Halide 22.0.0 Halide compiler and libraries

LoopNest.h
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1/** This file defines the LoopNest, which is our
2 * representation of a Halide schedule, and contains methods to
3 * generate candidates for scheduling as well as extract a
4 * featurization that can be used to cost each candidate. */
5
6#ifndef LOOP_NEST_H
7#define LOOP_NEST_H
8
9#include "ASLog.h"
10#include "CostModel.h"
11#include "FunctionDAG.h"
12#include "GPULoopInfo.h"
13#include "GPUMemInfo.h"
14#include "PerfectHashMap.h"
15#include "SearchSpaceOptions.h"
16#include "Statistics.h"
17#include "ThreadInfo.h"
18#include "Tiling.h"
19#include <set>
20#include <vector>
21
22 namespace Halide {
23 namespace Internal {
24 namespace Autoscheduler {
25
26 template<typename T>
27 using NodeMap = PerfectHashMap<FunctionDAG::Node, T>;
28
29 template<typename T>
30 using StageMap = PerfectHashMap<FunctionDAG::Node::Stage, T>;
31
32 enum class GPU_parallelism {
33 Block,
34 Thread,
35 Serial,
36 Simd,
37 Parallelized,
38 None
39};
40
41std::string stringify(GPU_parallelism label);
42
43// inlined => func is inlined so has no memory store location
44 enum class GPUMemoryType {
45 Global,
46 Shared,
47 Local,
48 Registers,
49 Inlined
50};
51
52 bool may_subtile(const Anderson2021Params &params);
53
54 int64_t get_shared_memory_limit(const Anderson2021Params &params);
55
56 int64_t get_shared_memory_sm_limit(const Anderson2021Params &params);
57
58 int64_t get_active_block_hardware_limit(const Anderson2021Params &params);
59
60 int64_t get_active_warp_hardware_limit(const Anderson2021Params &params);
61
62 constexpr int64_t get_register_mem_alloc_limit() {
63 return 128;
64}
65
66 int get_unroll_limit(const Target &target);
67
68 bool in_range_zero_one(double x);
69
70 bool are_valid_thread_extents(const vector<int64_t> &counts);
71
72 double get_idle_lane_wastage_limit_env_var();
73 double get_idle_lane_wastage_limit();
74
75 bool all(const vector<int> &v);
76 bool accessed_at_constant_indices(const std::vector<int> &unrolled, const FunctionDAG::Edge *e);
77
78// We're going to do a tree search over possible schedules to find an
79// optimal one. A tree search requires a state, and a function that
80// gives you children of the state (with costs). The following struct
81// represents the state, which is a partial schedule.
82//
83// A partial schedule is a tree. Each node is some portion of the for
84// loop nest of some Func. If there are no children, it's the
85// innermost set of loops. If there are children, it's a loop over
86// tiles of that Func.
87 struct LoopNest {
88 mutable RefCount ref_count;
89
90 // The extents of this loop. Put another way, the number of tiles,
91 // not the size of each tile.
92 vector<int64_t> size;
93
94 // The nodes inside the loop body
95 vector<IntrusivePtr<const LoopNest>> children;
96
97 // Funcs inlined into this inner loop, and the number of times
98 // each is called. Only valid if children is empty.
99 NodeMap<int64_t> inlined;
100
101 // Funcs stored inside this loop
102 std::set<const FunctionDAG::Node *> store_at;
103
104 // The total bounds required of any given Func over all iterations
105 // of this loop. In the paper, this is represented using the
106 // little boxes to the left of the loop nest tree figures.
107 mutable NodeMap<Bound> bounds;
108
109 // The Func this loop nest belongs to
110 const FunctionDAG::Node *node = nullptr;
111
112 // The stage of the Func
113 const FunctionDAG::Node::Stage *stage = nullptr;
114
115 // Is this the innermost loop of this func (the SIMD loop)?
116 bool innermost = false;
117
118 // Are we permitted to tile this loop?
119 bool tileable = false;
120
121 // Is this the parallel outer loop?
122 bool parallel = false;
123
124 // What dimension is this Func vectorized over, in terms of the pure args of the Func?
125 int vector_dim = -1;
126
127 // Which loop corresponds to the innermost storage dimension and will be vectorized. -1 means none of them.
128 int vectorized_loop_index = -1;
129
130 // Apply gpu threads to this loop nest
131 mutable GPU_parallelism gpu_label = GPU_parallelism::None;
132
133 struct FeatureIntermediates {
134 double inlined_calls;
135 double num_vectors;
136 double num_scalars;
137 double vector_size;
138 double innermost_pure_loop_extent;
139 double outer_parallelism;
140 double num_warps_per_block;
141 double num_threads_per_block;
142 double points_computed_per_thread;
143 };
144
145 mutable std::map<uint64_t, StageMap<StageMap<FeatureIntermediates>>> feature_intermediates;
146 mutable std::map<uint64_t, StageMap<ScheduleFeatures>> features;
147
148 bool is_gpu_serial(const Target &target) const {
149 return target.has_gpu_feature() && gpu_label == GPU_parallelism::Serial;
150 }
151
152 bool is_gpu_thread(const Target &target) const {
153 return target.has_gpu_feature() && gpu_label == GPU_parallelism::Thread;
154 }
155
156 bool is_gpu_block(const Target &target) const {
157 return target.has_gpu_feature() && gpu_label == GPU_parallelism::Block;
158 }
159
160 bool is_scalar() const {
161 return size.empty();
162 }
163
164 // given a newly inserted node f into this LoopNest, get union of thread counts in each dimension
165 // across all siblings of f.
166 vector<int64_t> get_union_thread_counts(const FunctionDAG::Node *f) const;
167
168 // given a newly inserted node f into this LoopNest, gets the size of
169 // all of f's stages and their pure_dim indices
170 void get_stage_sizes(const FunctionDAG::Node *f,
171 vector<vector<int64_t>> &stage_sizes,
172 vector<vector<int>> &pure_dims,
173 vector<int> &vectorized_indices) const;
174
175 // given the loop nest of a stage to parallelize at root, figure out if using odd tile sizes
176 // for the vectorized dimension will allow the resulting thread tiles to be multiples of 32
177 // if so, we will include these in the serial loop sizes
178 void generate_vec_dim_serial_tilings(vector<int> &serial_sizes) const;
179
180 // get the loop nests of a newly inserted node, f, that is marked GPU threads. Tiles
181 // the newly inserted loop nests of f into a threads loop outside a serial loop.
182 // V is the vectorized dimension of f. Adds loopnests created from each tiling option in result.
183 bool add_gpu_thread_tilings(const FunctionDAG::Node *f,
184 const Anderson2021Params &params,
185 const Target &target,
186 int v,
187 vector<IntrusivePtr<const LoopNest>> &result,
188 const vector<int64_t> &max_size);
189
190 void copy_from(const LoopNest &n);
191 void copy_from_including_features(const LoopNest &n);
192
193 static void hash_combine(uint64_t &h, uint64_t next) {
194 // From boost
195 h ^= (next + 0x9e3779b9 + (h << 6) + (h >> 2));
196 }
197
198 // Hash the loop structure and sizes up to a fixed depth. This is
199 // used as the hash function for the coarse-to-fine beam search in
200 // the paper.
201 void structural_hash(uint64_t &h, int depth) const;
202
203 // How many funcs are scheduled inside this loop level. Used in
204 // the structural hash.
205 size_t funcs_realized_or_inlined() const {
206 size_t count = inlined.size() + store_at.size();
207 for (const auto &c : children) {
208 count += c->funcs_realized_or_inlined();
209 }
210 return count;
211 }
212
213 // All of a stage's interesting locations in the loop nest. Used to help compute the featurization of a stage.
