1 //===- ScheduleOptimizer.cpp - Calculate an optimized schedule ------------===// 2 // 3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. 4 // See https://llvm.org/LICENSE.txt for license information. 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 6 // 7 //===----------------------------------------------------------------------===// 8 // 9 // This pass generates an entirely new schedule tree from the data dependences 10 // and iteration domains. The new schedule tree is computed in two steps: 11 // 12 // 1) The isl scheduling optimizer is run 13 // 14 // The isl scheduling optimizer creates a new schedule tree that maximizes 15 // parallelism and tileability and minimizes data-dependence distances. The 16 // algorithm used is a modified version of the ``Pluto'' algorithm: 17 // 18 // U. Bondhugula, A. Hartono, J. Ramanujam, and P. Sadayappan. 19 // A Practical Automatic Polyhedral Parallelizer and Locality Optimizer. 20 // In Proceedings of the 2008 ACM SIGPLAN Conference On Programming Language 21 // Design and Implementation, PLDI ’08, pages 101–113. ACM, 2008. 22 // 23 // 2) A set of post-scheduling transformations is applied on the schedule tree. 24 // 25 // These optimizations include: 26 // 27 // - Tiling of the innermost tilable bands 28 // - Prevectorization - The choice of a possible outer loop that is strip-mined 29 // to the innermost level to enable inner-loop 30 // vectorization. 31 // - Some optimizations for spatial locality are also planned. 32 // 33 // For a detailed description of the schedule tree itself please see section 6 34 // of: 35 // 36 // Polyhedral AST generation is more than scanning polyhedra 37 // Tobias Grosser, Sven Verdoolaege, Albert Cohen 38 // ACM Transactions on Programming Languages and Systems (TOPLAS), 39 // 37(4), July 2015 40 // http://www.grosser.es/#pub-polyhedral-AST-generation 41 // 42 // This publication also contains a detailed discussion of the different options 43 // for polyhedral loop unrolling, full/partial tile separation and other uses 44 // of the schedule tree. 45 // 46 //===----------------------------------------------------------------------===// 47 48 #include "polly/ScheduleOptimizer.h" 49 #include "polly/CodeGen/CodeGeneration.h" 50 #include "polly/DependenceInfo.h" 51 #include "polly/ManualOptimizer.h" 52 #include "polly/MatmulOptimizer.h" 53 #include "polly/Options.h" 54 #include "polly/ScheduleTreeTransform.h" 55 #include "polly/Support/ISLOStream.h" 56 #include "polly/Support/ISLTools.h" 57 #include "llvm/ADT/Sequence.h" 58 #include "llvm/ADT/Statistic.h" 59 #include "llvm/Analysis/OptimizationRemarkEmitter.h" 60 #include "llvm/InitializePasses.h" 61 #include "llvm/Support/CommandLine.h" 62 #include "isl/options.h" 63 64 using namespace llvm; 65 using namespace polly; 66 67 namespace llvm { 68 class Loop; 69 class Module; 70 } // namespace llvm 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::cat(PollyCategory)); 78 79 static cl::opt<std::string> 80 SimplifyDeps("polly-opt-simplify-deps", 81 cl::desc("Dependences should be simplified (yes/no)"), 82 cl::Hidden, cl::init("yes"), cl::cat(PollyCategory)); 83 84 static cl::opt<int> MaxConstantTerm( 85 "polly-opt-max-constant-term", 86 cl::desc("The maximal constant term allowed (-1 is unlimited)"), cl::Hidden, 87 cl::init(20), cl::cat(PollyCategory)); 88 89 static cl::opt<int> MaxCoefficient( 90 "polly-opt-max-coefficient", 91 cl::desc("The maximal coefficient allowed (-1 is unlimited)"), cl::Hidden, 92 cl::init(20), cl::cat(PollyCategory)); 93 94 static cl::opt<std::string> 95 MaximizeBandDepth("polly-opt-maximize-bands", 96 cl::desc("Maximize the band depth (yes/no)"), cl::Hidden, 97 cl::init("yes"), cl::cat(PollyCategory)); 98 99 static cl::opt<bool> 100 GreedyFusion("polly-loopfusion-greedy", 101 cl::desc("Aggressively try to fuse everything"), cl::Hidden, 102 cl::cat(PollyCategory)); 103 104 static cl::opt<std::string> OuterCoincidence( 105 "polly-opt-outer-coincidence", 106 cl::desc("Try to construct schedules where the outer member of each band " 107 "satisfies the coincidence constraints (yes/no)"), 108 cl::Hidden, cl::init("no"), cl::cat(PollyCategory)); 109 110 static cl::opt<int> PrevectorWidth( 111 "polly-prevect-width", 112 cl::desc( 113 "The number of loop iterations to strip-mine for pre-vectorization"), 114 cl::Hidden, cl::init(4), cl::cat(PollyCategory)); 115 116 static cl::opt<bool> FirstLevelTiling("polly-tiling", 117 cl::desc("Enable loop tiling"), 118 cl::init(true), cl::cat(PollyCategory)); 119 120 static cl::opt<int> FirstLevelDefaultTileSize( 121 "polly-default-tile-size", 122 cl::desc("The default tile size (if not enough were provided by" 123 " --polly-tile-sizes)"), 124 cl::Hidden, cl::init(32), cl::cat(PollyCategory)); 125 126 static cl::list<int> 127 FirstLevelTileSizes("polly-tile-sizes", 128 cl::desc("A tile size for each loop dimension, filled " 129 "with --polly-default-tile-size"), 130 cl::Hidden, cl::CommaSeparated, cl::cat(PollyCategory)); 131 132 static cl::opt<bool> 133 SecondLevelTiling("polly-2nd-level-tiling", 134 cl::desc("Enable a 2nd level loop of loop tiling"), 135 cl::cat(PollyCategory)); 136 137 static cl::opt<int> SecondLevelDefaultTileSize( 138 "polly-2nd-level-default-tile-size", 139 cl::desc("The default 2nd-level tile size (if not enough were provided by" 140 " --polly-2nd-level-tile-sizes)"), 141 cl::Hidden, cl::init(16), cl::cat(PollyCategory)); 142 143 static cl::list<int> 144 SecondLevelTileSizes("polly-2nd-level-tile-sizes", 145 cl::desc("A tile size for each loop dimension, filled " 146 "with --polly-default-tile-size"), 147 cl::Hidden, cl::CommaSeparated, 148 cl::cat(PollyCategory)); 149 150 static cl::opt<bool> RegisterTiling("polly-register-tiling", 151 cl::desc("Enable register tiling"), 152 cl::cat(PollyCategory)); 153 154 static cl::opt<int> RegisterDefaultTileSize( 155 "polly-register-tiling-default-tile-size", 156 cl::desc("The default register tile size (if not enough were provided by" 157 " --polly-register-tile-sizes)"), 158 cl::Hidden, cl::init(2), cl::cat(PollyCategory)); 159 160 static cl::list<int> 161 RegisterTileSizes("polly-register-tile-sizes", 162 cl::desc("A tile size for each loop dimension, filled " 163 "with --polly-register-tile-size"), 164 cl::Hidden, cl::CommaSeparated, cl::cat(PollyCategory)); 165 166 static cl::opt<bool> PragmaBasedOpts( 167 "polly-pragma-based-opts", 168 cl::desc("Apply user-directed transformation from metadata"), 169 cl::init(true), cl::cat(PollyCategory)); 170 171 static cl::opt<bool> EnableReschedule("polly-reschedule", 172 cl::desc("Optimize SCoPs using ISL"), 173 cl::init(true), cl::cat(PollyCategory)); 174 175 static cl::opt<bool> 176 PMBasedOpts("polly-pattern-matching-based-opts", 177 cl::desc("Perform optimizations