1 //===- Schedule.cpp - Calculate an optimized schedule ---------------------===//
2 //
3 //                     The LLVM Compiler Infrastructure
4 //
5 // This file is distributed under the University of Illinois Open Source
6 // License. See LICENSE.TXT for details.
7 //
8 //===----------------------------------------------------------------------===//
9 //
10 // This pass generates an entirey new schedule tree from the data dependences
11 // and iteration domains. The new schedule tree is computed in two steps:
12 //
13 // 1) The isl scheduling optimizer is run
14 //
15 // The isl scheduling optimizer creates a new schedule tree that maximizes
16 // parallelism and tileability and minimizes data-dependence distances. The
17 // algorithm used is a modified version of the ``Pluto'' algorithm:
18 //
19 //   U. Bondhugula, A. Hartono, J. Ramanujam, and P. Sadayappan.
20 //   A Practical Automatic Polyhedral Parallelizer and Locality Optimizer.
21 //   In Proceedings of the 2008 ACM SIGPLAN Conference On Programming Language
22 //   Design and Implementation, PLDI ’08, pages 101–113. ACM, 2008.
23 //
24 // 2) A set of post-scheduling transformations is applied on the schedule tree.
25 //
26 // These optimizations include:
27 //
28 //  - Tiling of the innermost tilable bands
29 //  - Prevectorization - The coice of a possible outer loop that is strip-mined
30 //                       to the innermost level to enable inner-loop
31 //                       vectorization.
32 //  - Some optimizations for spatial locality are also planned.
33 //
34 // For a detailed description of the schedule tree itself please see section 6
35 // of:
36 //
37 // Polyhedral AST generation is more than scanning polyhedra
38 // Tobias Grosser, Sven Verdoolaege, Albert Cohen
39 // ACM Transations on Programming Languages and Systems (TOPLAS),
40 // 37(4), July 2015
41 // http://www.grosser.es/#pub-polyhedral-AST-generation
42 //
43 // This publication also contains a detailed discussion of the different options
44 // for polyhedral loop unrolling, full/partial tile separation and other uses
45 // of the schedule tree.
46 //
47 //===----------------------------------------------------------------------===//
48 
49 #include "polly/ScheduleOptimizer.h"
50 #include "polly/CodeGen/CodeGeneration.h"
51 #include "polly/DependenceInfo.h"
52 #include "polly/LinkAllPasses.h"
53 #include "polly/Options.h"
54 #include "polly/ScopInfo.h"
55 #include "polly/Support/GICHelper.h"
56 #include "llvm/Support/Debug.h"
57 #include "isl/aff.h"
58 #include "isl/band.h"
59 #include "isl/constraint.h"
60 #include "isl/map.h"
61 #include "isl/options.h"
62 #include "isl/printer.h"
63 #include "isl/schedule.h"
64 #include "isl/schedule_node.h"
65 #include "isl/space.h"
66 #include "isl/union_map.h"
67 #include "isl/union_set.h"
68 
69 using namespace llvm;
70 using namespace polly;
71 
72 #define DEBUG_TYPE "polly-opt-isl"
73 
74 static cl::opt<std::string>
75     OptimizeDeps("polly-opt-optimize-only",
76                  cl::desc("Only a certain kind of dependences (all/raw)"),
77                  cl::Hidden, cl::init("all"), cl::ZeroOrMore,
78                  cl::cat(PollyCategory));
79 
80 static cl::opt<std::string>
81     SimplifyDeps("polly-opt-simplify-deps",
82                  cl::desc("Dependences should be simplified (yes/no)"),
83                  cl::Hidden, cl::init("yes"), cl::ZeroOrMore,
84                  cl::cat(PollyCategory));
85 
86 static cl::opt<int> MaxConstantTerm(
87     "polly-opt-max-constant-term",
88     cl::desc("The maximal constant term allowed (-1 is unlimited)"), cl::Hidden,
89     cl::init(20), cl::ZeroOrMore, cl::cat(PollyCategory));
90 
91 static cl::opt<int> MaxCoefficient(
92     "polly-opt-max-coefficient",
93     cl::desc("The maximal coefficient allowed (-1 is unlimited)"), cl::Hidden,
94     cl::init(20), cl::ZeroOrMore, cl::cat(PollyCategory));