214 struct Sites {
215 const LoopNest *compute = nullptr; // Its containing compute_at site
216 const LoopNest *store = nullptr; // Its containing store_at site
217 const LoopNest *produce = nullptr; // Its own outermost node
218 const LoopNest *innermost = nullptr; // Its innermost node - usually a SIMD loop
219 const LoopNest *task = nullptr; // The parallel for loop it belongs to
220 const LoopNest *thread = nullptr; // Its containing gpu_thread loop
221 GPUMemoryType gpu_store_memory_type; // global, local, shared?
222 int64_t allocation_size = 0; // Allocation size in bytes
223 bool is_constant_allocation = false; // Does the allocation have constant size?
224 int64_t num_realizations = 0; // Number of times this stage is realized. Only valid for unscheduled producers
225 bool inlined = false; // Is the Func inlined?
226 std::vector<const LoopNest *> inlined_innermosts; // Is the Func inlined?
227 uint64_t hash_of_producers_stored_at_root;
228
229 bool is_stored_in_global_mem() const {
230 return gpu_store_memory_type == GPUMemoryType::Global;
231 }
232 bool is_stored_in_shared_mem() const {
233 return gpu_store_memory_type == GPUMemoryType::Shared;
234 }
235 bool is_stored_in_local_mem() const {
236 return gpu_store_memory_type == GPUMemoryType::Local;
237 }
238 bool is_stored_in_registers() const {
239 return gpu_store_memory_type == GPUMemoryType::Registers;
240 }
241 };
242
243 GPUMemoryType get_gpu_memory_type(bool in_block,
244 bool in_thread,
245 bool is_inlined = false) const;
246
247 std::vector<int> unrolled_loops(const Target &target,
248 const LoopNest *parent,
249 const LoopNest *grandparent) const;
250
251 void get_allocs_that_can_be_promoted_to_registers(const Target &target,
252 StageMap<Sites> &sites,
253 NodeMap<bool> &can_be_promoted_to_registers,
254 const LoopNest *grandparent,
255 const LoopNest *parent) const;
256
257 bool promote_allocs_to_registers(const Target &target,
258 StageMap<Sites> &sites) const;
259
260 // Compute all the sites of interest for each pipeline stage
261 void get_sites(const Target &target,
262 StageMap<Sites> &sites,
263 StageMap<int64_t> &shared_mem_alloc_sizes,
264 const LoopNest *task = nullptr,
265 const LoopNest *parent = nullptr,
266 const LoopNest *current_thread_loop = nullptr) const;
267
268 // A helper for the working_set_at_task feature. Most features are
269 // computed in the recursive pass 'compute_features' below, but
270 // this one must be done in a second separate recursive pass.
271 void set_working_set_at_task_feature(int64_t working_set,
272 StageMap<ScheduleFeatures> *features) const {
273 for (const auto &c : children) {
274 c->set_working_set_at_task_feature(working_set, features);
275 features->get(c->stage).working_set_at_task = working_set;
276 }
277 }
278
279 bool exceeds_serial_extents_limit(const Target &target,
280 const LoopNest *parent,
281 bool in_threads_loop) const;
282
283 bool node_has_dynamic_region_computed(const FunctionDAG::Node *f) const;
284
285 bool has_dynamic_allocation_inside_thread(bool in_thread_loop) const;
286
287 const LoopNest *find_pure_stage_loop_nest(const FunctionDAG::Node *node) const;
288
289 int get_pure_stage_vectorized_loop_index(const FunctionDAG::Node *node) const;
290
291 int get_vectorized_loop_index_from_pure_stage(const LoopNest &root) const;
292
293 // Get the stride over "node's" storage for a unit increment in the vectorized loop's
294 // index
295 double storage_stride(const LoadJacobian &jac,
296 int innermost_storage_dim,
297 const FunctionDAG::Node *storage_node,
298 const Bound &store_bounds,
299 const LoopNest &root) const;
300
301 Strides compute_strides(const LoadJacobian &jac,
302 int innermost_storage_dim,
303 const FunctionDAG::Node *storage_node,
304 const Bound &store_bounds,
305 const ThreadInfo *thread_info,
306 bool verbose = false) const;
307
308 bool all_strides_exist(const LoadJacobian &jac,
309 const FunctionDAG::Node *storage_node,
310 const LoopNest &root) const;
311
312 int get_actual_vector_dim(const Bound &store_bounds) const;
313
314 void compute_gpu_store_features(const LoadJacobian &jac,
315 int consumer_innermost_dim,
316 const FunctionDAG::Node *node,
317 const Bound &consumer_store_bounds,
318 const GPULoopInfo &gpu_loop_info,
319 const std::vector<int64_t> &inner_serial_loop_extents,
320 const Sites &consumer_site,
321 ScheduleFeatures &feat,
322 const LoopNest *parent,
323 const LoopNest &root,
324 GlobalMemInfo &global_mem_loads,
325 SharedMemInfo &shared_mem_loads,
326 LocalMemInfo &local_mem_loads,
327 bool verbose = false) const;
328
329 bool can_vectorize_access_for_innermost_dim(const LoadJacobian &jac,
330 const FunctionDAG::Node *accessed,
331 int innermost_dim,
332 int loop_index) const;
333
334 bool can_vectorize_store_access(const LoadJacobian &jac,
335 const FunctionDAG::Node *accessed,
336 bool accessed_has_been_scheduled,
337 int innermost_dim,
338 int loop_index,
339 const GPUMemoryType &mem_type) const;
340
341 int vectorized_load_access_size(const LoadJacobian &jac,
342 const FunctionDAG::Node *accessed,
343 bool accessed_has_been_scheduled,
344 int innermost_dim,
345 const GPUMemoryType &mem_type,
346 bool verbose = false) const;
347
348 int vectorized_access_size(size_t loop_index,
349 bool verbose = false) const;
350
351 template<typename T>
352 void compute_num_mem_accesses_per_block(const LoadJacobian &jac,
353 const FunctionDAG::Node *node,
354 const Bound &store_bounds,
355 const ThreadInfo *thread_info,
356 int innermost_dim,
357 double num_requests_per_warp,
358 MemInfoType<T> &mem_info,
359 bool verbose = false) const;
360
361 std::pair<double, double> compute_local_mem_store_features(const LoadJacobian &jac,
362 int consumer_innermost_dim,
363 const FunctionDAG::Node *node,
364 const Bound &consumer_store_bounds,
365 const LoopNest &root,
366 double serial_loop_extents) const;
367
368 template<typename T>
369 MemInfoType<T> compute_mem_store_info(const LoadJacobian &jac,
370 int consumer_innermost_dim,
371 const FunctionDAG::Node *node,
372 const Bound &consumer_store_bounds,
373 const ThreadInfo *thread_info,
374 double serial_loop_extents,
375 bool verbose) const;
376
377 template<typename T>
378 void compute_mem_load_features(const LoadJacobian &jac,
379 int producer_innermost_dim,
380 const FunctionDAG::Node *node,
381 const Bound &producer_store_bounds,
382 bool producer_has_been_scheduled,
383 const ThreadInfo *thread_info,
384 MemInfoType<T> &mem_info,
385 double serial_loop_extents,
386 bool verbose = false) const;
387
388 double compute_local_mem_stride(double stride,
389 double bytes) const;
390
391 // Assumes block, serial, thread or block, thread nesting
392 const LoopNest *get_enclosing_block(const LoopNest *parent,
393 const LoopNest *grandparent) const;
394
395 std::pair<int64_t, int64_t> get_block_and_serial_extents(const LoopNest *block) const;
396
397 bool all_paths_to_leaves_have_thread_loop() const;
398
399 bool has_thread_loop_descendant() const;
400
401 void compute_warp_features(ScheduleFeatures &features,
402 const GPULoopInfo &gpu_loop_info) const;
403
404 // Assume that when a block is active, all its warps are active
405 void compute_warp_and_block_occupancy(const Anderson2021Params &params,
406 ScheduleFeatures &feat,
407 const GPULoopInfo &gpu_loop_info) const;
408
409 void compute_shared_mem_occupancy(const Anderson2021Params &params,
410 const Target &target,
411 int64_t total_shared_mem_alloc_size,
412 ScheduleFeatures &feat) const;
413
414 std::pair<const LoopNest *, const LoopNest *> find_innermost_and_parent() const;
415
416 int64_t points_accessed_per_thread(const Anderson2021Params &params,
417 const Target &target,
418 const GPULoopInfo &gpu_loop_info,
419 const std::vector<const FunctionDAG::Edge *> &edge_chain,
420 const LoadJacobian &jac,
421 const LoopNest *parent,
422 const LoopNest *grandparent,
423 int64_t n,
424 const ScheduleFeatures &feat,
425 const LoadJacobian &serial_jac,
426 bool producer_has_been_scheduled,
427 int producer_innermost_dim,
428 const GPUMemoryType &mem_type,
429 bool verbose) const;
430
431 int64_t compute_licm_amortization(const LoopNest *innermost,
432 const LoopNest *parent,
433 const ScheduleFeatures &feat,
434 const LoadJacobian &jac,
435 int producer_dims) const;
436
437 void memoize_points_computed_minimum(StageMap<ScheduleFeatures> &memoized_features,
438 const StageMap<ScheduleFeatures> *features) const;
439
440 vector<pair<int, int>> collect_producers(const StageMap<Sites> &sites) const;
441
442 uint64_t compute_hash_of_producers_stored_at_root(const StageMap<Sites> &sites) const;
443
444 void collect_stages(std::set<const FunctionDAG::Node::Stage *> &stages) const;
445
446 void memoize_features(StageMap<ScheduleFeatures> &memoized_features,
447 const StageMap<ScheduleFeatures> *features) const;
448
449 void compute_working_set_from_features(int64_t *working_set,
450 const StageMap<ScheduleFeatures> *features) const;
451
452 void recompute_inlined_features(const StageMap<Sites> &sites,
453 StageMap<ScheduleFeatures> *features) const;
454
455 std::pair<int64_t, bool> compute_alloc_size_of_node_here(const FunctionDAG::Node *f) const;
456
457 // Do a recursive walk over the loop nest computing features to feed the cost model.
