1268 #define STMT_VINFO_REDUC_IDX(S) (S)->reduc_idx
1269 #define STMT_VINFO_FORCE_SINGLE_CYCLE(S) (S)->force_single_cycle
1270
1271 #define STMT_VINFO_DR_WRT_VEC_LOOP(S) (S)->dr_wrt_vec_loop
1272 #define STMT_VINFO_DR_BASE_ADDRESS(S) (S)->dr_wrt_vec_loop.base_address
1273 #define STMT_VINFO_DR_INIT(S) (S)->dr_wrt_vec_loop.init
1274 #define STMT_VINFO_DR_OFFSET(S) (S)->dr_wrt_vec_loop.offset
1275 #define STMT_VINFO_DR_STEP(S) (S)->dr_wrt_vec_loop.step
1276 #define STMT_VINFO_DR_BASE_ALIGNMENT(S) (S)->dr_wrt_vec_loop.base_alignment
1277 #define STMT_VINFO_DR_BASE_MISALIGNMENT(S) \
1278 (S)->dr_wrt_vec_loop.base_misalignment
1279 #define STMT_VINFO_DR_OFFSET_ALIGNMENT(S) \
1280 (S)->dr_wrt_vec_loop.offset_alignment
1281 #define STMT_VINFO_DR_STEP_ALIGNMENT(S) \
1282 (S)->dr_wrt_vec_loop.step_alignment
1283
1284 #define STMT_VINFO_DR_INFO(S) \
1285 (gcc_checking_assert ((S)->dr_aux.stmt == (S)), &(S)->dr_aux)
1286
1287 #define STMT_VINFO_IN_PATTERN_P(S) (S)->in_pattern_p
1288 #define STMT_VINFO_RELATED_STMT(S) (S)->related_stmt
1289 #define STMT_VINFO_PATTERN_DEF_SEQ(S) (S)->pattern_def_seq
1290 #define STMT_VINFO_SIMD_CLONE_INFO(S) (S)->simd_clone_info
1291 #define STMT_VINFO_DEF_TYPE(S) (S)->def_type
1292 #define STMT_VINFO_GROUPED_ACCESS(S) \
1293 ((S)->dr_aux.dr && DR_GROUP_FIRST_ELEMENT(S))
1294 #define STMT_VINFO_LOOP_PHI_EVOLUTION_BASE_UNCHANGED(S) (S)->loop_phi_evolution_base_unchanged
1295 #define STMT_VINFO_LOOP_PHI_EVOLUTION_PART(S) (S)->loop_phi_evolution_part
1296 #define STMT_VINFO_MIN_NEG_DIST(S) (S)->min_neg_dist
1297 #define STMT_VINFO_REDUC_TYPE(S) (S)->reduc_type
1298 #define STMT_VINFO_REDUC_CODE(S) (S)->reduc_code
1299 #define STMT_VINFO_REDUC_FN(S) (S)->reduc_fn
1300 #define STMT_VINFO_REDUC_DEF(S) (S)->reduc_def
1301 #define STMT_VINFO_REDUC_VECTYPE(S) (S)->reduc_vectype
1302 #define STMT_VINFO_REDUC_VECTYPE_IN(S) (S)->reduc_vectype_in
1303 #define STMT_VINFO_SLP_VECT_ONLY(S) (S)->slp_vect_only_p
1304
1305 #define DR_GROUP_FIRST_ELEMENT(S) \
1306 (gcc_checking_assert ((S)->dr_aux.dr), (S)->first_element)
1307 #define DR_GROUP_NEXT_ELEMENT(S) \
1308 (gcc_checking_assert ((S)->dr_aux.dr), (S)->next_element)
1309 #define DR_GROUP_SIZE(S) \
1310 (gcc_checking_assert ((S)->dr_aux.dr), (S)->size)
1311 #define DR_GROUP_STORE_COUNT(S) \
1312 (gcc_checking_assert ((S)->dr_aux.dr), (S)->store_count)
1313 #define DR_GROUP_GAP(S) \
1314 (gcc_checking_assert ((S)->dr_aux.dr), (S)->gap)
1315
1316 #define REDUC_GROUP_FIRST_ELEMENT(S) \
1317 (gcc_checking_assert (!(S)->dr_aux.dr), (S)->first_element)
1318 #define REDUC_GROUP_NEXT_ELEMENT(S) \
1319 (gcc_checking_assert (!(S)->dr_aux.dr), (S)->next_element)
1320 #define REDUC_GROUP_SIZE(S) \
1321 (gcc_checking_assert (!(S)->dr_aux.dr), (S)->size)
1322
1323 #define STMT_VINFO_RELEVANT_P(S) ((S)->relevant != vect_unused_in_scope)
1324
1325 #define HYBRID_SLP_STMT(S) ((S)->slp_type == hybrid)
1326 #define PURE_SLP_STMT(S) ((S)->slp_type == pure_slp)
1327 #define STMT_SLP_TYPE(S) (S)->slp_type
1328
1329 #define VECT_MAX_COST 1000
1330
1331 /* The maximum number of intermediate steps required in multi-step type
1332 conversion. */
1333 #define MAX_INTERM_CVT_STEPS 3
1334
1335 #define MAX_VECTORIZATION_FACTOR INT_MAX
1336
1337 /* Nonzero if TYPE represents a (scalar) boolean type or type
1338 in the middle-end compatible with it (unsigned precision 1 integral
1339 types). Used to determine which types should be vectorized as
1340 VECTOR_BOOLEAN_TYPE_P. */
1341
1342 #define VECT_SCALAR_BOOLEAN_TYPE_P(TYPE) \
1343 (TREE_CODE (TYPE) == BOOLEAN_TYPE \
1344 || ((TREE_CODE (TYPE) == INTEGER_TYPE \
1345 || TREE_CODE (TYPE) == ENUMERAL_TYPE) \
1346 && TYPE_PRECISION (TYPE) == 1 \
1347 && TYPE_UNSIGNED (TYPE)))
1348
1349 static inline bool
1350 nested_in_vect_loop_p (class loop *loop, stmt_vec_info stmt_info)
1351 {
1352 return (loop->inner
1353 && (loop->inner == (gimple_bb (stmt_info->stmt))->loop_father));
1354 }
1355
1356 /* Return true if STMT_INFO should produce a vector mask type rather than
1357 a normal nonmask type. */
1358
1359 static inline bool
1360 vect_use_mask_type_p (stmt_vec_info stmt_info)
1361 {
1362 return stmt_info->mask_precision && stmt_info->mask_precision != ~0U;