95 
96 static cl::opt<std::string> FusionStrategy(
97     "polly-opt-fusion", cl::desc("The fusion strategy to choose (min/max)"),
98     cl::Hidden, cl::init("min"), cl::ZeroOrMore, cl::cat(PollyCategory));
99 
100 static cl::opt<std::string>
101     MaximizeBandDepth("polly-opt-maximize-bands",
102                       cl::desc("Maximize the band depth (yes/no)"), cl::Hidden,
103                       cl::init("yes"), cl::ZeroOrMore, cl::cat(PollyCategory));
104 
105 static cl::opt<std::string> OuterCoincidence(
106     "polly-opt-outer-coincidence",
107     cl::desc("Try to construct schedules where the outer member of each band "
108              "satisfies the coincidence constraints (yes/no)"),
109     cl::Hidden, cl::init("no"), cl::ZeroOrMore, cl::cat(PollyCategory));
110 
111 static cl::opt<int> PrevectorWidth(
112     "polly-prevect-width",
113     cl::desc(
114         "The number of loop iterations to strip-mine for pre-vectorization"),
115     cl::Hidden, cl::init(4), cl::ZeroOrMore, cl::cat(PollyCategory));
116 
117 static cl::opt<bool> FirstLevelTiling("polly-tiling",
118                                       cl::desc("Enable loop tiling"),
119                                       cl::init(true), cl::ZeroOrMore,
120                                       cl::cat(PollyCategory));
121 
122 static cl::opt<int> FirstLevelDefaultTileSize(
123     "polly-default-tile-size",
124     cl::desc("The default tile size (if not enough were provided by"
125              " --polly-tile-sizes)"),
126     cl::Hidden, cl::init(32), cl::ZeroOrMore, cl::cat(PollyCategory));
127 
128 static cl::list<int> FirstLevelTileSizes(
129     "polly-tile-sizes", cl::desc("A tile size for each loop dimension, filled "
130                                  "with --polly-default-tile-size"),
131     cl::Hidden, cl::ZeroOrMore, cl::CommaSeparated, cl::cat(PollyCategory));
132 
133 static cl::opt<bool>
134     SecondLevelTiling("polly-2nd-level-tiling",
135                       cl::desc("Enable a 2nd level loop of loop tiling"),
136                       cl::init(false), cl::ZeroOrMore, cl::cat(PollyCategory));
137 
138 static cl::opt<int> SecondLevelDefaultTileSize(
139     "polly-2nd-level-default-tile-size",
140     cl::desc("The default 2nd-level tile size (if not enough were provided by"
141              " --polly-2nd-level-tile-sizes)"),
142     cl::Hidden, cl::init(16), cl::ZeroOrMore, cl::cat(PollyCategory));
143 
144 static cl::list<int>
145     SecondLevelTileSizes("polly-2nd-level-tile-sizes",
146                          cl::desc("A tile size for each loop dimension, filled "
147                                   "with --polly-default-tile-size"),
148                          cl::Hidden, cl::ZeroOrMore, cl::CommaSeparated,
149                          cl::cat(PollyCategory));
150 
151 static cl::opt<bool> RegisterTiling("polly-register-tiling",
152                                     cl::desc("Enable register tiling"),
153                                     cl::init(false), cl::ZeroOrMore,
154                                     cl::cat(PollyCategory));
155 
156 static cl::opt<int> RegisterDefaultTileSize(
157     "polly-register-tiling-default-tile-size",
158     cl::desc("The default register tile size (if not enough were provided by"
159              " --polly-register-tile-sizes)"),
160     cl::Hidden, cl::init(2), cl::ZeroOrMore, cl::cat(PollyCategory));
161 
162 static cl::list<int>
163     RegisterTileSizes("polly-register-tile-sizes",
164                       cl::desc("A tile size for each loop dimension, filled "
165                                "with --polly-register-tile-size"),
166                       cl::Hidden, cl::ZeroOrMore, cl::CommaSeparated,
167                       cl::cat(PollyCategory));
168 
169 /// @brief Create an isl_union_set, which describes the isolate option based
170 ///        on IsoalteDomain.