458 void compute_features(const FunctionDAG &dag,
459 const Anderson2021Params &params,
460 const Target &target,
461 const StageMap<Sites> &sites,
462 int64_t instances,
463 int64_t parallelism,
464 const LoopNest *parent,
465 const LoopNest *grandparent,
466 const LoopNest &root,
467 GPULoopInfo gpu_loop_info,
468 bool use_memoized_features,
469 const StageMap<int64_t> &total_shared_mem_alloc_sizes,
470 int64_t *working_set,
471 int64_t *working_set_local_constant,
472 int64_t *working_set_local_dynamic,
473 StageMap<ScheduleFeatures> *features,
474 Statistics &stats,
475 bool verbose = false) const;
476
477 bool is_root() const {
478 // The root is the sole node without a Func associated with
479 // it.
480 return node == nullptr;
481 }
482
483 // Set the region required of a Func at this site.
484 const Bound &set_bounds(const FunctionDAG::Node *f, BoundContents *b) const {
485 return bounds.emplace(f, b);
486 }
487
488 // Get the region required of a Func at this site, from which we
489 // know what region would be computed if it were scheduled here,
490 // and what its loop nest would be.
491 const Bound &get_bounds(const FunctionDAG::Node *f) const;
492
493 // Get the region required of a Func at this site (but only to satisfy the
494 // consumers along the given edge chain), from which we know what region
495 // would be computed if it were scheduled here and what its loop nest
496 // would be.
497 Bound get_bounds_along_edge_chain(const FunctionDAG::Node *f,
498 const vector<const FunctionDAG::Edge *> &edge_chain) const;
499
500 void dump() const;
501
502 std::string to_string() const;
503
504 // Recursively print a loop nest representation to stderr
505 template<typename T>
506 void dump(T &stream, string prefix, const LoopNest *parent) const;
507
508 // Does this loop nest access the given Func
509 bool calls(const FunctionDAG::Node *f) const;
510
511 // What is the maximum number of inlined calls to a Func that
512 // occur within this loop. Used to prune states that would
513 // generate too much code.
514 int64_t max_inlined_calls() const;
515
516 // Does this loop nest access an input buffer? Used to select
517 // trail strategies when splitting loops. We don't want to read
518 // out of bounds on inputs, even if we don't intend to use the
519 // values read. It could create annoying assertion failures for
520 // the user. It's OK to read out of range of the values computed
521 // on internal Funcs though. Allocation bounds inference just pads
522 // out the bounds so that it won't fault.
523 bool accesses_input_buffer() const;
524
525 // Does this loop nest contain a computation of the given Func.
526 bool computes(const FunctionDAG::Node *f) const;
527
528 // Above here most methods query the loop nest. Below we have
529 // methods that mutate the loop nest.
530
531 // Inline a Func into all consumers within this loop.
532 void inline_func(const FunctionDAG::Node *f);
533
534 // Compute a Func at this site.
535 bool compute_here(const FunctionDAG::Node *f,
536 bool tileable,
537 int v,
538 bool in_threads_loop,
539 const Anderson2021Params &params,
540 const Target &target);
541
542 // Parallelize this loop according to the given tiling.
543 IntrusivePtr<const LoopNest> parallelize_in_tiles(const vector<int64_t> &tiling,
544 const LoopNest *parent,
545 const Anderson2021Params &params,
546 const Target &target,
547 bool inner_tiling,
548 bool adjust_tiling,
549 bool move_all_rvars_inward = true,
550 const vector<int> &rvars_to_move_inward = {}) const;
551
552 int64_t get_total_local_mem_alloc_size(bool constant_allocs_only = false,
553 bool in_threads_loop = false) const;
554 int64_t get_total_constant_local_mem_alloc_size() const;
555
556 // All store ats further in than the block level must be fixed
557 // sized allocations. This method checks if f will require a dynamic
558 // allocation
559 bool requires_dynamic_allocation(const FunctionDAG::Node *f,
560 const Target &target,
561 bool in_threads_loop) const;
562
563 // Return all possible ways to compute f in tiles somewhere within
564 // this loop nest.
565 // in_threads_loop tracks whether or not function is going to be placed inside a
566 // loop marked gpu_threads, in which case f's loops cannot be gpu_threads
567 vector<IntrusivePtr<const LoopNest>> compute_in_tiles(const FunctionDAG::Node *f,
568 const LoopNest *parent,
569 const Anderson2021Params &params,
570 const Target &target,
571 const SearchSpaceOptions &search_space_options,
572 int v,
573 bool in_realization,
574 bool in_threads_loop,
575 bool is_pre_pass,
576 vector<int64_t> union_counts = vector<int64_t>()) const;
577
578 // Below here we have methods that apply a schedule to a Halide pipeline.
579
580 // A model of the state of the loop nest of a Func while applying
581 // Halide's scheduling directives.
582
583 // Note that StageScheduleState is movable-but-not-copyable thanks to its ostringstream member.
584 struct StageScheduleState {
585 // How much parallelism do we need to exploit with this Func?
586 double num_cores = 0;
587
588 // Which storage dimension is vectorized? We need to reorder it innermost
589 int vector_dim = -1;
590 int vectorized_loop_index = -1;
591
592 // The various Vars and RVars used for scheduling a Func.
593 struct FuncVar {
594 // The top-level var or rvar this was split off from
595 VarOrRVar orig;
596
597 // This var.
598 VarOrRVar var;
599
600 // Source code to access this Var/RVar. Used for printing
601 // valid Halide source for this schedule.
602 string accessor;
603
604 // Our estimate of the extent of this var. This is exact
605 // when constant_extent flag is true.
606 int64_t extent = 0;
607
608 // Which index in the symbolic loop nest does this var
609 // belong to.
610 size_t index = 0;
611
612 // Some flags.