1363 }
1364
1365 /* Return TRUE if a statement represented by STMT_INFO is a part of a
1366 pattern. */
1367
1368 static inline bool
1369 is_pattern_stmt_p (stmt_vec_info stmt_info)
1370 {
1371 return stmt_info->pattern_stmt_p;
1372 }
1373
1374 /* If STMT_INFO is a pattern statement, return the statement that it
1375 replaces, otherwise return STMT_INFO itself. */
1376
1377 inline stmt_vec_info
1378 vect_orig_stmt (stmt_vec_info stmt_info)
1379 {
1380 if (is_pattern_stmt_p (stmt_info))
1381 return STMT_VINFO_RELATED_STMT (stmt_info);
1382 return stmt_info;
1383 }
1384
1385 /* Return the later statement between STMT1_INFO and STMT2_INFO. */
1386
1387 static inline stmt_vec_info
1388 get_later_stmt (stmt_vec_info stmt1_info, stmt_vec_info stmt2_info)
1389 {
1390 if (gimple_uid (vect_orig_stmt (stmt1_info)->stmt)
1391 > gimple_uid (vect_orig_stmt (stmt2_info)->stmt))
1392 return stmt1_info;
1393 else
1394 return stmt2_info;
1395 }
1396
1397 /* If STMT_INFO has been replaced by a pattern statement, return the
1398 replacement statement, otherwise return STMT_INFO itself. */
1399
1400 inline stmt_vec_info
1401 vect_stmt_to_vectorize (stmt_vec_info stmt_info)
1402 {
1403 if (STMT_VINFO_IN_PATTERN_P (stmt_info))
1404 return STMT_VINFO_RELATED_STMT (stmt_info);
1405 return stmt_info;
1406 }
1407
1408 /* Return true if BB is a loop header. */
1409
1410 static inline bool
1411 is_loop_header_bb_p (basic_block bb)
1412 {
1413 if (bb == (bb->loop_father)->header)
1414 return true;
1415 gcc_checking_assert (EDGE_COUNT (bb->preds) == 1);
1416 return false;
1417 }
1418
1419 /* Return pow2 (X). */
1420
1421 static inline int
1422 vect_pow2 (int x)
1423 {
1424 int i, res = 1;
1425
1426 for (i = 0; i < x; i++)
1427 res *= 2;
1428
1429 return res;
1430 }
1431
1432 /* Alias targetm.vectorize.builtin_vectorization_cost. */
1433
1434 static inline int
1435 builtin_vectorization_cost (enum vect_cost_for_stmt type_of_cost,
1436 tree vectype, int misalign)
1437 {
1438 return targetm.vectorize.builtin_vectorization_cost (type_of_cost,
1439 vectype, misalign);
1440 }
1441
1442 /* Get cost by calling cost target builtin. */
1443
1444 static inline
1445 int vect_get_stmt_cost (enum vect_cost_for_stmt type_of_cost)
1446 {
1447 return builtin_vectorization_cost (type_of_cost, NULL, 0);
1448 }
1449
1450 /* Alias targetm.vectorize.init_cost. */
1451
1452 static inline void *
1453 init_cost (class loop *loop_info)
1454 {
1455 return targetm.vectorize.init_cost (loop_info);
1456 }
1457
1458 extern void dump_stmt_cost (FILE *, void *, int, enum vect_cost_for_stmt,
1459 stmt_vec_info, tree, int, unsigned,
1460 enum vect_cost_model_location);
1461
1462 /* Alias targetm.vectorize.add_stmt_cost. */
1463
1464 static inline unsigned
1465 add_stmt_cost (vec_info *vinfo, void *data, int count,
1466 enum vect_cost_for_stmt kind,
1467 stmt_vec_info stmt_info, tree vectype, int misalign,
1468 enum vect_cost_model_location where)
1469 {
1470 unsigned cost = targetm.vectorize.add_stmt_cost (vinfo, data, count, kind,
1471 stmt_info, vectype,
1472 misalign, where);
1473 if (dump_file && (dump_flags & TDF_DETAILS))
1474 dump_stmt_cost (dump_file, data, count, kind, stmt_info, vectype, misalign,
1475 cost, where);
1476 return cost;
1477 }
1478
1479 /* Alias targetm.vectorize.finish_cost. */
1480
1481 static inline void
1482 finish_cost (void *data, unsigned *prologue_cost,
1483 unsigned *body_cost, unsigned *epilogue_cost)
1484 {
1485 targetm.vectorize.finish_cost (data, prologue_cost, body_cost, epilogue_cost);
1486 }
1487
1488 /* Alias targetm.vectorize.destroy_cost_data. */
1489
1490 static inline void
1491 destroy_cost_data (void *data)
1492 {
1493 targetm.vectorize.destroy_cost_data (data);
1494 }
1495
1496 inline void
1497 add_stmt_costs (vec_info *vinfo, void *data, stmt_vector_for_cost *cost_vec)
1498 {
1499 stmt_info_for_cost *cost;
1500 unsigned i;
1501 FOR_EACH_VEC_ELT (*cost_vec, i, cost)
1502 add_stmt_cost (vinfo, data, cost->count, cost->kind, cost->stmt_info,
1503 cost->vectype, cost->misalign, cost->where);
1504 }
1505
1506 /*-----------------------------------------------------------------*/