171 ///
172 /// @param IsolateDomain An isl_set whose last dimension is the only one that
173 ///                      should belong to the current band node.
174 static __isl_give isl_union_set *
175 getIsolateOptions(__isl_take isl_set *IsolateDomain) {
176   auto Dims = isl_set_dim(IsolateDomain, isl_dim_set);
177   auto *IsolateRelation = isl_map_from_domain(IsolateDomain);
178   IsolateRelation = isl_map_move_dims(IsolateRelation, isl_dim_out, 0,
179                                       isl_dim_in, Dims - 1, 1);
180   auto *IsolateOption = isl_map_wrap(IsolateRelation);
181   auto *Id = isl_id_alloc(isl_set_get_ctx(IsolateOption), "isolate", NULL);
182   return isl_union_set_from_set(isl_set_set_tuple_id(IsolateOption, Id));
183 }
184 
185 /// @brief Create an isl_union_set, which describes the atomic option for the
186 ///        dimension of the current node.
187 ///
188 /// It may help to reduce the size of generated code.
189 ///
190 /// @param Ctx An isl_ctx, which is used to create the isl_union_set.
191 static __isl_give isl_union_set *getAtomicOptions(__isl_take isl_ctx *Ctx) {
192   auto *Space = isl_space_set_alloc(Ctx, 0, 1);
193   auto *AtomicOption = isl_set_universe(Space);
194   auto *Id = isl_id_alloc(Ctx, "atomic", NULL);
195   return isl_union_set_from_set(isl_set_set_tuple_id(AtomicOption, Id));
196 }
197 
198 /// @brief Make the last dimension of Set to take values
199 ///        from 0 to VectorWidth - 1.
200 ///
201 /// @param Set         A set, which should be modified.
202 /// @param VectorWidth A parameter, which determines the constraint.
203 static __isl_give isl_set *addExtentConstraints(__isl_take isl_set *Set,
204                                                 int VectorWidth) {
205   auto Dims = isl_set_dim(Set, isl_dim_set);
206   auto Space = isl_set_get_space(Set);
207   auto *LocalSpace = isl_local_space_from_space(Space);
208   auto *ExtConstr =
209       isl_constraint_alloc_inequality(isl_local_space_copy(LocalSpace));
210   ExtConstr = isl_constraint_set_constant_si(ExtConstr, 0);
211   ExtConstr =
212       isl_constraint_set_coefficient_si(ExtConstr, isl_dim_set, Dims - 1, 1);
213   Set = isl_set_add_constraint(Set, ExtConstr);
214   ExtConstr = isl_constraint_alloc_inequality(LocalSpace);
215   ExtConstr = isl_constraint_set_constant_si(ExtConstr, VectorWidth - 1);
216   ExtConstr =
217       isl_constraint_set_coefficient_si(ExtConstr, isl_dim_set, Dims - 1, -1);
218   return isl_set_add_constraint(Set, ExtConstr);
219 }
220 
221 /// @brief Build the desired set of partial tile prefixes.
222 ///
223 /// We build a set of partial tile prefixes, which are prefixes of the vector
224 /// loop that have exactly VectorWidth iterations.
225 ///
226 /// 1. Get all prefixes of the vector loop.
227 /// 2. Extend it to a set, which has exactly VectorWidth iterations for
228 ///    any prefix from the set that was built on the previous step.
229 /// 3. Subtract loop domain from it, project out the vector loop dimension and
230 ///    get a set of prefixes, which don’t have exactly VectorWidth iterations.