613 bool innermost_pure_dim = false;
614 bool outermost = false;
615 bool parallel = false;
616 bool exists = false;
617 bool pure = false;
618 bool constant_extent = false;
619
620 bool vectorized = false;
621 bool gpu_threads = false;
622
623 FuncVar()
624 : orig(Var()),
625 var(Var()) {
626 }
627 };
628 const FunctionDAG::Node *node;
629 const FunctionDAG::Node::Stage *stage;
630 bool parallel = false;
631 bool vectorized = false;
632 bool all_innermost_unrolled = false;
633 FuncVar vectorized_var;
634
635 // In order from innermost to outermost. Each group of d is one tiling level.
636 vector<FuncVar> vars;
637
638 // In order from innermost to outermost. Each group of d is one tiling level.
639 vector<FuncVar> ordered_vars;
640 vector<int64_t> gpu_thread_extents;
641
642 NodeMap<std::vector<std::pair<const LoopNest *, std::vector<const FunctionDAG::Edge *>>>>
643 producers_to_be_staged;
644
645 // From outermost in
646 vector<StageScheduleState *> ancestors;
647
648 std::ostringstream schedule_source;
649 };
650
651 bool has_constant_region_computed(const FunctionDAG::Node *node) const;
652 bool has_constant_region_required(const FunctionDAG::Node *node) const;
653 bool other_stage_has_same_producer(const FunctionDAG::Node *producer) const;
654 int num_serial_loops(const FunctionDAG::Node::Stage *stage) const;
655 int num_serial_loops() const;
656 bool producer_computed_here_or_further_in(const FunctionDAG::Node *producer) const;
657
658 void update_producers_to_be_staged(StageScheduleState &state,
659 const NodeMap<bool> &all_inlined) const;
660 bool region_computed_shrinks(const FunctionDAG::Node *f,
661 const LoopNest *parent) const;
662
663 // Apply the schedule represented by this loop nest to a Halide pipeline.
664 void apply(LoopLevel here,
665 StageMap<std::unique_ptr<StageScheduleState>> &state_map,
666 double num_cores,
667 int depth,
668 const LoopNest *parent,
669 const LoopNest *compute_site,
670 const Target &target,
671 std::vector<StageScheduleState *> &ancestors,
672 const NodeMap<bool> &all_inlined) const;
673
674 double max_idle_lane_wastage(const Target &target,
675 GPULoopInfo gpu_loop_info) const;
676
677 bool has_valid_thread_extents() const;
678
679 void collect_nodes_that_should_be_inlined(const NodeMap<bool> &nodes_to_freeze,
680 NodeMap<bool> &inlined_nodes) const;
681
682 void collect_all_inlined(NodeMap<bool> &all_inlined) const;
683
684 int64_t product_of_self_and_descendants(int loop_index) const;
685 int64_t product_of_descendants(int loop_index) const;
686
687 void get_stages_computed_in_each_compute_root_loop(StageMap<StageMap<bool>> &descendants,
688 const LoopNest *compute_root_loop_nest = nullptr) const;
689};
690
691 struct Filter {
692 const LoopNest *loop_nest;
693 bool logging = false;
694
695 explicit Filter(const LoopNest *loop_nest)
696 : loop_nest{loop_nest},
697 logging{enable_filter_printing()} {
698 if (logging) {
699 std::cerr << "\nState filtered: \n";
700 loop_nest->dump();
701 std::cerr << "Reason: ";
702 }
703 }
704
705 template<typename T>
706 Filter &operator<<(T &&x) {
707 if (logging) {
708 std::cerr << std::forward<T>(x);
709 }
710 return *this;
711 }
712
713 static bool enable_filter_printing();
714};
715
716} // namespace Autoscheduler
717} // namespace Internal
718} // namespace Halide
719
720#endif // LOOP_NEST_H
ASLog.h
GPULoopInfo.h
Data structure containing information about the current GPU loop nest hierarchy of blocks,...
GPUMemInfo.h
Data structures that help track memory access information.
PerfectHashMap.h
SearchSpaceOptions.h
Statistics.h
ThreadInfo.h
Data structure containing information about GPU threads for a particular location in the loop nest an...
Tiling.h
CostModel.h
FunctionDAG.h
Halide::Internal::Autoscheduler::LoadJacobian
Definition: FunctionDAG.h:126
Halide::Internal::RefCount
A class representing a reference count to be used with IntrusivePtr.
Definition: IntrusivePtr.h:19
Halide::LoopLevel
A reference to a site in a Halide statement at the top of the body of a particular for loop.
Definition: Schedule.h:203
Halide::Var
A Halide variable, to be used when defining functions.
Definition: Var.h:19
PerfectHashMap
Definition: PerfectHashMap.h:38
Halide::Internal::Autoscheduler::get_active_block_hardware_limit
int64_t get_active_block_hardware_limit(const Anderson2021Params &params)
Halide::Internal::Autoscheduler::all
bool all(const vector< int > &v)
Halide::Internal::Autoscheduler::are_valid_thread_extents
bool are_valid_thread_extents(const vector< int64_t > &counts)
Halide::Internal::Autoscheduler::in_range_zero_one
bool in_range_zero_one(double x)
Halide::Internal::Autoscheduler::accessed_at_constant_indices
bool accessed_at_constant_indices(const std::vector< int > &unrolled, const FunctionDAG::Edge *e)
Halide::Internal::Autoscheduler::get_register_mem_alloc_limit
constexpr int64_t get_register_mem_alloc_limit()
Definition: LoopNest.h:62
Halide::Internal::Autoscheduler::StageMap
PerfectHashMap< FunctionDAG::Node::Stage, T > StageMap
Definition: LoopNest.h:24
Halide::Internal::Autoscheduler::get_idle_lane_wastage_limit
double get_idle_lane_wastage_limit()
Halide::Internal::Autoscheduler::NodeMap
PerfectHashMap< FunctionDAG::Node, T > NodeMap
Definition: LoopNest.h:21
Halide::Internal::Autoscheduler::get_shared_memory_sm_limit
int64_t get_shared_memory_sm_limit(const Anderson2021Params &params)
Halide::Internal::Autoscheduler::get_active_warp_hardware_limit
int64_t get_active_warp_hardware_limit(const Anderson2021Params &params)
Halide::Internal::Autoscheduler::may_subtile
bool may_subtile(const Anderson2021Params &params)
Halide::Internal::Autoscheduler::get_idle_lane_wastage_limit_env_var
double get_idle_lane_wastage_limit_env_var()
Halide::Internal::Autoscheduler::get_unroll_limit
int get_unroll_limit(const Target &target)
Halide::Internal::Autoscheduler::GPUMemoryType
GPUMemoryType
Definition: LoopNest.h:44
Halide::Internal::Autoscheduler::GPUMemoryType::Global
@ Global
Halide::Internal::Autoscheduler::GPUMemoryType::Local
@ Local
Halide::Internal::Autoscheduler::GPUMemoryType::Shared
@ Shared
Halide::Internal::Autoscheduler::GPUMemoryType::Registers
@ Registers
Halide::Internal::Autoscheduler::GPUMemoryType::Inlined
@ Inlined
Halide::Internal::Autoscheduler::get_shared_memory_limit
int64_t get_shared_memory_limit(const Anderson2021Params &params)
Halide::Internal::Autoscheduler::stringify
std::string stringify(GPU_parallelism label)
Halide::Internal::Autoscheduler::GPU_parallelism
GPU_parallelism
Definition: LoopNest.h:32
Halide::Internal::Autoscheduler::GPU_parallelism::Parallelized
@ Parallelized
Halide::Internal::Autoscheduler::GPU_parallelism::Serial
@ Serial
Halide::Internal::Autoscheduler::GPU_parallelism::None
@ None
Halide::Internal::Autoscheduler::GPU_parallelism::Thread
@ Thread
Halide::Internal::Autoscheduler::GPU_parallelism::Simd
@ Simd
Halide::Internal::Autoscheduler::GPU_parallelism::Block
@ Block
Halide
This file defines the class FunctionDAG, which is our representation of a Halide pipeline,...
