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 the isl to calculate a schedule that is optimized for parallelism 11 // and tileablility. The algorithm used in isl is an optimized version of the 12 // algorithm described in following paper: 13 // 14 // U. Bondhugula, A. Hartono, J. Ramanujam, and P. Sadayappan. 15 // A Practical Automatic Polyhedral Parallelizer and Locality Optimizer. 16 // In Proceedings of the 2008 ACM SIGPLAN Conference On Programming Language 17 // Design and Implementation, PLDI ’08, pages 101–113. ACM, 2008. 18 //===----------------------------------------------------------------------===// 19 20 #include "polly/ScheduleOptimizer.h" 21 #include "polly/CodeGen/CodeGeneration.h" 22 #include "polly/DependenceInfo.h" 23 #include "polly/LinkAllPasses.h" 24 #include "polly/Options.h" 25 #include "polly/ScopInfo.h" 26 #include "polly/Support/GICHelper.h" 27 #include "llvm/Support/Debug.h" 28 #include "isl/aff.h" 29 #include "isl/band.h" 30 #include "isl/constraint.h" 31 #include "isl/map.h" 32 #include "isl/options.h" 33 #include "isl/printer.h" 34 #include "isl/schedule.h" 35 #include "isl/schedule_node.h" 36 #include "isl/space.h" 37 #include "isl/union_map.h" 38 #include "isl/union_set.h" 39 40 using namespace llvm; 41 using namespace polly; 42 43 #define DEBUG_TYPE "polly-opt-isl" 44 45 namespace polly { 46 bool DisablePollyTiling; 47 } 48 static cl::opt<bool, true> 49 DisableTiling("polly-no-tiling", 50 cl::desc("Disable tiling in the scheduler"), 51 cl::location(polly::DisablePollyTiling), cl::init(false), 52 cl::ZeroOrMore, cl::cat(PollyCategory)); 53 54 static cl::opt<std::string> 55 OptimizeDeps("polly-opt-optimize-only", 56 cl::desc("Only a certain kind of dependences (all/raw)"), 57 cl::Hidden, cl::init("all"), cl::ZeroOrMore, 58 cl::cat(PollyCategory)); 59 60 static cl::opt<std::string> 61 SimplifyDeps("polly-opt-simplify-deps", 62 cl::desc("Dependences should be simplified (yes/no)"), 63 cl::Hidden, cl::init("yes"), cl::ZeroOrMore, 64 cl::cat(PollyCategory)); 65 66 static cl::opt<int> MaxConstantTerm( 67 "polly-opt-max-constant-term", 68 cl::desc("The maximal constant term allowed (-1 is unlimited)"), cl::Hidden, 69 cl::init(20), cl::ZeroOrMore, cl::cat(PollyCategory)); 70 71 static cl::opt<int> MaxCoefficient( 72 "polly-opt-max-coefficient", 73 cl::desc("The maximal coefficient allowed (-1 is unlimited)"), cl::Hidden, 74 cl::init(20), cl::ZeroOrMore, cl::cat(PollyCategory)); 75 76 static cl::opt<std::string> FusionStrategy( 77 "polly-opt-fusion", cl::desc("The fusion strategy to choose (min/max)"), 78 cl::Hidden, cl::init("min"), cl::ZeroOrMore, cl::cat(PollyCategory)); 79 80 static cl::opt<std::string> 81 MaximizeBandDepth("polly-opt-maximize-bands", 82 cl::desc("Maximize the band depth (yes/no)"), cl::Hidden, 83 cl::init("yes"), cl::ZeroOrMore, cl::cat(PollyCategory)); 84 85 static cl::opt<int> DefaultTileSize( 86 "polly-default-tile-size", 87 cl::desc("The default tile size (if not enough were provided by" 88 " --polly-tile-sizes)"), 89 cl::Hidden, cl::init(32), cl::ZeroOrMore, cl::cat(PollyCategory)); 90 91 static cl::list<int> TileSizes("polly-tile-sizes", 92 cl::desc("A tile size" 93 " for each loop dimension, filled with" 94 " --polly-default-tile-size"), 95 cl::Hidden, cl::ZeroOrMore, cl::CommaSeparated, 96 cl::cat(PollyCategory)); 97 namespace { 98 99 class IslScheduleOptimizer : public ScopPass { 100 public: 101 static char ID; 102 explicit IslScheduleOptimizer() : ScopPass(ID) { LastSchedule = nullptr; } 103 104 ~IslScheduleOptimizer() { isl_schedule_free(LastSchedule); } 105 106 bool runOnScop(Scop &S) override; 107 void printScop(raw_ostream &OS, Scop &S) const override; 108 void getAnalysisUsage(AnalysisUsage &AU) const override; 109 110 private: 111 isl_schedule *LastSchedule; 112 113 /// @brief Decide if the @p NewSchedule is profitable for @p S. 114 /// 115 /// @param S The SCoP we optimize. 