231 /// 4. Subtract it from all prefixes of the vector loop and get the desired
232 ///    set.
233 ///
234 /// @param ScheduleRange A range of a map, which describes a prefix schedule
235 ///                      relation.
236 static __isl_give isl_set *
237 getPartialTilePrefixes(__isl_take isl_set *ScheduleRange, int VectorWidth) {
238   auto Dims = isl_set_dim(ScheduleRange, isl_dim_set);
239   auto *LoopPrefixes = isl_set_project_out(isl_set_copy(ScheduleRange),
240                                            isl_dim_set, Dims - 1, 1);
241   auto *ExtentPrefixes =
242       isl_set_add_dims(isl_set_copy(LoopPrefixes), isl_dim_set, 1);
243   ExtentPrefixes = addExtentConstraints(ExtentPrefixes, VectorWidth);
244   auto *BadPrefixes = isl_set_subtract(ExtentPrefixes, ScheduleRange);
245   BadPrefixes = isl_set_project_out(BadPrefixes, isl_dim_set, Dims - 1, 1);
246   return isl_set_subtract(LoopPrefixes, BadPrefixes);
247 }
248 
249 __isl_give isl_schedule_node *ScheduleTreeOptimizer::isolateFullPartialTiles(
250     __isl_take isl_schedule_node *Node, int VectorWidth) {
251   assert(isl_schedule_node_get_type(Node) == isl_schedule_node_band);
252   Node = isl_schedule_node_child(Node, 0);
253   Node = isl_schedule_node_child(Node, 0);
254   auto *SchedRelUMap = isl_schedule_node_get_prefix_schedule_relation(Node);
255   auto *ScheduleRelation = isl_map_from_union_map(SchedRelUMap);
256   auto *ScheduleRange = isl_map_range(ScheduleRelation);
257   auto *IsolateDomain = getPartialTilePrefixes(ScheduleRange, VectorWidth);
258   auto *AtomicOption = getAtomicOptions(isl_set_get_ctx(IsolateDomain));
259   auto *IsolateOption = getIsolateOptions(IsolateDomain);
260   Node = isl_schedule_node_parent(Node);
261   Node = isl_schedule_node_parent(Node);
262   auto *Options = isl_union_set_union(IsolateOption, AtomicOption);
263   Node = isl_schedule_node_band_set_ast_build_options(Node, Options);
264   return Node;
265 }
266 
267 __isl_give isl_schedule_node *
268 ScheduleTreeOptimizer::prevectSchedBand(__isl_take isl_schedule_node *Node,
269                                         unsigned DimToVectorize,
270                                         int VectorWidth) {
271   assert(isl_schedule_node_get_type(Node) == isl_schedule_node_band);
272 
273   auto Space = isl_schedule_node_band_get_space(Node);
274   auto ScheduleDimensions = isl_space_dim(Space, isl_dim_set);
275   isl_space_free(Space);
276   assert(DimToVectorize < ScheduleDimensions);
277 
278   if (DimToVectorize > 0) {
279     Node = isl_schedule_node_band_split(Node, DimToVectorize);
280     Node = isl_schedule_node_child(Node, 0);
281   }
282   if (DimToVectorize < ScheduleDimensions - 1)
283     Node = isl_schedule_node_band_split(Node, 1);
284   Space = isl_schedule_node_band_get_space(Node);
285   auto Sizes = isl_multi_val_zero(Space);
286   auto Ctx = isl_schedule_node_get_ctx(Node);
287   Sizes =
288       isl_multi_val_set_val(Sizes, 0, isl_val_int_from_si(Ctx, VectorWidth));
289   Node = isl_schedule_node_band_tile(Node, Sizes);
290   Node = isolateFullPartialTiles(Node, VectorWidth);
291   Node = isl_schedule_node_child(Node, 0);
292   // Make sure the "trivially vectorizable loop" is not unrolled. Otherwise,
293   // we will have troubles to match it in the backend.