Definition: AbstractGenerator.h:19
Halide::LinkageType::Internal
@ Internal
Not visible externally, similar to 'static' linkage in C.
uint64_t
unsigned __INT64_TYPE__ uint64_t
Definition: runtime_internal.h:23
int64_t
signed __INT64_TYPE__ int64_t
Definition: runtime_internal.h:22
Halide::Internal::Autoscheduler::Anderson2021Params
Definition: CostModel.h:18
Halide::Internal::Autoscheduler::BoundContents
Definition: FunctionDAG.h:274
Halide::Internal::Autoscheduler::Filter
Definition: LoopNest.h:691
Halide::Internal::Autoscheduler::Filter::loop_nest
const LoopNest * loop_nest
Definition: LoopNest.h:692
Halide::Internal::Autoscheduler::Filter::Filter
Filter(const LoopNest *loop_nest)
Definition: LoopNest.h:695
Halide::Internal::Autoscheduler::Filter::operator<<
Filter & operator<<(T &&x)
Definition: LoopNest.h:706
Halide::Internal::Autoscheduler::Filter::enable_filter_printing
static bool enable_filter_printing()
Halide::Internal::Autoscheduler::Filter::logging
bool logging
Definition: LoopNest.h:693
Halide::Internal::Autoscheduler::FunctionDAG::Edge
Definition: FunctionDAG.h:526
Halide::Internal::Autoscheduler::FunctionDAG::Node::Stage
Definition: FunctionDAG.h:448
Halide::Internal::Autoscheduler::FunctionDAG::Node
Definition: FunctionDAG.h:378
Halide::Internal::Autoscheduler::FunctionDAG
Definition: FunctionDAG.h:367
Halide::Internal::Autoscheduler::GPULoopInfo
Definition: GPULoopInfo.h:22
Halide::Internal::Autoscheduler::LoopNest::FeatureIntermediates
Definition: LoopNest.h:133
Halide::Internal::Autoscheduler::LoopNest::FeatureIntermediates::points_computed_per_thread
double points_computed_per_thread
Definition: LoopNest.h:142
Halide::Internal::Autoscheduler::LoopNest::FeatureIntermediates::outer_parallelism
double outer_parallelism
Definition: LoopNest.h:139
Halide::Internal::Autoscheduler::LoopNest::FeatureIntermediates::num_warps_per_block
double num_warps_per_block
Definition: LoopNest.h:140
Halide::Internal::Autoscheduler::LoopNest::FeatureIntermediates::num_vectors
double num_vectors
Definition: LoopNest.h:135
Halide::Internal::Autoscheduler::LoopNest::FeatureIntermediates::innermost_pure_loop_extent
double innermost_pure_loop_extent
Definition: LoopNest.h:138
Halide::Internal::Autoscheduler::LoopNest::FeatureIntermediates::num_scalars
double num_scalars
Definition: LoopNest.h:136
Halide::Internal::Autoscheduler::LoopNest::FeatureIntermediates::num_threads_per_block
double num_threads_per_block
Definition: LoopNest.h:141
Halide::Internal::Autoscheduler::LoopNest::FeatureIntermediates::vector_size
double vector_size
Definition: LoopNest.h:137
Halide::Internal::Autoscheduler::LoopNest::FeatureIntermediates::inlined_calls
double inlined_calls
Definition: LoopNest.h:134
Halide::Internal::Autoscheduler::LoopNest::Sites
Definition: LoopNest.h:100
Halide::Internal::Autoscheduler::LoopNest::Sites::hash_of_producers_stored_at_root
uint64_t hash_of_producers_stored_at_root
Definition: LoopNest.h:109
Halide::Internal::Autoscheduler::LoopNest::Sites::is_stored_in_registers
bool is_stored_in_registers() const
Definition: LoopNest.h:238
Halide::Internal::Autoscheduler::LoopNest::Sites::task
const LoopNest * task
Definition: LoopNest.h:105
Halide::Internal::Autoscheduler::LoopNest::Sites::innermost
const LoopNest * innermost
Definition: LoopNest.h:104
Halide::Internal::Autoscheduler::LoopNest::Sites::is_stored_in_shared_mem
bool is_stored_in_shared_mem() const
Definition: LoopNest.h:232
Halide::Internal::Autoscheduler::LoopNest::Sites::thread
const LoopNest * thread
Definition: LoopNest.h:220
Halide::Internal::Autoscheduler::LoopNest::Sites::is_stored_in_local_mem
bool is_stored_in_local_mem() const
Definition: LoopNest.h:235
Halide::Internal::Autoscheduler::LoopNest::Sites::allocation_size
int64_t allocation_size
Definition: LoopNest.h:222
Halide::Internal::Autoscheduler::LoopNest::Sites::store
const LoopNest * store
Definition: LoopNest.h:102
Halide::Internal::Autoscheduler::LoopNest::Sites::gpu_store_memory_type
GPUMemoryType gpu_store_memory_type
Definition: LoopNest.h:221
Halide::Internal::Autoscheduler::LoopNest::Sites::inlined_innermosts
std::vector< const LoopNest * > inlined_innermosts
Definition: LoopNest.h:226
Halide::Internal::Autoscheduler::LoopNest::Sites::produce
const LoopNest * produce
Definition: LoopNest.h:103
Halide::Internal::Autoscheduler::LoopNest::Sites::num_realizations
int64_t num_realizations
Definition: LoopNest.h:224
Halide::Internal::Autoscheduler::LoopNest::Sites::inlined
bool inlined
Definition: LoopNest.h:106
Halide::Internal::Autoscheduler::LoopNest::Sites::compute
const LoopNest * compute
Definition: LoopNest.h:101
Halide::Internal::Autoscheduler::LoopNest::Sites::is_stored_in_global_mem
bool is_stored_in_global_mem() const
Definition: LoopNest.h:229
Halide::Internal::Autoscheduler::LoopNest::Sites::is_constant_allocation
bool is_constant_allocation
Definition: LoopNest.h:223
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar
Definition: LoopNest.h:218
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::FuncVar
FuncVar()
Definition: LoopNest.h:623
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::innermost_pure_dim
bool innermost_pure_dim
Definition: LoopNest.h:238
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::index
size_t index
Definition: LoopNest.h:235
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::pure
bool pure
Definition: LoopNest.h:242
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::orig
VarOrRVar orig
Definition: LoopNest.h:220
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::constant_extent
bool constant_extent
Definition: LoopNest.h:243
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::parallel
bool parallel
Definition: LoopNest.h:240
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::exists
bool exists
Definition: LoopNest.h:241
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::outermost
bool outermost
Definition: LoopNest.h:239
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::gpu_threads
bool gpu_threads
Definition: LoopNest.h:621
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::var
VarOrRVar var
Definition: LoopNest.h:223
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::extent
int64_t extent
Definition: LoopNest.h:231
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::vectorized
bool vectorized
Definition: LoopNest.h:620
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::FuncVar::accessor
string accessor
Definition: LoopNest.h:227
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState
Definition: LoopNest.h:209
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::num_cores
double num_cores
Definition: LoopNest.h:211
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::ancestors
vector< StageScheduleState * > ancestors
Definition: LoopNest.h:646
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::node
const FunctionDAG::Node * node
Definition: LoopNest.h:628
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::parallel
bool parallel
Definition: LoopNest.h:630
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::vectorized
bool vectorized
Definition: LoopNest.h:631
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::vars
vector< FuncVar > vars