116 /// @param NewSchedule The new schedule we computed. 117 /// 118 /// @return True, if we believe @p NewSchedule is an improvement for @p S. 119 bool isProfitableSchedule(Scop &S, __isl_keep isl_union_map *NewSchedule); 120 121 /// @brief Pre-vectorizes one scheduling dimension of a schedule band. 122 /// 123 /// prevectSchedBand splits out the dimension DimToVectorize, tiles it and 124 /// sinks the resulting point loop. 125 /// 126 /// Example (DimToVectorize=0, VectorWidth=4): 127 /// 128 /// | Before transformation: 129 /// | 130 /// | A[i,j] -> [i,j] 131 /// | 132 /// | for (i = 0; i < 128; i++) 133 /// | for (j = 0; j < 128; j++) 134 /// | A(i,j); 135 /// 136 /// | After transformation: 137 /// | 138 /// | for (it = 0; it < 32; it+=1) 139 /// | for (j = 0; j < 128; j++) 140 /// | for (ip = 0; ip <= 3; ip++) 141 /// | A(4 * it + ip,j); 142 /// 143 /// The goal of this transformation is to create a trivially vectorizable 144 /// loop. This means a parallel loop at the innermost level that has a 145 /// constant number of iterations corresponding to the target vector width. 146 /// 147 /// This transformation creates a loop at the innermost level. The loop has 148 /// a constant number of iterations, if the number of loop iterations at 149 /// DimToVectorize can be divided by VectorWidth. The default VectorWidth is 150 /// currently constant and not yet target specific. This function does not 151 /// reason about parallelism. 152 static __isl_give isl_schedule_node * 153 prevectSchedBand(__isl_take isl_schedule_node *Node, unsigned DimToVectorize, 154 int VectorWidth = 4); 155 156 /// @brief Apply additional optimizations on the bands in the schedule tree. 157 /// 158 /// We are looking for an innermost band node and apply the following 159 /// transformations: 160 /// 161 /// - Tile the band 162 /// - if the band is tileable 163 /// - if the band has more than one loop dimension 164 /// 165 /// - Prevectorize the schedule of the band (or the point loop in case of 166 /// tiling). 167 /// - if vectorization is enabled 168 /// 169 /// @param Node The schedule node to (possibly) optimize. 170 /// @param User A pointer to forward some use information (currently unused). 171 static isl_schedule_node *optimizeBand(isl_schedule_node *Node, void *User); 172 173 /// @brief Apply post-scheduling transformations. 174 /// 175 /// This function applies a set of additional local transformations on the 176 /// schedule tree as it computed by the isl scheduler. Local transformations 177 /// applied include: 178 /// 179 /// - Tiling 180 /// - Prevectorization 181 /// 182 /// @param Schedule The schedule object post-transformations will be applied 183 /// on. 184 /// @returns The transformed schedule. 