1507 /* Info on data references alignment. */
1508 /*-----------------------------------------------------------------*/
1509 #define DR_MISALIGNMENT_UNKNOWN (-1)
1510 #define DR_MISALIGNMENT_UNINITIALIZED (-2)
1511
1512 inline void
1513 set_dr_misalignment (dr_vec_info *dr_info, int val)
1514 {
1515 dr_info->misalignment = val;
1516 }
1517
1518 inline int
1519 dr_misalignment (dr_vec_info *dr_info)
1520 {
1521 int misalign = dr_info->misalignment;
1522 gcc_assert (misalign != DR_MISALIGNMENT_UNINITIALIZED);
1523 return misalign;
1524 }
1525
1526 /* Reflects actual alignment of first access in the vectorized loop,
1527 taking into account peeling/versioning if applied. */
1528 #define DR_MISALIGNMENT(DR) dr_misalignment (DR)
1529 #define SET_DR_MISALIGNMENT(DR, VAL) set_dr_misalignment (DR, VAL)
1530
1531 /* Only defined once DR_MISALIGNMENT is defined. */
1532 #define DR_TARGET_ALIGNMENT(DR) ((DR)->target_alignment)
1533
1534 /* Return true if data access DR_INFO is aligned to its target alignment
1535 (which may be less than a full vector). */
1536
1537 static inline bool
1538 aligned_access_p (dr_vec_info *dr_info)
1539 {
1540 return (DR_MISALIGNMENT (dr_info) == 0);
1541 }
1542
1543 /* Return TRUE if the alignment of the data access is known, and FALSE
1544 otherwise. */
1545
1546 static inline bool
1547 known_alignment_for_access_p (dr_vec_info *dr_info)
1548 {
1549 return (DR_MISALIGNMENT (dr_info) != DR_MISALIGNMENT_UNKNOWN);
1550 }
1551
1552 /* Return the minimum alignment in bytes that the vectorized version
1553 of DR_INFO is guaranteed to have. */
1554
1555 static inline unsigned int
1556 vect_known_alignment_in_bytes (dr_vec_info *dr_info)
1557 {
1558 if (DR_MISALIGNMENT (dr_info) == DR_MISALIGNMENT_UNKNOWN)
1559 return TYPE_ALIGN_UNIT (TREE_TYPE (DR_REF (dr_info->dr)));
1560 if (DR_MISALIGNMENT (dr_info) == 0)
1561 return known_alignment (DR_TARGET_ALIGNMENT (dr_info));
1562 return DR_MISALIGNMENT (dr_info) & -DR_MISALIGNMENT (dr_info);
1563 }
1564
1565 /* Return the behavior of DR_INFO with respect to the vectorization context
1566 (which for outer loop vectorization might not be the behavior recorded
1567 in DR_INFO itself). */
1568
1569 static inline innermost_loop_behavior *
1570 vect_dr_behavior (vec_info *vinfo, dr_vec_info *dr_info)
1571 {
1572 stmt_vec_info stmt_info = dr_info->stmt;
1573 loop_vec_info loop_vinfo = dyn_cast<loop_vec_info> (vinfo);
1574 if (loop_vinfo == NULL
1575 || !nested_in_vect_loop_p (LOOP_VINFO_LOOP (loop_vinfo), stmt_info))
1576 return &DR_INNERMOST (dr_info->dr);
1577 else
1578 return &STMT_VINFO_DR_WRT_VEC_LOOP (stmt_info);
1579 }
1580
1581 /* Return the offset calculated by adding the offset of this DR_INFO to the
1582 corresponding data_reference's offset. If CHECK_OUTER then use
1583 vect_dr_behavior to select the appropriate data_reference to use. */
1584
1585 inline tree
1586 get_dr_vinfo_offset (vec_info *vinfo,
1587 dr_vec_info *dr_info, bool check_outer = false)
1588 {
1589 innermost_loop_behavior *base;
1590 if (check_outer)
1591 base = vect_dr_behavior (vinfo, dr_info);
1592 else
1593 base = &dr_info->dr->innermost;
1594
1595 tree offset = base->offset;
1596
1597 if (!dr_info->offset)
1598 return offset;
1599
1600 offset = fold_convert (sizetype, offset);
1601 return fold_build2 (PLUS_EXPR, TREE_TYPE (dr_info->offset), offset,
1602 dr_info->offset);
1603 }
1604
1605
1606 /* Return true if the vect cost model is unlimited. */
1607 static inline bool
1608 unlimited_cost_model (loop_p loop)
1609 {
1610 if (loop != NULL && loop->force_vectorize
1611 && flag_simd_cost_model != VECT_COST_MODEL_DEFAULT)
1612 return flag_simd_cost_model == VECT_COST_MODEL_UNLIMITED;
1613 return (flag_vect_cost_model == VECT_COST_MODEL_UNLIMITED);
1614 }
1615
1616 /* Return true if the loop described by LOOP_VINFO is fully-masked and
1617 if the first iteration should use a partial mask in order to achieve
1618 alignment. */
1619
1620 static inline bool
1621 vect_use_loop_mask_for_alignment_p (loop_vec_info loop_vinfo)
1622 {
1623 return (LOOP_VINFO_FULLY_MASKED_P (loop_vinfo)
1624 && LOOP_VINFO_PEELING_FOR_ALIGNMENT (loop_vinfo));
1625 }
1626
1627 /* Return the number of vectors of type VECTYPE that are needed to get