Definition: LoopNest.h:636
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::vector_dim
int vector_dim
Definition: LoopNest.h:214
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::vectorized_loop_index
int vectorized_loop_index
Definition: LoopNest.h:215
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::gpu_thread_extents
vector< int64_t > gpu_thread_extents
Definition: LoopNest.h:640
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::all_innermost_unrolled
bool all_innermost_unrolled
Definition: LoopNest.h:632
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::ordered_vars
vector< FuncVar > ordered_vars
Definition: LoopNest.h:639
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::stage
const FunctionDAG::Node::Stage * stage
Definition: LoopNest.h:629
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::schedule_source
std::ostringstream schedule_source
Definition: LoopNest.h:252
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::producers_to_be_staged
NodeMap< std::vector< std::pair< const LoopNest *, std::vector< const FunctionDAG::Edge * > > > > producers_to_be_staged
Definition: LoopNest.h:643
Halide::Internal::Autoscheduler::LoopNest::StageScheduleState::vectorized_var
FuncVar vectorized_var
Definition: LoopNest.h:633
Halide::Internal::Autoscheduler::LoopNest
Definition: LoopNest.h:34
Halide::Internal::Autoscheduler::LoopNest::collect_producers
vector< pair< int, int > > collect_producers(const StageMap< Sites > &sites) const
Halide::Internal::Autoscheduler::LoopNest::is_gpu_thread
bool is_gpu_thread(const Target &target) const
Definition: LoopNest.h:152
Halide::Internal::Autoscheduler::LoopNest::compute_in_tiles
vector< IntrusivePtr< const LoopNest > > compute_in_tiles(const FunctionDAG::Node *f, const LoopNest *parent, const Anderson2021Params &params, const Target &target, const SearchSpaceOptions &search_space_options, int v, bool in_realization, bool in_threads_loop, bool is_pre_pass, vector< int64_t > union_counts=vector< int64_t >()) const
Halide::Internal::Autoscheduler::LoopNest::vectorized_loop_index
int vectorized_loop_index
Definition: LoopNest.h:75
Halide::Internal::Autoscheduler::LoopNest::is_root
bool is_root() const
Definition: LoopNest.h:477
Halide::Internal::Autoscheduler::LoopNest::get_enclosing_block
const LoopNest * get_enclosing_block(const LoopNest *parent, const LoopNest *grandparent) const
Halide::Internal::Autoscheduler::LoopNest::is_scalar
bool is_scalar() const
Definition: LoopNest.h:160
Halide::Internal::Autoscheduler::LoopNest::num_serial_loops
int num_serial_loops(const FunctionDAG::Node::Stage *stage) const
Halide::Internal::Autoscheduler::LoopNest::points_accessed_per_thread
int64_t points_accessed_per_thread(const Anderson2021Params &params, const Target &target, const GPULoopInfo &gpu_loop_info, const std::vector< const FunctionDAG::Edge * > &edge_chain, const LoadJacobian &jac, const LoopNest *parent, const LoopNest *grandparent, int64_t n, const ScheduleFeatures &feat, const LoadJacobian &serial_jac, bool producer_has_been_scheduled, int producer_innermost_dim, const GPUMemoryType &mem_type, bool verbose) const
Halide::Internal::Autoscheduler::LoopNest::has_constant_region_required
bool has_constant_region_required(const FunctionDAG::Node *node) const
Halide::Internal::Autoscheduler::LoopNest::num_serial_loops
int num_serial_loops() const
Halide::Internal::Autoscheduler::LoopNest::features
std::map< uint64_t, StageMap< ScheduleFeatures > > features
Definition: LoopNest.h:146
Halide::Internal::Autoscheduler::LoopNest::get_pure_stage_vectorized_loop_index
int get_pure_stage_vectorized_loop_index(const FunctionDAG::Node *node) const
Halide::Internal::Autoscheduler::LoopNest::node
const FunctionDAG::Node * node
Definition: LoopNest.h:57
Halide::Internal::Autoscheduler::LoopNest::dump
void dump(T &stream, string prefix, const LoopNest *parent) const
Halide::Internal::Autoscheduler::LoopNest::product_of_self_and_descendants
int64_t product_of_self_and_descendants(int loop_index) const
Halide::Internal::Autoscheduler::LoopNest::gpu_label
GPU_parallelism gpu_label
Definition: LoopNest.h:131
Halide::Internal::Autoscheduler::LoopNest::all_strides_exist
bool all_strides_exist(const LoadJacobian &jac, const FunctionDAG::Node *storage_node, const LoopNest &root) const
Halide::Internal::Autoscheduler::LoopNest::recompute_inlined_features
void recompute_inlined_features(const StageMap< Sites > &sites, StageMap< ScheduleFeatures > *features) const
Halide::Internal::Autoscheduler::LoopNest::inline_func
void inline_func(const FunctionDAG::Node *f)
Halide::Internal::Autoscheduler::LoopNest::generate_vec_dim_serial_tilings
void generate_vec_dim_serial_tilings(vector< int > &serial_sizes) const
Halide::Internal::Autoscheduler::LoopNest::region_computed_shrinks
bool region_computed_shrinks(const FunctionDAG::Node *f, const LoopNest *parent) const
Halide::Internal::Autoscheduler::LoopNest::compute_gpu_store_features
void compute_gpu_store_features(const LoadJacobian &jac, int consumer_innermost_dim, const FunctionDAG::Node *node, const Bound &consumer_store_bounds, const GPULoopInfo &gpu_loop_info, const std::vector< int64_t > &inner_serial_loop_extents, const Sites &consumer_site, ScheduleFeatures &feat, const LoopNest *parent, const LoopNest &root, GlobalMemInfo &global_mem_loads, SharedMemInfo &shared_mem_loads, LocalMemInfo &local_mem_loads, bool verbose=false) const
Halide::Internal::Autoscheduler::LoopNest::compute_licm_amortization
int64_t compute_licm_amortization(const LoopNest *innermost, const LoopNest *parent, const ScheduleFeatures &feat, const LoadJacobian &jac, int producer_dims) const
Halide::Internal::Autoscheduler::LoopNest::product_of_descendants
int64_t product_of_descendants(int loop_index) const
Halide::Internal::Autoscheduler::LoopNest::requires_dynamic_allocation
bool requires_dynamic_allocation(const FunctionDAG::Node *f, const Target &target, bool in_threads_loop) const
Halide::Internal::Autoscheduler::LoopNest::is_gpu_block
bool is_gpu_block(const Target &target) const
Definition: LoopNest.h:156
Halide::Internal::Autoscheduler::LoopNest::node_has_dynamic_region_computed
bool node_has_dynamic_region_computed(const FunctionDAG::Node *f) const
Halide::Internal::Autoscheduler::LoopNest::exceeds_serial_extents_limit
bool exceeds_serial_extents_limit(const Target &target, const LoopNest *parent, bool in_threads_loop) const
Halide::Internal::Autoscheduler::LoopNest::collect_stages
void collect_stages(std::set< const FunctionDAG::Node::Stage * > &stages) const
Halide::Internal::Autoscheduler::LoopNest::accesses_input_buffer
bool accesses_input_buffer() const
Halide::Internal::Autoscheduler::LoopNest::size
std::vector< int64_t > size
Definition: LoopNest.h:39
Halide::Internal::Autoscheduler::LoopNest::get_bounds_along_edge_chain
Bound get_bounds_along_edge_chain(const FunctionDAG::Node *f, const vector< const FunctionDAG::Edge * > &edge_chain) const
Halide::Internal::Autoscheduler::LoopNest::get_total_constant_local_mem_alloc_size
int64_t get_total_constant_local_mem_alloc_size() const
Halide::Internal::Autoscheduler::LoopNest::get_bounds
const Bound & get_bounds(const FunctionDAG::Node *f) const
