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<int> PrevectorWidth(
106     "polly-prevect-width",
107     cl::desc(
108         "The number of loop iterations to strip-mine for pre-vectorization"),
109     cl::Hidden, cl::init(4), cl::ZeroOrMore, cl::cat(PollyCategory));
110 
111 static cl::opt<bool> FirstLevelTiling("polly-tiling",
112                                       cl::desc("Enable loop tiling"),
113                                       cl::init(true), cl::ZeroOrMore,
114                                       cl::cat(PollyCategory));
115 
116 static cl::opt<int> FirstLevelDefaultTileSize(
117     "polly-default-tile-size",
118     cl::desc("The default tile size (if not enough were provided by"
119              " --polly-tile-sizes)"),
120     cl::Hidden, cl::init(32), cl::ZeroOrMore, cl::cat(PollyCategory));
121 
122 static cl::list<int> FirstLevelTileSizes(
123     "polly-tile-sizes", cl::desc("A tile size for each loop dimension, filled "
124                                  "with --polly-default-tile-size"),
125     cl::Hidden, cl::ZeroOrMore, cl::CommaSeparated, cl::cat(PollyCategory));
126 
127 static cl::opt<bool>
128     SecondLevelTiling("polly-2nd-level-tiling",
129                       cl::desc("Enable a 2nd level loop of loop tiling"),
130                       cl::init(false), cl::ZeroOrMore, cl::cat(PollyCategory));
131 
132 static cl::opt<int> SecondLevelDefaultTileSize(
133     "polly-2nd-level-default-tile-size",
134     cl::desc("The default 2nd-level tile size (if not enough were provided by"
135              " --polly-2nd-level-tile-sizes)"),
136     cl::Hidden, cl::init(16), cl::ZeroOrMore, cl::cat(PollyCategory));
137 
138 static cl::list<int>
139     SecondLevelTileSizes("polly-2nd-level-tile-sizes",
140                          cl::desc("A tile size for each loop dimension, filled "
141                                   "with --polly-default-tile-size"),
142                          cl::Hidden, cl::ZeroOrMore, cl::CommaSeparated,
143                          cl::cat(PollyCategory));
144 
145 static cl::opt<bool> RegisterTiling("polly-register-tiling",
146                                     cl::desc("Enable register tiling"),
147                                     cl::init(false), cl::ZeroOrMore,
148                                     cl::cat(PollyCategory));
149 
150 static cl::opt<int> RegisterDefaultTileSize(
151     "polly-register-tiling-default-tile-size",
152     cl::desc("The default register tile size (if not enough were provided by"
153              " --polly-register-tile-sizes)"),
154     cl::Hidden, cl::init(2), cl::ZeroOrMore, cl::cat(PollyCategory));
155 
156 static cl::list<int>
157     RegisterTileSizes("polly-register-tile-sizes",
158                       cl::desc("A tile size for each loop dimension, filled "
159                                "with --polly-register-tile-size"),
160                       cl::Hidden, cl::ZeroOrMore, cl::CommaSeparated,
161                       cl::cat(PollyCategory));
162 
163 /// @brief Create an isl_union_set, which describes the isolate option based
164 ///        on IsoalteDomain.
165 ///
166 /// @param IsolateDomain An isl_set whose last dimension is the only one that
167 ///                      should belong to the current band node.
168 static __isl_give isl_union_set *
169 getIsolateOptions(__isl_take isl_set *IsolateDomain) {
170   auto Dims = isl_set_dim(IsolateDomain, isl_dim_set);
171   auto *IsolateRelation = isl_map_from_domain(IsolateDomain);
172   IsolateRelation = isl_map_move_dims(IsolateRelation, isl_dim_out, 0,
173                                       isl_dim_in, Dims - 1, 1);
174   auto *IsolateOption = isl_map_wrap(IsolateRelation);
175   auto *Id = isl_id_alloc(isl_set_get_ctx(IsolateOption), "isolate", NULL);
176   return isl_union_set_from_set(isl_set_set_tuple_id(IsolateOption, Id));
177 }
178 
179 /// @brief Create an isl_union_set, which describes the atomic option for the
180 ///        dimension of the current node.
181 ///
182 /// It may help to reduce the size of generated code.
183 ///
184 /// @param Ctx An isl_ctx, which is used to create the isl_union_set.