294   Node = isl_schedule_node_band_set_ast_build_options(
295       Node, isl_union_set_read_from_str(Ctx, "{ unroll[x]: 1 = 0 }"));
296   Node = isl_schedule_node_band_sink(Node);
297   Node = isl_schedule_node_child(Node, 0);
298   if (isl_schedule_node_get_type(Node) == isl_schedule_node_leaf)
299     Node = isl_schedule_node_parent(Node);
300   isl_id *LoopMarker = isl_id_alloc(Ctx, "SIMD", nullptr);
301   Node = isl_schedule_node_insert_mark(Node, LoopMarker);
302   return Node;
303 }
304 
305 __isl_give isl_schedule_node *
306 ScheduleTreeOptimizer::tileNode(__isl_take isl_schedule_node *Node,
307                                 const char *Identifier, ArrayRef<int> TileSizes,
308                                 int DefaultTileSize) {
309   auto Ctx = isl_schedule_node_get_ctx(Node);
310   auto Space = isl_schedule_node_band_get_space(Node);
311   auto Dims = isl_space_dim(Space, isl_dim_set);
312   auto Sizes = isl_multi_val_zero(Space);
313   std::string IdentifierString(Identifier);
314   for (unsigned i = 0; i < Dims; i++) {
315     auto tileSize = i < TileSizes.size() ? TileSizes[i] : DefaultTileSize;
316     Sizes = isl_multi_val_set_val(Sizes, i, isl_val_int_from_si(Ctx, tileSize));
317   }
318   auto TileLoopMarkerStr = IdentifierString + " - Tiles";
319   isl_id *TileLoopMarker =
320       isl_id_alloc(Ctx, TileLoopMarkerStr.c_str(), nullptr);
321   Node = isl_schedule_node_insert_mark(Node, TileLoopMarker);
322   Node = isl_schedule_node_child(Node, 0);
323   Node = isl_schedule_node_band_tile(Node, Sizes);
324   Node = isl_schedule_node_child(Node, 0);
325   auto PointLoopMarkerStr = IdentifierString + " - Points";
326   isl_id *PointLoopMarker =
327       isl_id_alloc(Ctx, PointLoopMarkerStr.c_str(), nullptr);
328   Node = isl_schedule_node_insert_mark(Node, PointLoopMarker);
329   Node = isl_schedule_node_child(Node, 0);
330   return Node;
331 }
332 
333 bool ScheduleTreeOptimizer::isTileableBandNode(
334     __isl_keep isl_schedule_node *Node) {
335   if (isl_schedule_node_get_type(Node) != isl_schedule_node_band)
336     return false;
337 
338   if (isl_schedule_node_n_children(Node) != 1)
339     return false;
340 
341   if (!isl_schedule_node_band_get_permutable(Node))
342     return false;
343 
344   auto Space = isl_schedule_node_band_get_space(Node);
345   auto Dims = isl_space_dim(Space, isl_dim_set);
346   isl_space_free(Space);
347 
348   if (Dims <= 1)
349     return false;
350 
351   auto Child = isl_schedule_node_get_child(Node, 0);
352   auto Type = isl_schedule_node_get_type(Child);
353   isl_schedule_node_free(Child);
354 
355   if (Type != isl_schedule_node_leaf)
356     return false;
357 
358   return true;
359 }
360 
361 __isl_give isl_schedule_node *
362 ScheduleTreeOptimizer::optimizeBand(__isl_take isl_schedule_node *Node,
363                                     void *User) {
364   if (!isTileableBandNode(Node))
365     return Node;
366 
367   if (FirstLevelTiling)
368     Node = tileNode(Node, "1st level tiling", FirstLevelTileSizes,
369                     FirstLevelDefaultTileSize);
370 
371   if (SecondLevelTiling)
372     Node = tileNode(Node, "2nd level tiling", SecondLevelTileSizes,
373                     SecondLevelDefaultTileSize);
374 
375   if (RegisterTiling) {
376     auto *Ctx = isl_schedule_node_get_ctx(Node);