Halide::Internal::Autoscheduler::LoopNest::compute_local_mem_store_features
std::pair< double, double > compute_local_mem_store_features(const LoadJacobian &jac, int consumer_innermost_dim, const FunctionDAG::Node *node, const Bound &consumer_store_bounds, const LoopNest &root, double serial_loop_extents) const
Halide::Internal::Autoscheduler::LoopNest::vectorized_load_access_size
int vectorized_load_access_size(const LoadJacobian &jac, const FunctionDAG::Node *accessed, bool accessed_has_been_scheduled, int innermost_dim, const GPUMemoryType &mem_type, bool verbose=false) const
Halide::Internal::Autoscheduler::LoopNest::all_paths_to_leaves_have_thread_loop
bool all_paths_to_leaves_have_thread_loop() const
Halide::Internal::Autoscheduler::LoopNest::get_gpu_memory_type
GPUMemoryType get_gpu_memory_type(bool in_block, bool in_thread, bool is_inlined=false) const
Halide::Internal::Autoscheduler::LoopNest::compute_warp_and_block_occupancy
void compute_warp_and_block_occupancy(const Anderson2021Params &params, ScheduleFeatures &feat, const GPULoopInfo &gpu_loop_info) const
Halide::Internal::Autoscheduler::LoopNest::get_union_thread_counts
vector< int64_t > get_union_thread_counts(const FunctionDAG::Node *f) const
Halide::Internal::Autoscheduler::LoopNest::vector_dim
int vector_dim
Definition: LoopNest.h:72
Halide::Internal::Autoscheduler::LoopNest::collect_nodes_that_should_be_inlined
void collect_nodes_that_should_be_inlined(const NodeMap< bool > &nodes_to_freeze, NodeMap< bool > &inlined_nodes) const
Halide::Internal::Autoscheduler::LoopNest::has_valid_thread_extents
bool has_valid_thread_extents() const
Halide::Internal::Autoscheduler::LoopNest::apply
void apply(LoopLevel here, StageMap< std::unique_ptr< StageScheduleState > > &state_map, double num_cores, int depth, const LoopNest *parent, const LoopNest *compute_site, const Target &target, std::vector< StageScheduleState * > &ancestors, const NodeMap< bool > &all_inlined) const
Halide::Internal::Autoscheduler::LoopNest::feature_intermediates
std::map< uint64_t, StageMap< StageMap< FeatureIntermediates > > > feature_intermediates
Definition: LoopNest.h:145
Halide::Internal::Autoscheduler::LoopNest::get_actual_vector_dim
int get_actual_vector_dim(const Bound &store_bounds) const
Halide::Internal::Autoscheduler::LoopNest::compute_shared_mem_occupancy
void compute_shared_mem_occupancy(const Anderson2021Params &params, const Target &target, int64_t total_shared_mem_alloc_size, ScheduleFeatures &feat) const
Halide::Internal::Autoscheduler::LoopNest::compute_strides
Strides compute_strides(const LoadJacobian &jac, int innermost_storage_dim, const FunctionDAG::Node *storage_node, const Bound &store_bounds, const ThreadInfo *thread_info, bool verbose=false) const
Halide::Internal::Autoscheduler::LoopNest::get_vectorized_loop_index_from_pure_stage
int get_vectorized_loop_index_from_pure_stage(const LoopNest &root) const
Halide::Internal::Autoscheduler::LoopNest::computes
bool computes(const FunctionDAG::Node *f) const
Halide::Internal::Autoscheduler::LoopNest::storage_stride
double storage_stride(const LoadJacobian &jac, int innermost_storage_dim, const FunctionDAG::Node *storage_node, const Bound &store_bounds, const LoopNest &root) const
Halide::Internal::Autoscheduler::LoopNest::tileable
bool tileable
Definition: LoopNest.h:66
Halide::Internal::Autoscheduler::LoopNest::children
std::vector< IntrusivePtr< const LoopNest > > children
Definition: LoopNest.h:42
Halide::Internal::Autoscheduler::LoopNest::set_working_set_at_task_feature
void set_working_set_at_task_feature(int64_t working_set, StageMap< ScheduleFeatures > *features) const
Definition: LoopNest.h:271
Halide::Internal::Autoscheduler::LoopNest::copy_from
void copy_from(const LoopNest &n)
Halide::Internal::Autoscheduler::LoopNest::promote_allocs_to_registers
bool promote_allocs_to_registers(const Target &target, StageMap< Sites > &sites) const
Halide::Internal::Autoscheduler::LoopNest::get_block_and_serial_extents
std::pair< int64_t, int64_t > get_block_and_serial_extents(const LoopNest *block) const
Halide::Internal::Autoscheduler::LoopNest::set_bounds
const Bound & set_bounds(const FunctionDAG::Node *f, BoundContents *b) const
Definition: LoopNest.h:484
Halide::Internal::Autoscheduler::LoopNest::has_dynamic_allocation_inside_thread
bool has_dynamic_allocation_inside_thread(bool in_thread_loop) const
Halide::Internal::Autoscheduler::LoopNest::memoize_points_computed_minimum
void memoize_points_computed_minimum(StageMap< ScheduleFeatures > &memoized_features, const StageMap< ScheduleFeatures > *features) const
Halide::Internal::Autoscheduler::LoopNest::has_constant_region_computed
bool has_constant_region_computed(const FunctionDAG::Node *node) const
Halide::Internal::Autoscheduler::LoopNest::compute_local_mem_stride
double compute_local_mem_stride(double stride, double bytes) const
Halide::Internal::Autoscheduler::LoopNest::compute_mem_store_info
MemInfoType< T > compute_mem_store_info(const LoadJacobian &jac, int consumer_innermost_dim, const FunctionDAG::Node *node, const Bound &consumer_store_bounds, const ThreadInfo *thread_info, double serial_loop_extents, bool verbose) const
Halide::Internal::Autoscheduler::LoopNest::add_gpu_thread_tilings
bool add_gpu_thread_tilings(const FunctionDAG::Node *f, const Anderson2021Params &params, const Target &target, int v, vector< IntrusivePtr< const LoopNest > > &result, const vector< int64_t > &max_size)
Halide::Internal::Autoscheduler::LoopNest::parallelize_in_tiles
IntrusivePtr< const LoopNest > parallelize_in_tiles(const vector< int64_t > &tiling, const LoopNest *parent, const Anderson2021Params &params, const Target &target, bool inner_tiling, bool adjust_tiling, bool move_all_rvars_inward=true, const vector< int > &rvars_to_move_inward={}) const
Halide::Internal::Autoscheduler::LoopNest::memoize_features
void memoize_features(StageMap< ScheduleFeatures > &memoized_features, const StageMap< ScheduleFeatures > *features) const
Halide::Internal::Autoscheduler::LoopNest::collect_all_inlined
void collect_all_inlined(NodeMap< bool > &all_inlined) const
Halide::Internal::Autoscheduler::LoopNest::unrolled_loops
std::vector< int > unrolled_loops(const Target &target, const LoopNest *parent, const LoopNest *grandparent) const
Halide::Internal::Autoscheduler::LoopNest::to_string
std::string to_string() const
Halide::Internal::Autoscheduler::LoopNest::is_gpu_serial
bool is_gpu_serial(const Target &target) const
Definition: LoopNest.h:148
Halide::Internal::Autoscheduler::LoopNest::max_idle_lane_wastage
double max_idle_lane_wastage(const Target &target, GPULoopInfo gpu_loop_info) const
Halide::Internal::Autoscheduler::LoopNest::hash_combine
static void hash_combine(uint64_t &h, uint64_t next)
Definition: LoopNest.h:193
Halide::Internal::Autoscheduler::LoopNest::find_pure_stage_loop_nest
const LoopNest * find_pure_stage_loop_nest(const FunctionDAG::Node *node) const
Halide::Internal::Autoscheduler::LoopNest::dump
void dump(std::ostream &os, string prefix, const LoopNest *parent) const
Halide::Internal::Autoscheduler::LoopNest::ref_count
RefCount ref_count
Definition: LoopNest.h:35
Halide::Internal::Autoscheduler::LoopNest::bounds