185 static __isl_give isl_union_set *getAtomicOptions(__isl_take isl_ctx *Ctx) {
186   auto *Space = isl_space_set_alloc(Ctx, 0, 1);
187   auto *AtomicOption = isl_set_universe(Space);
188   auto *Id = isl_id_alloc(Ctx, "atomic", NULL);
189   return isl_union_set_from_set(isl_set_set_tuple_id(AtomicOption, Id));
190 }
191 
192 /// @brief Make the last dimension of Set to take values
193 ///        from 0 to VectorWidth - 1.
194 ///
195 /// @param Set         A set, which should be modified.
196 /// @param VectorWidth A parameter, which determines the constraint.
197 static __isl_give isl_set *addExtentConstraints(__isl_take isl_set *Set,
198                                                 int VectorWidth) {
199   auto Dims = isl_set_dim(Set, isl_dim_set);
200   auto Space = isl_set_get_space(Set);
201   auto *LocalSpace = isl_local_space_from_space(Space);
202   auto *ExtConstr =
203       isl_constraint_alloc_inequality(isl_local_space_copy(LocalSpace));
204   ExtConstr = isl_constraint_set_constant_si(ExtConstr, 0);
205   ExtConstr =
206       isl_constraint_set_coefficient_si(ExtConstr, isl_dim_set, Dims - 1, 1);
207   Set = isl_set_add_constraint(Set, ExtConstr);
208   ExtConstr = isl_constraint_alloc_inequality(LocalSpace);
209   ExtConstr = isl_constraint_set_constant_si(ExtConstr, VectorWidth - 1);
210   ExtConstr =
211       isl_constraint_set_coefficient_si(ExtConstr, isl_dim_set, Dims - 1, -1);
212   return isl_set_add_constraint(Set, ExtConstr);
213 }
214 
215 /// @brief Build the desired set of partial tile prefixes.
216 ///
217 /// We build a set of partial tile prefixes, which are prefixes of the vector
218 /// loop that have exactly VectorWidth iterations.
219 ///
220 /// 1. Get all prefixes of the vector loop.
221 /// 2. Extend it to a set, which has exactly VectorWidth iterations for
222 ///    any prefix from the set that was built on the previous step.
223 /// 3. Subtract loop domain from it, project out the vector loop dimension and
224 ///    get a set of prefixes, which don’t have exactly VectorWidth iterations.
225 /// 4. Subtract it from all prefixes of the vector loop and get the desired
226 ///    set.
227 ///
228 /// @param ScheduleRange A range of a map, which describes a prefix schedule
229 ///                      relation.
230 static __isl_give isl_set *
231 getPartialTilePrefixes(__isl_take isl_set *ScheduleRange, int VectorWidth) {
232   auto Dims = isl_set_dim(ScheduleRange, isl_dim_set);
233   auto *LoopPrefixes = isl_set_project_out(isl_set_copy(ScheduleRange),
234                                            isl_dim_set, Dims - 1, 1);
235   auto *ExtentPrefixes =
236       isl_set_add_dims(isl_set_copy(LoopPrefixes), isl_dim_set, 1);
237   ExtentPrefixes = addExtentConstraints(ExtentPrefixes, VectorWidth);
238   auto *BadPrefixes = isl_set_subtract(ExtentPrefixes, ScheduleRange);
239   BadPrefixes = isl_set_project_out(BadPrefixes, isl_dim_set, Dims - 1, 1);
240   return isl_set_subtract(LoopPrefixes, BadPrefixes);
241 }
242 
243 __isl_give isl_schedule_node *ScheduleTreeOptimizer::isolateFullPartialTiles(
244     __isl_take isl_schedule_node *Node, int VectorWidth) {
245   assert(isl_schedule_node_get_type(Node) == isl_schedule_node_band);
246   Node = isl_schedule_node_child(Node, 0);
247   Node = isl_schedule_node_child(Node, 0);
248   auto *SchedRelUMap = isl_schedule_node_get_prefix_schedule_relation(Node);
249   auto *ScheduleRelation = isl_map_from_union_map(SchedRelUMap);
250   auto *ScheduleRange = isl_map_range(ScheduleRelation);
251   auto *IsolateDomain = getPartialTilePrefixes(ScheduleRange, VectorWidth);
252   auto *AtomicOption = getAtomicOptions(isl_set_get_ctx(IsolateDomain));
253   auto *IsolateOption = getIsolateOptions(IsolateDomain);