377     Node = tileNode(Node, "Register tiling", RegisterTileSizes,
378                     RegisterDefaultTileSize);
379     Node = isl_schedule_node_band_set_ast_build_options(
380         Node, isl_union_set_read_from_str(Ctx, "{unroll[x]}"));
381   }
382 
383   if (PollyVectorizerChoice == VECTORIZER_NONE)
384     return Node;
385 
386   auto Space = isl_schedule_node_band_get_space(Node);
387   auto Dims = isl_space_dim(Space, isl_dim_set);
388   isl_space_free(Space);
389 
390   for (int i = Dims - 1; i >= 0; i--)
391     if (isl_schedule_node_band_member_get_coincident(Node, i)) {
392       Node = prevectSchedBand(Node, i, PrevectorWidth);
393       break;
394     }
395 
396   return Node;
397 }
398 
399 __isl_give isl_schedule *
400 ScheduleTreeOptimizer::optimizeSchedule(__isl_take isl_schedule *Schedule) {
401   isl_schedule_node *Root = isl_schedule_get_root(Schedule);
402   Root = optimizeScheduleNode(Root);
403   isl_schedule_free(Schedule);
404   auto S = isl_schedule_node_get_schedule(Root);
405   isl_schedule_node_free(Root);
406   return S;
407 }
408 
409 __isl_give isl_schedule_node *ScheduleTreeOptimizer::optimizeScheduleNode(
410     __isl_take isl_schedule_node *Node) {
411   Node = isl_schedule_node_map_descendant_bottom_up(Node, optimizeBand, NULL);
412   return Node;
413 }
414 
415 bool ScheduleTreeOptimizer::isProfitableSchedule(
416     Scop &S, __isl_keep isl_union_map *NewSchedule) {
417   // To understand if the schedule has been optimized we check if the schedule
418   // has changed at all.
419   // TODO: We can improve this by tracking if any necessarily beneficial
420   // transformations have been performed. This can e.g. be tiling, loop
421   // interchange, or ...) We can track this either at the place where the
422   // transformation has been performed or, in case of automatic ILP based
423   // optimizations, by comparing (yet to be defined) performance metrics
424   // before/after the scheduling optimizer
425   // (e.g., #stride-one accesses)
426   isl_union_map *OldSchedule = S.getSchedule();
427   bool changed = !isl_union_map_is_equal(OldSchedule, NewSchedule);
428   isl_union_map_free(OldSchedule);
429   return changed;
430 }
431 
432 namespace {
433 class IslScheduleOptimizer : public ScopPass {
434 public:
435   static char ID;
436   explicit IslScheduleOptimizer() : ScopPass(ID) { LastSchedule = nullptr; }
437 
438   ~IslScheduleOptimizer() { isl_schedule_free(LastSchedule); }
439 
440   /// @brief Optimize the schedule of the SCoP @p S.
441   bool runOnScop(Scop &S) override;
442 
443   /// @brief Print the new schedule for the SCoP @p S.
444   void printScop(raw_ostream &OS, Scop &S) const override;
445 
446   /// @brief Register all analyses and transformation required.
447   void getAnalysisUsage(AnalysisUsage &AU) const override;
448 
449   /// @brief Release the internal memory.
450   void releaseMemory() override {
451     isl_schedule_free(LastSchedule);
452     LastSchedule = nullptr;
453   }
454 
455 private:
456   isl_schedule *LastSchedule;
457 };
458 }
459 
460 char IslScheduleOptimizer::ID = 0;
461 
462 bool IslScheduleOptimizer::runOnScop(Scop &S) {
463 
464   // Skip empty SCoPs but still allow code generation as it will delete the
465   // loops present but not needed.