based on pattern matching"), 178 cl::init(true), cl::cat(PollyCategory)); 179 180 static cl::opt<bool> 181 EnablePostopts("polly-postopts", 182 cl::desc("Apply post-rescheduling optimizations such as " 183 "tiling (requires -polly-reschedule)"), 184 cl::init(true), cl::cat(PollyCategory)); 185 186 static cl::opt<bool> OptimizedScops( 187 "polly-optimized-scops", 188 cl::desc("Polly - Dump polyhedral description of Scops optimized with " 189 "the isl scheduling optimizer and the set of post-scheduling " 190 "transformations is applied on the schedule tree"), 191 cl::cat(PollyCategory)); 192 193 STATISTIC(ScopsProcessed, "Number of scops processed"); 194 STATISTIC(ScopsRescheduled, "Number of scops rescheduled"); 195 STATISTIC(ScopsOptimized, "Number of scops optimized"); 196 197 STATISTIC(NumAffineLoopsOptimized, "Number of affine loops optimized"); 198 STATISTIC(NumBoxedLoopsOptimized, "Number of boxed loops optimized"); 199 200 #define THREE_STATISTICS(VARNAME, DESC) \ 201 static Statistic VARNAME[3] = { \ 202 {DEBUG_TYPE, #VARNAME "0", DESC " (original)"}, \ 203 {DEBUG_TYPE, #VARNAME "1", DESC " (after scheduler)"}, \ 204 {DEBUG_TYPE, #VARNAME "2", DESC " (after optimizer)"}} 205 206 THREE_STATISTICS(NumBands, "Number of bands"); 207 THREE_STATISTICS(NumBandMembers, "Number of band members"); 208 THREE_STATISTICS(NumCoincident, "Number of coincident band members"); 209 THREE_STATISTICS(NumPermutable, "Number of permutable bands"); 210 THREE_STATISTICS(NumFilters, "Number of filter nodes"); 211 THREE_STATISTICS(NumExtension, "Number of extension nodes"); 212 213 STATISTIC(FirstLevelTileOpts, "Number of first level tiling applied"); 214 STATISTIC(SecondLevelTileOpts, "Number of second level tiling applied"); 215 STATISTIC(RegisterTileOpts, "Number of register tiling applied"); 216 STATISTIC(PrevectOpts, "Number of strip-mining for prevectorization applied"); 217 STATISTIC(MatMulOpts, 218 "Number of matrix multiplication patterns detected and optimized"); 219 220 namespace { 221 /// Additional parameters of the schedule optimizer. 222 /// 223 /// Target Transform Info and the SCoP dependencies used by the schedule 224 /// optimizer. 225 struct OptimizerAdditionalInfoTy { 226 const llvm::TargetTransformInfo *TTI; 227 const Dependences *D; 228 bool PatternOpts; 229 bool Postopts; 230 bool Prevect; 231 }; 232 233 class ScheduleTreeOptimizer final { 234 public: 235 /// Apply schedule tree transformations. 236 /// 237 /// This function takes an (possibly already optimized) schedule tree and 238 /// applies a set of additional optimizations on the schedule tree. The 239 /// transformations applied include: 240 /// 241 /// - Pattern-based optimizations 242 /// - Tiling 243 /// - Prevectorization 244 /// 245 /// @param Schedule The schedule object the transformations will be applied 246 /// to. 247 /// @param OAI Target Transform Info and the SCoP dependencies. 248 /// @returns The transformed schedule. 249 static isl::schedule 250 optimizeSchedule(isl::schedule Schedule, 251 const OptimizerAdditionalInfoTy *OAI = nullptr); 252 253 /// Apply schedule tree transformations. 254 /// 255 /// This function takes a node in an (possibly already optimized) schedule 256 /// tree and applies a set of additional optimizations on this schedule tree 257 /// node and its descendants. The transformations applied include: 258 /// 259 /// - Pattern-based optimizations 260 /// - Tiling 261 /// - Prevectorization 262 /// 263 /// @param Node The schedule object post-transformations will be applied to. 264 /// @param OAI Target Transform Info and the SCoP dependencies. 