254   Node = isl_schedule_node_parent(Node);
255   Node = isl_schedule_node_parent(Node);
256   auto *Options = isl_union_set_union(IsolateOption, AtomicOption);
257   Node = isl_schedule_node_band_set_ast_build_options(Node, Options);
258   return Node;
259 }
260 
261 __isl_give isl_schedule_node *
262 ScheduleTreeOptimizer::prevectSchedBand(__isl_take isl_schedule_node *Node,
263                                         unsigned DimToVectorize,
264                                         int VectorWidth) {
265   assert(isl_schedule_node_get_type(Node) == isl_schedule_node_band);
266 
267   auto Space = isl_schedule_node_band_get_space(Node);
268   auto ScheduleDimensions = isl_space_dim(Space, isl_dim_set);
269   isl_space_free(Space);
270   assert(DimToVectorize < ScheduleDimensions);
271 
272   if (DimToVectorize > 0) {
273     Node = isl_schedule_node_band_split(Node, DimToVectorize);
274     Node = isl_schedule_node_child(Node, 0);
275   }
276   if (DimToVectorize < ScheduleDimensions - 1)
277     Node = isl_schedule_node_band_split(Node, 1);
278   Space = isl_schedule_node_band_get_space(Node);
279   auto Sizes = isl_multi_val_zero(Space);
280   auto Ctx = isl_schedule_node_get_ctx(Node);
281   Sizes =
282       isl_multi_val_set_val(Sizes, 0, isl_val_int_from_si(Ctx, VectorWidth));
283   Node = isl_schedule_node_band_tile(Node, Sizes);
284   Node = isolateFullPartialTiles(Node, VectorWidth);
285   Node = isl_schedule_node_child(Node, 0);
286   // Make sure the "trivially vectorizable loop" is not unrolled. Otherwise,
287   // we will have troubles to match it in the backend.
288   Node = isl_schedule_node_band_set_ast_build_options(
289       Node, isl_union_set_read_from_str(Ctx, "{ unroll[x]: 1 = 0 }"));
290   Node = isl_schedule_node_band_sink(Node);
291   Node = isl_schedule_node_child(Node, 0);
292   if (isl_schedule_node_get_type(Node) == isl_schedule_node_leaf)
293     Node = isl_schedule_node_parent(Node);
294   isl_id *LoopMarker = isl_id_alloc(Ctx, "SIMD", nullptr);
295   Node = isl_schedule_node_insert_mark(Node, LoopMarker);
296   return Node;
297 }
298 
299 __isl_give isl_schedule_node *
300 ScheduleTreeOptimizer::tileNode(__isl_take isl_schedule_node *Node,
301                                 const char *Identifier, ArrayRef<int> TileSizes,
302                                 int DefaultTileSize) {
303   auto Ctx = isl_schedule_node_get_ctx(Node);
304   auto Space = isl_schedule_node_band_get_space(Node);
305   auto Dims = isl_space_dim(Space, isl_dim_set);
306   auto Sizes = isl_multi_val_zero(Space);
307   std::string IdentifierString(Identifier);
308   for (unsigned i = 0; i < Dims; i++) {
309     auto tileSize = i < TileSizes.size() ? TileSizes[i] : DefaultTileSize;
310     Sizes = isl_multi_val_set_val(Sizes, i, isl_val_int_from_si(Ctx, tileSize));
311   }
312   auto TileLoopMarkerStr = IdentifierString + " - Tiles";
313   isl_id *TileLoopMarker =
314       isl_id_alloc(Ctx, TileLoopMarkerStr.c_str(), nullptr);
315   Node = isl_schedule_node_insert_mark(Node, TileLoopMarker);
316   Node = isl_schedule_node_child(Node, 0);
317   Node = isl_schedule_node_band_tile(Node, Sizes);
318   Node = isl_schedule_node_child(Node, 0);
319   auto PointLoopMarkerStr = IdentifierString + " - Points";
320   isl_id *PointLoopMarker =
321       isl_id_alloc(Ctx, PointLoopMarkerStr.c_str(), nullptr);
322   Node = isl_schedule_node_insert_mark(Node, PointLoopMarker);
323   Node = isl_schedule_node_child(Node, 0);
324   return Node;
325 }
326 
327 bool ScheduleTreeOptimizer::isTileableBandNode(
328     __isl_keep isl_schedule_node *Node) {
329   if (isl_schedule_node_get_type(Node) != isl_schedule_node_band)
330     return false;
331 