1628 NUNITS elements. NUNITS should be based on the vectorization factor,
1629 so it is always a known multiple of the number of elements in VECTYPE. */
1630
1631 static inline unsigned int
1632 vect_get_num_vectors (poly_uint64 nunits, tree vectype)
1633 {
1634 return exact_div (nunits, TYPE_VECTOR_SUBPARTS (vectype)).to_constant ();
1635 }
1636
1637 /* Return the number of copies needed for loop vectorization when
1638 a statement operates on vectors of type VECTYPE. This is the
1639 vectorization factor divided by the number of elements in
1640 VECTYPE and is always known at compile time. */
1641
1642 static inline unsigned int
1643 vect_get_num_copies (loop_vec_info loop_vinfo, tree vectype)
1644 {
1645 return vect_get_num_vectors (LOOP_VINFO_VECT_FACTOR (loop_vinfo), vectype);
1646 }
1647
1648 /* Update maximum unit count *MAX_NUNITS so that it accounts for
1649 NUNITS. *MAX_NUNITS can be 1 if we haven't yet recorded anything. */
1650
1651 static inline void
1652 vect_update_max_nunits (poly_uint64 *max_nunits, poly_uint64 nunits)
1653 {
1654 /* All unit counts have the form vec_info::vector_size * X for some
1655 rational X, so two unit sizes must have a common multiple.
1656 Everything is a multiple of the initial value of 1. */
1657 *max_nunits = force_common_multiple (*max_nunits, nunits);
1658 }
1659
1660 /* Update maximum unit count *MAX_NUNITS so that it accounts for
1661 the number of units in vector type VECTYPE. *MAX_NUNITS can be 1
1662 if we haven't yet recorded any vector types. */
1663
1664 static inline void
1665 vect_update_max_nunits (poly_uint64 *max_nunits, tree vectype)
1666 {
1667 vect_update_max_nunits (max_nunits, TYPE_VECTOR_SUBPARTS (vectype));
1668 }
1669
1670 /* Return the vectorization factor that should be used for costing
1671 purposes while vectorizing the loop described by LOOP_VINFO.
1672 Pick a reasonable estimate if the vectorization factor isn't
1673 known at compile time. */
1674
1675 static inline unsigned int
1676 vect_vf_for_cost (loop_vec_info loop_vinfo)
1677 {
1678 return estimated_poly_value (LOOP_VINFO_VECT_FACTOR (loop_vinfo));
1679 }
1680
1681 /* Estimate the number of elements in VEC_TYPE for costing purposes.
1682 Pick a reasonable estimate if the exact number isn't known at
1683 compile time. */
1684
1685 static inline unsigned int
1686 vect_nunits_for_cost (tree vec_type)
1687 {
1688 return estimated_poly_value (TYPE_VECTOR_SUBPARTS (vec_type));
1689 }
1690
1691 /* Return the maximum possible vectorization factor for LOOP_VINFO. */
1692
1693 static inline unsigned HOST_WIDE_INT
1694 vect_max_vf (loop_vec_info loop_vinfo)
1695 {
1696 unsigned HOST_WIDE_INT vf;
1697 if (LOOP_VINFO_VECT_FACTOR (loop_vinfo).is_constant (&vf))
1698 return vf;
1699 return MAX_VECTORIZATION_FACTOR;
1700 }
1701
1702 /* Return the size of the value accessed by unvectorized data reference
1703 DR_INFO. This is only valid once STMT_VINFO_VECTYPE has been calculated
1704 for the associated gimple statement, since that guarantees that DR_INFO
1705 accesses either a scalar or a scalar equivalent. ("Scalar equivalent"
1706 here includes things like V1SI, which can be vectorized in the same way
1707 as a plain SI.) */
1708
1709 inline unsigned int
1710 vect_get_scalar_dr_size (dr_vec_info *dr_info)
1711 {
1712 return tree_to_uhwi (TYPE_SIZE_UNIT (TREE_TYPE (DR_REF (dr_info->dr))));
1713 }
1714
1715 /* Return true if LOOP_VINFO requires a runtime check for whether the
1716 vector loop is profitable. */
1717
1718 inline bool
1719 vect_apply_runtime_profitability_check_p (loop_vec_info loop_vinfo)
1720 {
1721 unsigned int th = LOOP_VINFO_COST_MODEL_THRESHOLD (loop_vinfo);
1722 return (!LOOP_VINFO_NITERS_KNOWN_P (loop_vinfo)
1723 && th >= vect_vf_for_cost (loop_vinfo));
1724 }
1725
1726 /* Source location + hotness information. */
1727 extern dump_user_location_t vect_location;
1728
1729 /* A macro for calling:
1730 dump_begin_scope (MSG, vect_location);
1731 via an RAII object, thus printing "=== MSG ===\n" to the dumpfile etc,
1732 and then calling
1733 dump_end_scope ();
1734 once the object goes out of scope, thus capturing the nesting of
1735 the scopes.