466   if (S.getSize() == 0) {
467     S.markAsOptimized();
468     return false;
469   }
470 
471   const Dependences &D =
472       getAnalysis<DependenceInfo>().getDependences(Dependences::AL_Statement);
473 
474   if (!D.hasValidDependences())
475     return false;
476 
477   isl_schedule_free(LastSchedule);
478   LastSchedule = nullptr;
479 
480   // Build input data.
481   int ValidityKinds =
482       Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW;
483   int ProximityKinds;
484 
485   if (OptimizeDeps == "all")
486     ProximityKinds =
487         Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW;
488   else if (OptimizeDeps == "raw")
489     ProximityKinds = Dependences::TYPE_RAW;
490   else {
491     errs() << "Do not know how to optimize for '" << OptimizeDeps << "'"
492            << " Falling back to optimizing all dependences.\n";
493     ProximityKinds =
494         Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW;
495   }
496 
497   isl_union_set *Domain = S.getDomains();
498 
499   if (!Domain)
500     return false;
501 
502   isl_union_map *Validity = D.getDependences(ValidityKinds);
503   isl_union_map *Proximity = D.getDependences(ProximityKinds);
504 
505   // Simplify the dependences by removing the constraints introduced by the
506   // domains. This can speed up the scheduling time significantly, as large
507   // constant coefficients will be removed from the dependences. The
508   // introduction of some additional dependences reduces the possible
509   // transformations, but in most cases, such transformation do not seem to be
510   // interesting anyway. In some cases this option may stop the scheduler to
511   // find any schedule.
512   if (SimplifyDeps == "yes") {
513     Validity = isl_union_map_gist_domain(Validity, isl_union_set_copy(Domain));
514     Validity = isl_union_map_gist_range(Validity, isl_union_set_copy(Domain));
515     Proximity =
516         isl_union_map_gist_domain(Proximity, isl_union_set_copy(Domain));
517     Proximity = isl_union_map_gist_range(Proximity, isl_union_set_copy(Domain));
518   } else if (SimplifyDeps != "no") {
519     errs() << "warning: Option -polly-opt-simplify-deps should either be 'yes' "
520               "or 'no'. Falling back to default: 'yes'\n";
521   }
522 
523   DEBUG(dbgs() << "\n\nCompute schedule from: ");
524   DEBUG(dbgs() << "Domain := " << stringFromIslObj(Domain) << ";\n");
525   DEBUG(dbgs() << "Proximity := " << stringFromIslObj(Proximity) << ";\n");
526   DEBUG(dbgs() << "Validity := " << stringFromIslObj(Validity) << ";\n");
527 
528   unsigned IslSerializeSCCs;
529 
530   if (FusionStrategy == "max") {
531     IslSerializeSCCs = 0;
532   } else if (FusionStrategy == "min") {
533     IslSerializeSCCs = 1;
534   } else {
535     errs() << "warning: Unknown fusion strategy. Falling back to maximal "
536               "fusion.\n";
537     IslSerializeSCCs = 0;
538   }
539 
540   int IslMaximizeBands;
541 
542   if (MaximizeBandDepth == "yes") {
543     IslMaximizeBands = 1;
544   } else if (MaximizeBandDepth == "no") {
545     IslMaximizeBands = 0;
546   } else {
547     errs() << "warning: Option -polly-opt-maximize-bands should either be 'yes'"
548               " or 'no'. Falling back to default: 'yes'\n";
549     IslMaximizeBands = 1;
550   }
551 
552   int IslOuterCoincidence;
553 
554   if (OuterCoincidence == "yes") {
555     IslOuterCoincidence = 1;
556   } else if (OuterCoincidence == "no") {
557     IslOuterCoincidence = 0;
558   } else {