332   if (isl_schedule_node_n_children(Node) != 1)
333     return false;
334 
335   if (!isl_schedule_node_band_get_permutable(Node))
336     return false;
337 
338   auto Space = isl_schedule_node_band_get_space(Node);
339   auto Dims = isl_space_dim(Space, isl_dim_set);
340   isl_space_free(Space);
341 
342   if (Dims <= 1)
343     return false;
344 
345   auto Child = isl_schedule_node_get_child(Node, 0);
346   auto Type = isl_schedule_node_get_type(Child);
347   isl_schedule_node_free(Child);
348 
349   if (Type != isl_schedule_node_leaf)
350     return false;
351 
352   return true;
353 }
354 
355 __isl_give isl_schedule_node *
356 ScheduleTreeOptimizer::optimizeBand(__isl_take isl_schedule_node *Node,
357                                     void *User) {
358   if (!isTileableBandNode(Node))
359     return Node;
360 
361   if (FirstLevelTiling)
362     Node = tileNode(Node, "1st level tiling", FirstLevelTileSizes,
363                     FirstLevelDefaultTileSize);
364 
365   if (SecondLevelTiling)
366     Node = tileNode(Node, "2nd level tiling", SecondLevelTileSizes,
367                     SecondLevelDefaultTileSize);
368 
369   if (RegisterTiling) {
370     auto *Ctx = isl_schedule_node_get_ctx(Node);
371     Node = tileNode(Node, "Register tiling", RegisterTileSizes,
372                     RegisterDefaultTileSize);
373     Node = isl_schedule_node_band_set_ast_build_options(
374         Node, isl_union_set_read_from_str(Ctx, "{unroll[x]}"));
375   }
376 
377   if (PollyVectorizerChoice == VECTORIZER_NONE)
378     return Node;
379 
380   auto Space = isl_schedule_node_band_get_space(Node);
381   auto Dims = isl_space_dim(Space, isl_dim_set);
382   isl_space_free(Space);
383 
384   for (int i = Dims - 1; i >= 0; i--)
385     if (isl_schedule_node_band_member_get_coincident(Node, i)) {
386       Node = prevectSchedBand(Node, i, PrevectorWidth);
387       break;
388     }
389 
390   return Node;
391 }
392 
393 __isl_give isl_schedule *
394 ScheduleTreeOptimizer::optimizeSchedule(__isl_take isl_schedule *Schedule) {
395   isl_schedule_node *Root = isl_schedule_get_root(Schedule);
396   Root = optimizeScheduleNode(Root);
397   isl_schedule_free(Schedule);
398   auto S = isl_schedule_node_get_schedule(Root);
399   isl_schedule_node_free(Root);
400   return S;
401 }
402 
403 __isl_give isl_schedule_node *ScheduleTreeOptimizer::optimizeScheduleNode(
404     __isl_take isl_schedule_node *Node) {
405   Node = isl_schedule_node_map_descendant_bottom_up(Node, optimizeBand, NULL);
406   return Node;
407 }
408 
409 bool ScheduleTreeOptimizer::isProfitableSchedule(
410     Scop &S, __isl_keep isl_union_map *NewSchedule) {
411   // To understand if the schedule has been optimized we check if the schedule
412   // has changed at all.
413   // TODO: We can improve this by tracking if any necessarily beneficial
414   // transformations have been performed. This can e.g. be tiling, loop
415   // interchange, or ...) We can track this either at the place where the
416   // transformation has been performed or, in case of automatic ILP based
417   // optimizations, by comparing (yet to be defined) performance metrics
418   // before/after the scheduling optimizer
419   // (e.g., #stride-one accesses)
420   isl_union_map *OldSchedule = S.getSchedule();
421   bool changed = !isl_union_map_is_equal(OldSchedule, NewSchedule);
422   isl_union_map_free(OldSchedule);
423   return changed;
424 }
425 
426 namespace {
427 class IslScheduleOptimizer : public ScopPass {
428 public:
429   static char ID;
430   explicit IslScheduleOptimizer() : ScopPass(ID) { LastSchedule = nullptr; }
431 
432   ~IslScheduleOptimizer() { isl_schedule_free(LastSchedule); }
433 
434   /// @brief Optimize the schedule of the SCoP @p S.