1736
1737 These scopes affect dump messages within them: dump messages at the
1738 top level implicitly default to MSG_PRIORITY_USER_FACING, whereas those
1739 in a nested scope implicitly default to MSG_PRIORITY_INTERNALS. */
1740
1741 #define DUMP_VECT_SCOPE(MSG) \
1742 AUTO_DUMP_SCOPE (MSG, vect_location)
1743
1744 /* A sentinel class for ensuring that the "vect_location" global gets
1745 reset at the end of a scope.
1746
1747 The "vect_location" global is used during dumping and contains a
1748 location_t, which could contain references to a tree block via the
1749 ad-hoc data. This data is used for tracking inlining information,
1750 but it's not a GC root; it's simply assumed that such locations never
1751 get accessed if the blocks are optimized away.
1752
1753 Hence we need to ensure that such locations are purged at the end
1754 of any operations using them (e.g. via this class). */
1755
1756 class auto_purge_vect_location
1757 {
1758 public:
1759 ~auto_purge_vect_location ();
1760 };
1761
1762 /*-----------------------------------------------------------------*/
1763 /* Function prototypes. */
1764 /*-----------------------------------------------------------------*/
1765
1766 /* Simple loop peeling and versioning utilities for vectorizer's purposes -
1767 in tree-vect-loop-manip.c. */
1768 extern void vect_set_loop_condition (class loop *, loop_vec_info,
1769 tree, tree, tree, bool);
1770 extern bool slpeel_can_duplicate_loop_p (const class loop *, const_edge);
1771 class loop *slpeel_tree_duplicate_loop_to_edge_cfg (class loop *,
1772 class loop *, edge);
1773 class loop *vect_loop_versioning (loop_vec_info, gimple *);
1774 extern class loop *vect_do_peeling (loop_vec_info, tree, tree,
1775 tree *, tree *, tree *, int, bool, bool,
1776 tree *);
1777 extern void vect_prepare_for_masked_peels (loop_vec_info);
1778 extern dump_user_location_t find_loop_location (class loop *);
1779 extern bool vect_can_advance_ivs_p (loop_vec_info);
1780 extern void vect_update_inits_of_drs (loop_vec_info, tree, tree_code);
1781
1782 /* In tree-vect-stmts.c. */
1783 extern tree get_related_vectype_for_scalar_type (machine_mode, tree,
1784 poly_uint64 = 0);
1785 extern tree get_vectype_for_scalar_type (vec_info *, tree, unsigned int = 0);
1786 extern tree get_vectype_for_scalar_type (vec_info *, tree, slp_tree);
1787 extern tree get_mask_type_for_scalar_type (vec_info *, tree, unsigned int = 0);
1788 extern tree get_same_sized_vectype (tree, tree);
1789 extern bool vect_chooses_same_modes_p (vec_info *, machine_mode);
1790 extern bool vect_get_loop_mask_type (loop_vec_info);
1791 extern bool vect_is_simple_use (tree, vec_info *, enum vect_def_type *,
1792 stmt_vec_info * = NULL, gimple ** = NULL);
1793 extern bool vect_is_simple_use (tree, vec_info *, enum vect_def_type *,
1794 tree *, stmt_vec_info * = NULL,
1795 gimple ** = NULL);
1796 extern bool vect_is_simple_use (vec_info *, stmt_vec_info, slp_tree,
1797 unsigned, tree *, slp_tree *,
1798 enum vect_def_type *,
1799 tree *, stmt_vec_info * = NULL);
1800 extern bool vect_maybe_update_slp_op_vectype (slp_tree, tree);
1801 extern bool supportable_widening_operation (vec_info *,
1802 enum tree_code, stmt_vec_info,
1803 tree, tree, enum tree_code *,
1804 enum tree_code *, int *,
1805 vec<tree> *);
1806 extern bool supportable_narrowing_operation (enum tree_code, tree, tree,
1807 enum tree_code *, int *,
1808 vec<tree> *);
1809
1810 extern unsigned record_stmt_cost (stmt_vector_for_cost *, int,
1811 enum vect_cost_for_stmt, stmt_vec_info,
1812 tree, int, enum vect_cost_model_location);
1813
1814 /* Overload of record_stmt_cost with VECTYPE derived from STMT_INFO. */
1815
1816 static inline unsigned
1817 record_stmt_cost (stmt_vector_for_cost *body_cost_vec, int count,
1818 enum vect_cost_for_stmt kind, stmt_vec_info stmt_info,
1819 int misalign, enum vect_cost_model_location where)
1820 {
1821 return record_stmt_cost (body_cost_vec, count, kind, stmt_info,
1822 STMT_VINFO_VECTYPE (stmt_info), misalign, where);
1823 }
1824
1825 extern void vect_finish_replace_stmt (vec_info *, stmt_vec_info, gimple *);
1826 extern void vect_finish_stmt_generation (vec_info *, stmt_vec_info, gimple *,
1827 gimple_stmt_iterator *);
1828 extern opt_result vect_mark_stmts_to_be_vectorized (loop_vec_info, bool *);