559     errs() << "warning: Option -polly-opt-outer-coincidence should either be "
560               "'yes' or 'no'. Falling back to default: 'no'\n";
561     IslOuterCoincidence = 0;
562   }
563 
564   isl_options_set_schedule_outer_coincidence(S.getIslCtx(),
565                                              IslOuterCoincidence);
566   isl_options_set_schedule_serialize_sccs(S.getIslCtx(), IslSerializeSCCs);
567   isl_options_set_schedule_maximize_band_depth(S.getIslCtx(), IslMaximizeBands);
568   isl_options_set_schedule_max_constant_term(S.getIslCtx(), MaxConstantTerm);
569   isl_options_set_schedule_max_coefficient(S.getIslCtx(), MaxCoefficient);
570   isl_options_set_tile_scale_tile_loops(S.getIslCtx(), 0);
571 
572   isl_options_set_on_error(S.getIslCtx(), ISL_ON_ERROR_CONTINUE);
573 
574   isl_schedule_constraints *ScheduleConstraints;
575   ScheduleConstraints = isl_schedule_constraints_on_domain(Domain);
576   ScheduleConstraints =
577       isl_schedule_constraints_set_proximity(ScheduleConstraints, Proximity);
578   ScheduleConstraints = isl_schedule_constraints_set_validity(
579       ScheduleConstraints, isl_union_map_copy(Validity));
580   ScheduleConstraints =
581       isl_schedule_constraints_set_coincidence(ScheduleConstraints, Validity);
582   isl_schedule *Schedule;
583   Schedule = isl_schedule_constraints_compute_schedule(ScheduleConstraints);
584   isl_options_set_on_error(S.getIslCtx(), ISL_ON_ERROR_ABORT);
585 
586   // In cases the scheduler is not able to optimize the code, we just do not
587   // touch the schedule.
588   if (!Schedule)
589     return false;
590 
591   DEBUG({
592     auto *P = isl_printer_to_str(S.getIslCtx());
593     P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK);
594     P = isl_printer_print_schedule(P, Schedule);
595     dbgs() << "NewScheduleTree: \n" << isl_printer_get_str(P) << "\n";
596     isl_printer_free(P);
597   });
598 
599   isl_schedule *NewSchedule = ScheduleTreeOptimizer::optimizeSchedule(Schedule);
600   isl_union_map *NewScheduleMap = isl_schedule_get_map(NewSchedule);
601 
602   if (!ScheduleTreeOptimizer::isProfitableSchedule(S, NewScheduleMap)) {
603     isl_union_map_free(NewScheduleMap);
604     isl_schedule_free(NewSchedule);
605     return false;
606   }
607 
608   S.setScheduleTree(NewSchedule);
609   S.markAsOptimized();
610 
611   isl_union_map_free(NewScheduleMap);
612   return false;
613 }
614 
615 void IslScheduleOptimizer::printScop(raw_ostream &OS, Scop &) const {
616   isl_printer *p;
617   char *ScheduleStr;
618 
619   OS << "Calculated schedule:\n";
620 
621   if (!LastSchedule) {
622     OS << "n/a\n";
623     return;
624   }
625 
626   p = isl_printer_to_str(isl_schedule_get_ctx(LastSchedule));
627   p = isl_printer_print_schedule(p, LastSchedule);
628   ScheduleStr = isl_printer_get_str(p);
629   isl_printer_free(p);
630 
631   OS << ScheduleStr << "\n";
632 }
633 
634 void IslScheduleOptimizer::getAnalysisUsage(AnalysisUsage &AU) const {
635   ScopPass::getAnalysisUsage(AU);
636   AU.addRequired<DependenceInfo>();
637 }
638 
639 Pass *polly::createIslScheduleOptimizerPass() {
640   return new IslScheduleOptimizer();
641 }
642 
643 INITIALIZE_PASS_BEGIN(IslScheduleOptimizer, "polly-opt-isl",
644                       "Polly - Optimize schedule of SCoP", false, false);
645 INITIALIZE_PASS_DEPENDENCY(DependenceInfo);
646 INITIALIZE_PASS_DEPENDENCY(ScopInfo);
647 INITIALIZE_PASS_END(IslScheduleOptimizer, "polly-opt-isl",
648                     "Polly - Optimize schedule of SCoP", false, false)
649