435   bool runOnScop(Scop &S) override;
436 
437   /// @brief Print the new schedule for the SCoP @p S.
438   void printScop(raw_ostream &OS, Scop &S) const override;
439 
440   /// @brief Register all analyses and transformation required.
441   void getAnalysisUsage(AnalysisUsage &AU) const override;
442 
443   /// @brief Release the internal memory.
444   void releaseMemory() override {
445     isl_schedule_free(LastSchedule);
446     LastSchedule = nullptr;
447   }
448 
449 private:
450   isl_schedule *LastSchedule;
451 };
452 }
453 
454 char IslScheduleOptimizer::ID = 0;
455 
456 bool IslScheduleOptimizer::runOnScop(Scop &S) {
457 
458   // Skip empty SCoPs but still allow code generation as it will delete the
459   // loops present but not needed.
460   if (S.getSize() == 0) {
461     S.markAsOptimized();
462     return false;
463   }
464 
465   const Dependences &D =
466       getAnalysis<DependenceInfo>().getDependences(Dependences::AL_Statement);
467 
468   if (!D.hasValidDependences())
469     return false;
470 
471   isl_schedule_free(LastSchedule);
472   LastSchedule = nullptr;
473 
474   // Build input data.
475   int ValidityKinds =
476       Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW;
477   int ProximityKinds;
478 
479   if (OptimizeDeps == "all")
480     ProximityKinds =
481         Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW;
482   else if (OptimizeDeps == "raw")
483     ProximityKinds = Dependences::TYPE_RAW;
484   else {
485     errs() << "Do not know how to optimize for '" << OptimizeDeps << "'"
486            << " Falling back to optimizing all dependences.\n";
487     ProximityKinds =
488         Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW;
489   }
490 
491   isl_union_set *Domain = S.getDomains();
492 
493   if (!Domain)
494     return false;
495 
496   isl_union_map *Validity = D.getDependences(ValidityKinds);
497   isl_union_map *Proximity = D.getDependences(ProximityKinds);
498 
499   // Simplify the dependences by removing the constraints introduced by the
500   // domains. This can speed up the scheduling time significantly, as large
501   // constant coefficients will be removed from the dependences. The
502   // introduction of some additional dependences reduces the possible
503   // transformations, but in most cases, such transformation do not seem to be
504   // interesting anyway. In some cases this option may stop the scheduler to
505   // find any schedule.
506   if (SimplifyDeps == "yes") {
507     Validity = isl_union_map_gist_domain(Validity, isl_union_set_copy(Domain));
508     Validity = isl_union_map_gist_range(Validity, isl_union_set_copy(Domain));
509     Proximity =
510         isl_union_map_gist_domain(Proximity, isl_union_set_copy(Domain));
511     Proximity = isl_union_map_gist_range(Proximity, isl_union_set_copy(Domain));
512   } else if (SimplifyDeps != "no") {
513     errs() << "warning: Option -polly-opt-simplify-deps should either be 'yes' "
514               "or 'no'. Falling back to default: 'yes'\n";
515   }
516 
517   DEBUG(dbgs() << "\n\nCompute schedule from: ");
518   DEBUG(dbgs() << "Domain := " << stringFromIslObj(Domain) << ";\n");
519   DEBUG(dbgs() << "Proximity := " << stringFromIslObj(Proximity) << ";\n");
520   DEBUG(dbgs() << "Validity := " << stringFromIslObj(Validity) << ";\n");
521 
522   unsigned IslSerializeSCCs;
523 
524   if (FusionStrategy == "max") {
525     IslSerializeSCCs = 0;
526   } else if (FusionStrategy == "min") {
527     IslSerializeSCCs = 1;
528   } else {
529     errs() << "warning: Unknown fusion strategy. Falling back to maximal "
530               "fusion.\n";