1829 extern tree vect_get_store_rhs (stmt_vec_info);
1830 void vect_get_vec_defs_for_operand (vec_info *vinfo, stmt_vec_info, unsigned,
1831 tree op, vec<tree> *, tree = NULL);
1832 void vect_get_vec_defs (vec_info *, stmt_vec_info, slp_tree, unsigned,
1833 tree, vec<tree> *,
1834 tree = NULL, vec<tree> * = NULL,
1835 tree = NULL, vec<tree> * = NULL,
1836 tree = NULL, vec<tree> * = NULL);
1837 void vect_get_vec_defs (vec_info *, stmt_vec_info, slp_tree, unsigned,
1838 tree, vec<tree> *, tree,
1839 tree = NULL, vec<tree> * = NULL, tree = NULL,
1840 tree = NULL, vec<tree> * = NULL, tree = NULL,
1841 tree = NULL, vec<tree> * = NULL, tree = NULL);
1842 extern tree vect_init_vector (vec_info *, stmt_vec_info, tree, tree,
1843 gimple_stmt_iterator *);
1844 extern tree vect_get_slp_vect_def (slp_tree, unsigned);
1845 extern bool vect_transform_stmt (vec_info *, stmt_vec_info,
1846 gimple_stmt_iterator *,
1847 slp_tree, slp_instance);
1848 extern void vect_remove_stores (vec_info *, stmt_vec_info);
1849 extern bool vect_nop_conversion_p (stmt_vec_info);
1850 extern opt_result vect_analyze_stmt (vec_info *, stmt_vec_info, bool *,
1851 slp_tree,
1852 slp_instance, stmt_vector_for_cost *);
1853 extern void vect_get_load_cost (vec_info *, stmt_vec_info, int, bool,
1854 unsigned int *, unsigned int *,
1855 stmt_vector_for_cost *,
1856 stmt_vector_for_cost *, bool);
1857 extern void vect_get_store_cost (vec_info *, stmt_vec_info, int,
1858 unsigned int *, stmt_vector_for_cost *);
1859 extern bool vect_supportable_shift (vec_info *, enum tree_code, tree);
1860 extern tree vect_gen_perm_mask_any (tree, const vec_perm_indices &);
1861 extern tree vect_gen_perm_mask_checked (tree, const vec_perm_indices &);
1862 extern void optimize_mask_stores (class loop*);
1863 extern gcall *vect_gen_while (tree, tree, tree);
1864 extern tree vect_gen_while_not (gimple_seq *, tree, tree, tree);
1865 extern opt_result vect_get_vector_types_for_stmt (vec_info *,
1866 stmt_vec_info, tree *,
1867 tree *, unsigned int = 0);
1868 extern opt_tree vect_get_mask_type_for_stmt (stmt_vec_info, unsigned int = 0);
1869
1870 /* In tree-vect-data-refs.c. */
1871 extern bool vect_can_force_dr_alignment_p (const_tree, poly_uint64);
1872 extern enum dr_alignment_support vect_supportable_dr_alignment
1873 (vec_info *, dr_vec_info *, bool);
1874 extern tree vect_get_smallest_scalar_type (stmt_vec_info, HOST_WIDE_INT *,
1875 HOST_WIDE_INT *);
1876 extern opt_result vect_analyze_data_ref_dependences (loop_vec_info, unsigned int *);
1877 extern bool vect_slp_analyze_instance_dependence (vec_info *, slp_instance);
1878 extern opt_result vect_enhance_data_refs_alignment (loop_vec_info);
1879 extern opt_result vect_analyze_data_refs_alignment (loop_vec_info);
1880 extern bool vect_slp_analyze_instance_alignment (vec_info *, slp_instance);
1881 extern opt_result vect_analyze_data_ref_accesses (vec_info *, vec<int> *);
1882 extern opt_result vect_prune_runtime_alias_test_list (loop_vec_info);
1883 extern bool vect_gather_scatter_fn_p (vec_info *, bool, bool, tree, tree,
1884 tree, int, internal_fn *, tree *);
1885 extern bool vect_check_gather_scatter (stmt_vec_info, loop_vec_info,
1886 gather_scatter_info *);
1887 extern opt_result vect_find_stmt_data_reference (loop_p, gimple *,
1888 vec<data_reference_p> *,
1889 vec<int> *, int);
1890 extern opt_result vect_analyze_data_refs (vec_info *, poly_uint64 *, bool *);
1891 extern void vect_record_base_alignments (vec_info *);
1892 extern tree vect_create_data_ref_ptr (vec_info *,
1893 stmt_vec_info, tree, class loop *, tree,
1894 tree *, gimple_stmt_iterator *,
1895 gimple **, bool,
1896 tree = NULL_TREE, tree = NULL_TREE);
1897 extern tree bump_vector_ptr (vec_info *, tree, gimple *, gimple_stmt_iterator *,
1898 stmt_vec_info, tree);
1899 extern void vect_copy_ref_info (tree, tree);
1900 extern tree vect_create_destination_var (tree, tree);
1901 extern bool vect_grouped_store_supported (tree, unsigned HOST_WIDE_INT);
1902 extern bool vect_store_lanes_supported (tree, unsigned HOST_WIDE_INT, bool);
1903 extern bool vect_grouped_load_supported (tree, bool, unsigned HOST_WIDE_INT);
1904 extern bool vect_load_lanes_supported (tree, unsigned HOST_WIDE_INT, bool);
1905 extern void vect_permute_store_chain (vec_info *,
1906 vec<tree> ,unsigned int, stmt_vec_info,
1907 gimple_stmt_iterator *, vec<tree> *);