265 /// @returns The transformed schedule. 266 static isl::schedule_node 267 optimizeScheduleNode(isl::schedule_node Node, 268 const OptimizerAdditionalInfoTy *OAI = nullptr); 269 270 /// Decide if the @p NewSchedule is profitable for @p S. 271 /// 272 /// @param S The SCoP we optimize. 273 /// @param NewSchedule The new schedule we computed. 274 /// 275 /// @return True, if we believe @p NewSchedule is an improvement for @p S. 276 static bool isProfitableSchedule(polly::Scop &S, isl::schedule NewSchedule); 277 278 /// Isolate a set of partial tile prefixes. 279 /// 280 /// This set should ensure that it contains only partial tile prefixes that 281 /// have exactly VectorWidth iterations. 282 /// 283 /// @param Node A schedule node band, which is a parent of a band node, 284 /// that contains a vector loop. 285 /// @return Modified isl_schedule_node. 286 static isl::schedule_node isolateFullPartialTiles(isl::schedule_node Node, 287 int VectorWidth); 288 289 private: 290 /// Check if this node is a band node we want to tile. 291 /// 292 /// We look for innermost band nodes where individual dimensions are marked as 293 /// permutable. 294 /// 295 /// @param Node The node to check. 296 static bool isTileableBandNode(isl::schedule_node Node); 297 298 /// Pre-vectorizes one scheduling dimension of a schedule band. 299 /// 300 /// prevectSchedBand splits out the dimension DimToVectorize, tiles it and 301 /// sinks the resulting point loop. 302 /// 303 /// Example (DimToVectorize=0, VectorWidth=4): 304 /// 305 /// | Before transformation: 306 /// | 307 /// | A[i,j] -> [i,j] 308 /// | 309 /// | for (i = 0; i < 128; i++) 310 /// | for (j = 0; j < 128; j++) 311 /// | A(i,j); 312 /// 313 /// | After transformation: 314 /// | 315 /// | for (it = 0; it < 32; it+=1) 316 /// | for (j = 0; j < 128; j++) 317 /// | for (ip = 0; ip <= 3; ip++) 318 /// | A(4 * it + ip,j); 319 /// 320 /// The goal of this transformation is to create a trivially vectorizable 321 /// loop. This means a parallel loop at the innermost level that has a 322 /// constant number of iterations corresponding to the target vector width. 323 /// 324 /// This transformation creates a loop at the innermost level. The loop has 325 /// a constant number of iterations, if the number of loop iterations at 326 /// DimToVectorize can be divided by VectorWidth. The default VectorWidth is 327 /// currently constant and not yet target specific. This function does not 328 /// reason about parallelism. 329 static isl::schedule_node prevectSchedBand(isl::schedule_node Node, 330 unsigned DimToVectorize, 331 int VectorWidth); 332 333 /// Apply additional optimizations on the bands in the schedule tree. 334 /// 335 /// We are looking for an innermost band node and apply the following 336 /// transformations: 337 /// 338 /// - Tile the band 339 /// - if the band is tileable 340 /// - if the band has more than one loop dimension 341 /// 342 /// - Prevectorize the schedule of the band (or the point loop in case of 343 /// tiling). 344 /// - if vectorization is enabled 345 /// 346 /// @param Node The schedule node to (possibly) optimize. 347 /// @param User A pointer to forward some use information 348 /// (currently unused). 