531     IslSerializeSCCs = 0;
532   }
533 
534   int IslMaximizeBands;
535 
536   if (MaximizeBandDepth == "yes") {
537     IslMaximizeBands = 1;
538   } else if (MaximizeBandDepth == "no") {
539     IslMaximizeBands = 0;
540   } else {
541     errs() << "warning: Option -polly-opt-maximize-bands should either be 'yes'"
542               " or 'no'. Falling back to default: 'yes'\n";
543     IslMaximizeBands = 1;
544   }
545 
546   isl_options_set_schedule_serialize_sccs(S.getIslCtx(), IslSerializeSCCs);
547   isl_options_set_schedule_maximize_band_depth(S.getIslCtx(), IslMaximizeBands);
548   isl_options_set_schedule_max_constant_term(S.getIslCtx(), MaxConstantTerm);
549   isl_options_set_schedule_max_coefficient(S.getIslCtx(), MaxCoefficient);
550   isl_options_set_tile_scale_tile_loops(S.getIslCtx(), 0);
551 
552   isl_options_set_on_error(S.getIslCtx(), ISL_ON_ERROR_CONTINUE);
553 
554   isl_schedule_constraints *ScheduleConstraints;
555   ScheduleConstraints = isl_schedule_constraints_on_domain(Domain);
556   ScheduleConstraints =
557       isl_schedule_constraints_set_proximity(ScheduleConstraints, Proximity);
558   ScheduleConstraints = isl_schedule_constraints_set_validity(
559       ScheduleConstraints, isl_union_map_copy(Validity));
560   ScheduleConstraints =
561       isl_schedule_constraints_set_coincidence(ScheduleConstraints, Validity);
562   isl_schedule *Schedule;
563   Schedule = isl_schedule_constraints_compute_schedule(ScheduleConstraints);
564   isl_options_set_on_error(S.getIslCtx(), ISL_ON_ERROR_ABORT);
565 
566   // In cases the scheduler is not able to optimize the code, we just do not
567   // touch the schedule.
568   if (!Schedule)
569     return false;
570 
571   DEBUG({
572     auto *P = isl_printer_to_str(S.getIslCtx());
573     P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK);
574     P = isl_printer_print_schedule(P, Schedule);
575     dbgs() << "NewScheduleTree: \n" << isl_printer_get_str(P) << "\n";
576     isl_printer_free(P);
577   });
578 
579   isl_schedule *NewSchedule = ScheduleTreeOptimizer::optimizeSchedule(Schedule);
580   isl_union_map *NewScheduleMap = isl_schedule_get_map(NewSchedule);
581 
582   if (!ScheduleTreeOptimizer::isProfitableSchedule(S, NewScheduleMap)) {
583     isl_union_map_free(NewScheduleMap);
584     isl_schedule_free(NewSchedule);
585     return false;
586   }
587 
588   S.setScheduleTree(NewSchedule);
589   S.markAsOptimized();
590 
591   isl_union_map_free(NewScheduleMap);
592   return false;
593 }
594 
595 void IslScheduleOptimizer::printScop(raw_ostream &OS, Scop &) const {
596   isl_printer *p;
597   char *ScheduleStr;
598 
599   OS << "Calculated schedule:\n";
600 
601   if (!LastSchedule) {
602     OS << "n/a\n";
603     return;
604   }
605 
606   p = isl_printer_to_str(isl_schedule_get_ctx(LastSchedule));
607   p = isl_printer_print_schedule(p, LastSchedule);
608   ScheduleStr = isl_printer_get_str(p);
609   isl_printer_free(p);
610 
611   OS << ScheduleStr << "\n";
612 }
613 
614 void IslScheduleOptimizer::getAnalysisUsage(AnalysisUsage &AU) const {
615   ScopPass::getAnalysisUsage(AU);
616   AU.addRequired<DependenceInfo>();
617 }
618 
619 Pass *polly::createIslScheduleOptimizerPass() {
620   return new IslScheduleOptimizer();
621 }
622 
623 INITIALIZE_PASS_BEGIN(IslScheduleOptimizer, "polly-opt-isl",
624                       "Polly - Optimize schedule of SCoP", false, false);
625 INITIALIZE_PASS_DEPENDENCY(DependenceInfo);
626 INITIALIZE_PASS_DEPENDENCY(ScopInfo);
627 INITIALIZE_PASS_END(IslScheduleOptimizer, "polly-opt-isl",
628                     "Polly - Optimize schedule of SCoP", false, false)
629