1908 extern tree vect_setup_realignment (vec_info *,
1909 stmt_vec_info, gimple_stmt_iterator *,
1910 tree *, enum dr_alignment_support, tree,
1911 class loop **);
1912 extern void vect_transform_grouped_load (vec_info *, stmt_vec_info, vec<tree>,
1913 int, gimple_stmt_iterator *);
1914 extern void vect_record_grouped_load_vectors (vec_info *,
1915 stmt_vec_info, vec<tree>);
1916 extern tree vect_get_new_vect_var (tree, enum vect_var_kind, const char *);
1917 extern tree vect_get_new_ssa_name (tree, enum vect_var_kind,
1918 const char * = NULL);
1919 extern tree vect_create_addr_base_for_vector_ref (vec_info *,
1920 stmt_vec_info, gimple_seq *,
1921 tree, tree = NULL_TREE);
1922
1923 /* In tree-vect-loop.c. */
1924 extern widest_int vect_iv_limit_for_partial_vectors (loop_vec_info loop_vinfo);
1925 bool vect_rgroup_iv_might_wrap_p (loop_vec_info, rgroup_controls *);
1926 /* Used in tree-vect-loop-manip.c */
1927 extern opt_result vect_determine_partial_vectors_and_peeling (loop_vec_info,
1928 bool);
1929 /* Used in gimple-loop-interchange.c and tree-parloops.c. */
1930 extern bool check_reduction_path (dump_user_location_t, loop_p, gphi *, tree,
1931 enum tree_code);
1932 extern bool needs_fold_left_reduction_p (tree, tree_code);
1933 /* Drive for loop analysis stage. */
1934 extern opt_loop_vec_info vect_analyze_loop (class loop *, vec_info_shared *);
1935 extern tree vect_build_loop_niters (loop_vec_info, bool * = NULL);
1936 extern void vect_gen_vector_loop_niters (loop_vec_info, tree, tree *,
1937 tree *, bool);
1938 extern tree vect_halve_mask_nunits (tree, machine_mode);
1939 extern tree vect_double_mask_nunits (tree, machine_mode);
1940 extern void vect_record_loop_mask (loop_vec_info, vec_loop_masks *,
1941 unsigned int, tree, tree);
1942 extern tree vect_get_loop_mask (gimple_stmt_iterator *, vec_loop_masks *,
1943 unsigned int, tree, unsigned int);
1944 extern void vect_record_loop_len (loop_vec_info, vec_loop_lens *, unsigned int,
1945 tree, unsigned int);
1946 extern tree vect_get_loop_len (loop_vec_info, vec_loop_lens *, unsigned int,
1947 unsigned int);
1948 extern gimple_seq vect_gen_len (tree, tree, tree, tree);
1949 extern stmt_vec_info info_for_reduction (vec_info *, stmt_vec_info);
1950
1951 /* Drive for loop transformation stage. */
1952 extern class loop *vect_transform_loop (loop_vec_info, gimple *);
1953 extern opt_loop_vec_info vect_analyze_loop_form (class loop *,
1954 vec_info_shared *);
1955 extern bool vectorizable_live_operation (vec_info *,
1956 stmt_vec_info, gimple_stmt_iterator *,
1957 slp_tree, slp_instance, int,
1958 bool, stmt_vector_for_cost *);
1959 extern bool vectorizable_reduction (loop_vec_info, stmt_vec_info,
1960 slp_tree, slp_instance,
1961 stmt_vector_for_cost *);
1962 extern bool vectorizable_induction (loop_vec_info, stmt_vec_info,
1963 gimple **, slp_tree,
1964 stmt_vector_for_cost *);
1965 extern bool vect_transform_reduction (loop_vec_info, stmt_vec_info,
1966 gimple_stmt_iterator *,
1967 gimple **, slp_tree);
1968 extern bool vect_transform_cycle_phi (loop_vec_info, stmt_vec_info,
1969 gimple **,
1970 slp_tree, slp_instance);
1971 extern bool vectorizable_lc_phi (loop_vec_info, stmt_vec_info,
1972 gimple **, slp_tree);
1973 extern bool vectorizable_phi (vec_info *, stmt_vec_info, gimple **, slp_tree,
1974 stmt_vector_for_cost *);
1975 extern bool vect_worthwhile_without_simd_p (vec_info *, tree_code);
1976 extern int vect_get_known_peeling_cost (loop_vec_info, int, int *,
1977 stmt_vector_for_cost *,
1978 stmt_vector_for_cost *,
1979 stmt_vector_for_cost *);
1980 extern tree cse_and_gimplify_to_preheader (loop_vec_info, tree);
1981
1982 /* In tree-vect-slp.c. */
1983 extern void vect_slp_init (void);
1984 extern void vect_slp_fini (void);
1985 extern void vect_free_slp_instance (slp_instance);
1986 extern bool vect_transform_slp_perm_load (vec_info *, slp_tree, vec<tree>,
1987 gimple_stmt_iterator *, poly_uint64,
1988 bool, unsigned *,
1989 unsigned * = nullptr);
1990 extern bool vect_slp_analyze_operations (vec_info *);
1991 extern void vect_schedule_slp (vec_info *, vec<slp_instance>);
1992 extern opt_result vect_analyze_slp (vec_info *, unsigned);
1993 extern bool vect_make_slp_decision (loop_vec_info);
1994 extern void vect_detect_hybrid_slp (loop_vec_info);
1995 extern void vect_optimize_slp (vec_info *);