185 static __isl_give isl_schedule * 186 addPostTransforms(__isl_take isl_schedule *Schedule); 187 188 using llvm::Pass::doFinalization; 189 190 virtual bool doFinalization() override { 191 isl_schedule_free(LastSchedule); 192 LastSchedule = nullptr; 193 return true; 194 } 195 }; 196 } 197 198 char IslScheduleOptimizer::ID = 0; 199 200 __isl_give isl_schedule_node * 201 IslScheduleOptimizer::prevectSchedBand(__isl_take isl_schedule_node *Node, 202 unsigned DimToVectorize, 203 int VectorWidth) { 204 assert(isl_schedule_node_get_type(Node) == isl_schedule_node_band); 205 206 auto Space = isl_schedule_node_band_get_space(Node); 207 auto ScheduleDimensions = isl_space_dim(Space, isl_dim_set); 208 isl_space_free(Space); 209 assert(DimToVectorize < ScheduleDimensions); 210 211 if (DimToVectorize > 0) { 212 Node = isl_schedule_node_band_split(Node, DimToVectorize); 213 Node = isl_schedule_node_child(Node, 0); 214 } 215 if (DimToVectorize < ScheduleDimensions - 1) 216 Node = isl_schedule_node_band_split(Node, 1); 217 Space = isl_schedule_node_band_get_space(Node); 218 auto Sizes = isl_multi_val_zero(Space); 219 auto Ctx = isl_schedule_node_get_ctx(Node); 220 Sizes = 221 isl_multi_val_set_val(Sizes, 0, isl_val_int_from_si(Ctx, VectorWidth)); 222 Node = isl_schedule_node_band_tile(Node, Sizes); 223 Node = isl_schedule_node_child(Node, 0); 224 Node = isl_schedule_node_band_sink(Node); 225 Node = isl_schedule_node_child(Node, 0); 226 return Node; 227 } 228 229 isl_schedule_node *IslScheduleOptimizer::optimizeBand(isl_schedule_node *Node, 230 void *User) { 231 if (isl_schedule_node_get_type(Node) != isl_schedule_node_band) 232 return Node; 233 234 if (isl_schedule_node_n_children(Node) != 1) 235 return Node; 236 237 if (!isl_schedule_node_band_get_permutable(Node)) 238 return Node; 239 240 auto Space = isl_schedule_node_band_get_space(Node); 241 auto Dims = isl_space_dim(Space, isl_dim_set); 242 243 if (Dims <= 1) { 244 isl_space_free(Space); 245 return Node; 246 } 247 248 auto Child = isl_schedule_node_get_child(Node, 0); 249 auto Type = isl_schedule_node_get_type(Child); 250 isl_schedule_node_free(Child); 251 252 if (Type != isl_schedule_node_leaf) { 253 isl_space_free(Space); 254 return Node; 255 } 256 257 auto Sizes = isl_multi_val_zero(Space); 258 auto Ctx = isl_schedule_node_get_ctx(Node); 259 260 for (unsigned i = 0; i < Dims; i++) { 261 auto tileSize = TileSizes.size() > i ? TileSizes[i] : DefaultTileSize; 262 Sizes = isl_multi_val_set_val(Sizes, i, isl_val_int_from_si(Ctx, tileSize)); 263 } 264 265 isl_schedule_node *Res; 266 267 if (DisableTiling) { 268 isl_multi_val_free(Sizes); 269 Res = Node; 270 } else { 271 Res = isl_schedule_node_band_tile(Node, Sizes); 272 Res = isl_schedule_node_child(Res, 0); 273 } 274 275 if (PollyVectorizerChoice == VECTORIZER_NONE) 276 return Res; 277 278 for (int i = Dims - 1; i >= 0; i--) 279 if (isl_schedule_node_band_member_get_coincident(Res, i)) { 280 Res = IslScheduleOptimizer::prevectSchedBand(Res, i); 281 break; 282 } 283 284 return Res; 285 } 286 287 __isl_give isl_schedule * 288 IslScheduleOptimizer::addPostTransforms(__isl_take isl_schedule *Schedule) { 289 isl_schedule_node *Root = isl_schedule_get_root(Schedule); 290 isl_schedule_free(Schedule); 291 Root = isl_schedule_node_map_descendant_bottom_up( 292 Root, IslScheduleOptimizer::optimizeBand, NULL); 293 auto S = isl_schedule_node_get_schedule(Root); 294 isl_schedule_node_free(Root); 295 return S; 296 } 297 298 bool IslScheduleOptimizer::isProfitableSchedule( 299 Scop &S, __isl_keep isl_union_map *NewSchedule) { 300 // To understand if the schedule has been optimized we