NodeMap< Bound > bounds
Definition: LoopNest.h:54
Halide::Internal::Autoscheduler::LoopNest::get_stage_sizes
void get_stage_sizes(const FunctionDAG::Node *f, vector< vector< int64_t > > &stage_sizes, vector< vector< int > > &pure_dims, vector< int > &vectorized_indices) const
Halide::Internal::Autoscheduler::LoopNest::compute_hash_of_producers_stored_at_root
uint64_t compute_hash_of_producers_stored_at_root(const StageMap< Sites > &sites) const
Halide::Internal::Autoscheduler::LoopNest::max_inlined_calls
int64_t max_inlined_calls() const
Halide::Internal::Autoscheduler::LoopNest::stage
const FunctionDAG::Node::Stage * stage
Definition: LoopNest.h:60
Halide::Internal::Autoscheduler::LoopNest::innermost
bool innermost
Definition: LoopNest.h:63
Halide::Internal::Autoscheduler::LoopNest::other_stage_has_same_producer
bool other_stage_has_same_producer(const FunctionDAG::Node *producer) const
Halide::Internal::Autoscheduler::LoopNest::get_stages_computed_in_each_compute_root_loop
void get_stages_computed_in_each_compute_root_loop(StageMap< StageMap< bool > > &descendants, const LoopNest *compute_root_loop_nest=nullptr) const
Halide::Internal::Autoscheduler::LoopNest::compute_features
void compute_features(const FunctionDAG &dag, const Anderson2021Params &params, const Target &target, const StageMap< Sites > &sites, int64_t instances, int64_t parallelism, const LoopNest *parent, const LoopNest *grandparent, const LoopNest &root, GPULoopInfo gpu_loop_info, bool use_memoized_features, const StageMap< int64_t > &total_shared_mem_alloc_sizes, int64_t *working_set, int64_t *working_set_local_constant, int64_t *working_set_local_dynamic, StageMap< ScheduleFeatures > *features, Statistics &stats, bool verbose=false) const
Halide::Internal::Autoscheduler::LoopNest::get_sites
void get_sites(const Target &target, StageMap< Sites > &sites, StageMap< int64_t > &shared_mem_alloc_sizes, const LoopNest *task=nullptr, const LoopNest *parent=nullptr, const LoopNest *current_thread_loop=nullptr) const
Halide::Internal::Autoscheduler::LoopNest::parallel
bool parallel
Definition: LoopNest.h:69
Halide::Internal::Autoscheduler::LoopNest::calls
bool calls(const FunctionDAG::Node *f) const
Halide::Internal::Autoscheduler::LoopNest::producer_computed_here_or_further_in
bool producer_computed_here_or_further_in(const FunctionDAG::Node *producer) const
Halide::Internal::Autoscheduler::LoopNest::copy_from_including_features
void copy_from_including_features(const LoopNest &n)
Halide::Internal::Autoscheduler::LoopNest::can_vectorize_access_for_innermost_dim
bool can_vectorize_access_for_innermost_dim(const LoadJacobian &jac, const FunctionDAG::Node *accessed, int innermost_dim, int loop_index) const
Halide::Internal::Autoscheduler::LoopNest::update_producers_to_be_staged
void update_producers_to_be_staged(StageScheduleState &state, const NodeMap< bool > &all_inlined) const
Halide::Internal::Autoscheduler::LoopNest::has_thread_loop_descendant
bool has_thread_loop_descendant() const
Halide::Internal::Autoscheduler::LoopNest::can_vectorize_store_access
bool can_vectorize_store_access(const LoadJacobian &jac, const FunctionDAG::Node *accessed, bool accessed_has_been_scheduled, int innermost_dim, int loop_index, const GPUMemoryType &mem_type) const
Halide::Internal::Autoscheduler::LoopNest::dump
void dump() const
Halide::Internal::Autoscheduler::LoopNest::children
vector< IntrusivePtr< const LoopNest > > children
Definition: LoopNest.h:95
Halide::Internal::Autoscheduler::LoopNest::compute_mem_load_features
void compute_mem_load_features(const LoadJacobian &jac, int producer_innermost_dim, const FunctionDAG::Node *node, const Bound &producer_store_bounds, bool producer_has_been_scheduled, const ThreadInfo *thread_info, MemInfoType< T > &mem_info, double serial_loop_extents, bool verbose=false) const
Halide::Internal::Autoscheduler::LoopNest::get_allocs_that_can_be_promoted_to_registers
void get_allocs_that_can_be_promoted_to_registers(const Target &target, StageMap< Sites > &sites, NodeMap< bool > &can_be_promoted_to_registers, const LoopNest *grandparent, const LoopNest *parent) const
Halide::Internal::Autoscheduler::LoopNest::compute_warp_features
void compute_warp_features(ScheduleFeatures &features, const GPULoopInfo &gpu_loop_info) const
Halide::Internal::Autoscheduler::LoopNest::size
vector< int64_t > size
Definition: LoopNest.h:92
Halide::Internal::Autoscheduler::LoopNest::structural_hash
void structural_hash(uint64_t &h, int depth) const
Halide::Internal::Autoscheduler::LoopNest::funcs_realized_or_inlined
size_t funcs_realized_or_inlined() const
Definition: LoopNest.h:205
Halide::Internal::Autoscheduler::LoopNest::compute_num_mem_accesses_per_block
void compute_num_mem_accesses_per_block(const LoadJacobian &jac, const FunctionDAG::Node *node, const Bound &store_bounds, const ThreadInfo *thread_info, int innermost_dim, double num_requests_per_warp, MemInfoType< T > &mem_info, bool verbose=false) const
Halide::Internal::Autoscheduler::LoopNest::find_innermost_and_parent
std::pair< const LoopNest *, const LoopNest * > find_innermost_and_parent() const
Halide::Internal::Autoscheduler::LoopNest::store_at
std::set< const FunctionDAG::Node * > store_at
Definition: LoopNest.h:49
Halide::Internal::Autoscheduler::LoopNest::compute_alloc_size_of_node_here
std::pair< int64_t, bool > compute_alloc_size_of_node_here(const FunctionDAG::Node *f) const
Halide::Internal::Autoscheduler::LoopNest::compute_here
bool compute_here(const FunctionDAG::Node *f, bool tileable, int v, bool in_threads_loop, const Anderson2021Params &params, const Target &target)
Halide::Internal::Autoscheduler::LoopNest::get_total_local_mem_alloc_size
int64_t get_total_local_mem_alloc_size(bool constant_allocs_only=false, bool in_threads_loop=false) const
Halide::Internal::Autoscheduler::LoopNest::inlined
NodeMap< int64_t > inlined
Definition: LoopNest.h:46
Halide::Internal::Autoscheduler::LoopNest::compute_working_set_from_features
void compute_working_set_from_features(int64_t *working_set, const StageMap< ScheduleFeatures > *features) const
Halide::Internal::Autoscheduler::LoopNest::vectorized_access_size
int vectorized_access_size(size_t loop_index, bool verbose=false) const
Halide::Internal::Autoscheduler::MemInfo
Definition: GPUMemInfo.h:55
Halide::Internal::Autoscheduler::SearchSpaceOptions
Definition: SearchSpaceOptions.h:12
Halide::Internal::Autoscheduler::Statistics
Definition: Statistics.h:65
Halide::Internal::Autoscheduler::Strides
Definition: GPUMemInfo.h:114
Halide::Internal::Autoscheduler::ThreadInfo
Definition: ThreadInfo.h:40
Halide::Internal::Block
A sequence of statements to be executed in-order.
Definition: IR.h:452
Halide::Internal::IntrusivePtr
Intrusive shared pointers have a reference count (a RefCount object) stored in the class itself.
Definition: IntrusivePtr.h:71
Halide::Internal::ScheduleFeatures
Definition: Featurization.h:160
Halide::Target
A struct representing a target machine and os to generate code for.
Definition: Target.h:19
Halide::Target::has_gpu_feature
bool has_gpu_feature() const
Is a fully feature GPU compute runtime enabled? I.e.
Halide::VarOrRVar
A class that can represent Vars or RVars.
Definition: Func.h:29