1996 extern void vect_gather_slp_loads (vec_info *);
1997 extern void vect_get_slp_defs (slp_tree, vec<tree> *);
1998 extern void vect_get_slp_defs (vec_info *, slp_tree, vec<vec<tree> > *,
1999 unsigned n = -1U);
2000 extern bool vect_slp_bb (basic_block);
2001 extern bool vect_slp_function (function *);
2002 extern stmt_vec_info vect_find_last_scalar_stmt_in_slp (slp_tree);
2003 extern stmt_vec_info vect_find_first_scalar_stmt_in_slp (slp_tree);
2004 extern bool is_simple_and_all_uses_invariant (stmt_vec_info, loop_vec_info);
2005 extern bool can_duplicate_and_interleave_p (vec_info *, unsigned int, tree,
2006 unsigned int * = NULL,
2007 tree * = NULL, tree * = NULL);
2008 extern void duplicate_and_interleave (vec_info *, gimple_seq *, tree,
2009 vec<tree>, unsigned int, vec<tree> &);
2010 extern int vect_get_place_in_interleaving_chain (stmt_vec_info, stmt_vec_info);
2011 extern bool vect_update_shared_vectype (stmt_vec_info, tree);
2012 extern slp_tree vect_create_new_slp_node (unsigned, tree_code);
2013 extern void vect_free_slp_tree (slp_tree);
2014
2015 /* In tree-vect-patterns.c. */
2016 extern void
2017 vect_mark_pattern_stmts (vec_info *, stmt_vec_info, gimple *, tree);
2018
2019 /* Pattern recognition functions.
2020 Additional pattern recognition functions can (and will) be added
2021 in the future. */
2022 void vect_pattern_recog (vec_info *);
2023
2024 /* In tree-vectorizer.c. */
2025 unsigned vectorize_loops (void);
2026 void vect_free_loop_info_assumptions (class loop *);
2027 gimple *vect_loop_vectorized_call (class loop *, gcond **cond = NULL);
2028 bool vect_stmt_dominates_stmt_p (gimple *, gimple *);
2029
2030 /* SLP Pattern matcher types, tree-vect-slp-patterns.c. */
2031
2032 /* Forward declaration of possible two operands operation that can be matched
2033 by the complex numbers pattern matchers. */
2034 enum _complex_operation : unsigned;
2035
2036 /* All possible load permute values that could result from the partial data-flow
2037 analysis. */
2038 typedef enum _complex_perm_kinds {
2039 PERM_UNKNOWN,
2040 PERM_EVENODD,
2041 PERM_ODDEVEN,
2042 PERM_ODDODD,
2043 PERM_EVENEVEN,
2044 /* Can be combined with any other PERM values. */
2045 PERM_TOP
2046 } complex_perm_kinds_t;
2047
2048 /* A pair with a load permute and a corresponding complex_perm_kind which gives
2049 information about the load it represents. */
2050 typedef std::pair<complex_perm_kinds_t, load_permutation_t>
2051 complex_load_perm_t;
2052
2053 /* Cache from nodes to the load permutation they represent. */
2054 typedef hash_map <slp_tree, complex_load_perm_t>
2055 slp_tree_to_load_perm_map_t;
2056
2057 /* Vector pattern matcher base class. All SLP pattern matchers must inherit
2058 from this type. */
2059
2060 class vect_pattern
2061 {
2062 protected:
2063 /* The number of arguments that the IFN requires. */
2064 unsigned m_num_args;
2065
2066 /* The internal function that will be used when a pattern is created. */
2067 internal_fn m_ifn;
2068
2069 /* The current node being inspected. */
2070 slp_tree *m_node;
2071
2072 /* The list of operands to be the children for the node produced when the
2073 internal function is created. */
2074 vec<slp_tree> m_ops;
2075
2076 /* Default constructor where NODE is the root of the tree to inspect. */
2077 vect_pattern (slp_tree *node, vec<slp_tree> *m_ops, internal_fn ifn)
2078 {
2079 this->m_ifn = ifn;
2080 this->m_node = node;
2081 this->m_ops.create (0);
2082 this->m_ops.safe_splice (*m_ops);
2083 }
2084
2085 public:
2086
2087 /* Create a new instance of the pattern matcher class of the given type. */
2088 static vect_pattern* recognize (slp_tree_to_load_perm_map_t *, slp_tree *);
2089
2090 /* Build the pattern from the data collected so far. */
2091 virtual void build (vec_info *) = 0;
2092
2093 /* Default destructor. */
2094 virtual ~vect_pattern ()
2095 {
2096 this->m_ops.release ();
2097 }
2098 };
2099
2100 /* Function pointer to create a new pattern matcher from a generic type. */
2101 typedef vect_pattern* (*vect_pattern_decl_t) (slp_tree_to_load_perm_map_t *,
2102 slp_tree *);
2103
2104 /* List of supported pattern matchers. */
2105 extern vect_pattern_decl_t slp_patterns[];
2106
2107 /* Number of supported pattern matchers. */
2108 extern size_t num__slp_patterns;
2109
2110 #endif /* GCC_TREE_VECTORIZER_H */