check if the schedule 301 // has changed at all. 302 // TODO: We can improve this by tracking if any necessarily beneficial 303 // transformations have been performed. This can e.g. be tiling, loop 304 // interchange, or ...) We can track this either at the place where the 305 // transformation has been performed or, in case of automatic ILP based 306 // optimizations, by comparing (yet to be defined) performance metrics 307 // before/after the scheduling optimizer 308 // (e.g., #stride-one accesses) 309 isl_union_map *OldSchedule = S.getSchedule(); 310 bool changed = !isl_union_map_is_equal(OldSchedule, NewSchedule); 311 isl_union_map_free(OldSchedule); 312 return changed; 313 } 314 315 bool IslScheduleOptimizer::runOnScop(Scop &S) { 316 317 // Skip empty SCoPs but still allow code generation as it will delete the 318 // loops present but not needed. 319 if (S.getSize() == 0) { 320 S.markAsOptimized(); 321 return false; 322 } 323 324 const Dependences &D = getAnalysis<DependenceInfo>().getDependences(); 325 326 if (!D.hasValidDependences()) 327 return false; 328 329 isl_schedule_free(LastSchedule); 330 LastSchedule = nullptr; 331 332 // Build input data. 333 int ValidityKinds = 334 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW; 335 int ProximityKinds; 336 337 if (OptimizeDeps == "all") 338 ProximityKinds = 339 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW; 340 else if (OptimizeDeps == "raw") 341 ProximityKinds = Dependences::TYPE_RAW; 342 else { 343 errs() << "Do not know how to optimize for '" << OptimizeDeps << "'" 344 << " Falling back to optimizing all dependences.\n"; 345 ProximityKinds = 346 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW; 347 } 348 349 isl_union_set *Domain = S.getDomains(); 350 351 if (!Domain) 352 return false; 353 354 isl_union_map *Validity = D.getDependences(ValidityKinds); 355 isl_union_map *Proximity = D.getDependences(ProximityKinds); 356 357 // Simplify the dependences by removing the constraints introduced by the 358 // domains. This can speed up the scheduling time significantly, as large 359 // constant coefficients will be removed from the dependences. The 360 // introduction of some additional dependences reduces the possible 361 // transformations, but in most cases, such transformation do not seem to be 362 // interesting anyway. In some cases this option may stop the scheduler to 363 // find any schedule. 364 if (SimplifyDeps == "yes") { 365 Validity = isl_union_map_gist_domain(Validity, isl_union_set_copy(Domain)); 366 Validity = isl_union_map_gist_range(Validity, isl_union_set_copy(Domain)); 367 Proximity = 368 isl_union_map_gist_domain(Proximity, isl_union_set_copy(Domain)); 369 Proximity = isl_union_map_gist_range(Proximity, isl_union_set_copy(Domain)); 370 } else if (SimplifyDeps != "no") { 371 errs() << "warning: Option -polly-opt-simplify-deps should either be 'yes' " 372 "or 'no'. Falling back to default: 'yes'\n"; 373 } 374 375 DEBUG(dbgs() << "\n\nCompute schedule from: "); 376 DEBUG(dbgs() << "Domain := " << stringFromIslObj(Domain) << ";\n"); 377 DEBUG(dbgs() << "Proximity := " << stringFromIslObj(Proximity) << ";\n"); 378 DEBUG(dbgs() << "Validity := " << stringFromIslObj(Validity) << ";\n"); 379 380 unsigned IslSerializeSCCs; 381 382 if (FusionStrategy == "max") { 383 IslSerializeSCCs = 0; 384 } else if (FusionStrategy == "min") { 385 IslSerializeSCCs = 1; 386 } else { 387 errs() << "warning: Unknown fusion strategy. Falling back to maximal " 388 "fusion.\n"; 389 IslSerializeSCCs = 0; 390 } 391 392 int IslMaximizeBands; 393 394 if (MaximizeBandDepth == "yes") { 395 IslMaximizeBands = 1; 396 } else if (MaximizeBandDepth == "no") { 397 IslMaximizeBands = 0; 398 } else { 399 errs() << "warning: Option -polly-opt-maximize-bands should either be 'yes'" 400 " or 'no'. Falling back to default: 'yes'\n"; 401 IslMaximizeBands = 1; 402 } 403 404 isl_options_set_schedule_serialize_sccs(S.getIslCtx(), IslSerializeSCCs); 405 isl_options_set_schedule_maximize_band_depth(S.getIslCtx(), IslMaximizeBands); 406 isl_options_set_schedule_max_constant_term(S.getIslCtx(), MaxConstantTerm); 407 isl_options_set_schedule_max_coefficient(S.getIslCtx(), MaxCoefficient); 408 isl_options_set_tile_scale_tile_loops(S.getIslCtx(), 0); 409 410 isl_options_set_on_error(S.getIslCtx(), ISL_ON_ERROR_CONTINUE); 411 412 isl_schedule_constraints *ScheduleConstraints; 413 ScheduleConstraints = isl_schedule_constraints_on_domain(Domain); 414 ScheduleConstraints = 415 isl_schedule_constraints_set_proximity(ScheduleConstraints, Proximity); 416 ScheduleConstraints = isl_schedule_constraints_set_validity( 417 ScheduleConstraints, isl_union_map_copy(Validity)); 418 ScheduleConstraints = 419 isl_schedule_constraints_set_coincidence(ScheduleConstraints, Validity); 420 isl_schedule *Schedule; 421 Schedule = isl_schedule_constraints_compute_schedule(ScheduleConstraints); 422 isl_options_set_on_error(S.getIslCtx(), ISL_ON_ERROR_ABORT); 423 424 // In cases the scheduler is not able to optimize the code, we just do not 425 // touch the schedule. 426 if (!Schedule) 427 return false; 428 429 DEBUG({ 430 auto *P = isl_printer_to_str(S.getIslCtx()); 431 P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK); 432 P = isl_printer_print_schedule(P, Schedule); 433 dbgs() << "NewScheduleTree: \n" << isl_printer_get_str(P) << "\n"; 434 isl_printer_free(P); 435 }); 436 437 isl_schedule *NewSchedule = addPostTransforms(Schedule); 438 isl_union_map *NewScheduleMap = isl_schedule_get_map(NewSchedule); 439 440 if (!isProfitableSchedule(S, NewScheduleMap)) { 441 isl_union_map_free(NewScheduleMap); 442 isl_schedule_free(NewSchedule); 443 return false; 444 } 445 446 S.setScheduleTree(NewSchedule); 447 S.markAsOptimized(); 448 449 isl_union_map_free(NewScheduleMap); 450 return false; 451 } 452 453 void IslScheduleOptimizer::printScop(raw_ostream &OS, Scop &) const { 454 isl_printer *p; 455 char *ScheduleStr; 456 457 OS << "Calculated schedule:\n"; 458 459 if (!LastSchedule) { 460 OS << "n/a\n"; 461 return; 462 } 463 464 p = isl_printer_to_str(isl_schedule_get_ctx(LastSchedule)); 465 p = isl_printer_print_schedule(p, LastSchedule); 466 ScheduleStr = isl_printer_get_str(p); 467 isl_printer_free(p); 468 469 OS << ScheduleStr << "\n"; 470 } 471 472 void IslScheduleOptimizer::getAnalysisUsage(AnalysisUsage &AU) const { 473 ScopPass::getAnalysisUsage(AU); 474 AU.addRequired<DependenceInfo>(); 475 } 476 477 Pass *polly::createIslScheduleOptimizerPass() { 478 return new IslScheduleOptimizer(); 479 } 480 481 INITIALIZE_PASS_BEGIN(IslScheduleOptimizer, "polly-opt-isl", 482 "Polly - Optimize schedule of SCoP", false, false); 483 INITIALIZE_PASS_DEPENDENCY(DependenceInfo); 484 INITIALIZE_PASS_DEPENDENCY(ScopInfo); 485 INITIALIZE_PASS_END(IslScheduleOptimizer, "polly-opt-isl", 486 "Polly - Optimize schedule of SCoP", false, false) 487