349 static isl_schedule_node *optimizeBand(isl_schedule_node *Node, void *User); 350 351 /// Apply tiling optimizations on the bands in the schedule tree. 352 /// 353 /// @param Node The schedule node to (possibly) optimize. 354 static isl::schedule_node applyTileBandOpt(isl::schedule_node Node); 355 356 /// Apply prevectorization on the bands in the schedule tree. 357 /// 358 /// @param Node The schedule node to (possibly) prevectorize. 359 static isl::schedule_node applyPrevectBandOpt(isl::schedule_node Node); 360 }; 361 362 isl::schedule_node 363 ScheduleTreeOptimizer::isolateFullPartialTiles(isl::schedule_node Node, 364 int VectorWidth) { 365 assert(isl_schedule_node_get_type(Node.get()) == isl_schedule_node_band); 366 Node = Node.child(0).child(0); 367 isl::union_map SchedRelUMap = Node.get_prefix_schedule_relation(); 368 isl::union_set ScheduleRangeUSet = SchedRelUMap.range(); 369 isl::set ScheduleRange{ScheduleRangeUSet}; 370 isl::set IsolateDomain = getPartialTilePrefixes(ScheduleRange, VectorWidth); 371 auto AtomicOption = getDimOptions(IsolateDomain.ctx(), "atomic"); 372 isl::union_set IsolateOption = getIsolateOptions(IsolateDomain, 1); 373 Node = Node.parent().parent(); 374 isl::union_set Options = IsolateOption.unite(AtomicOption); 375 isl::schedule_node_band Result = 376 Node.as<isl::schedule_node_band>().set_ast_build_options(Options); 377 return Result; 378 } 379 380 struct InsertSimdMarkers final : ScheduleNodeRewriter<InsertSimdMarkers> { 381 isl::schedule_node visitBand(isl::schedule_node_band Band) { 382 isl::schedule_node Node = visitChildren(Band); 383 384 // Only add SIMD markers to innermost bands. 385 if (!Node.first_child().isa<isl::schedule_node_leaf>()) 386 return Node; 387 388 isl::id LoopMarker = isl::id::alloc(Band.ctx(), "SIMD", nullptr); 389 return Band.insert_mark(LoopMarker); 390 } 391 }; 392 393 isl::schedule_node ScheduleTreeOptimizer::prevectSchedBand( 394 isl::schedule_node Node, unsigned DimToVectorize, int VectorWidth) { 395 assert(isl_schedule_node_get_type(Node.get()) == isl_schedule_node_band); 396 397 auto Space = isl::manage(isl_schedule_node_band_get_space(Node.get())); 398 unsigned ScheduleDimensions = unsignedFromIslSize(Space.dim(isl::dim::set)); 399 assert(DimToVectorize < ScheduleDimensions); 400 401 if (DimToVectorize > 0) { 402 Node = isl::manage( 403 isl_schedule_node_band_split(Node.release(), DimToVectorize)); 404 Node = Node.child(0); 405 } 406 if (DimToVectorize < ScheduleDimensions - 1) 407 Node = isl::manage(isl_schedule_node_band_split(Node.release(), 1)); 408 Space = isl::manage(isl_schedule_node_band_get_space(Node.get())); 409 auto Sizes = isl::multi_val::zero(Space); 410 Sizes = Sizes.set_val(0, isl::val(Node.ctx(), VectorWidth)); 411 Node = 412 isl::manage(isl_schedule_node_band_tile(Node.release(), Sizes.release())); 413 Node = isolateFullPartialTiles(Node, VectorWidth); 414 Node = Node.child(0); 415 // Make sure the "trivially vectorizable loop" is not unrolled. Otherwise, 416 // we will have troubles to match it in the backend. 417 Node = Node.as<isl::schedule_node_band>().set_ast_build_options( 418 isl::union_set(Node.ctx(), "{ unroll[x]: 1 = 0 }")); 419 420 // Sink the inner loop into the smallest possible statements to make them 421 // represent a single vector instruction if possible. 422 Node = isl::manage(isl_schedule_node_band_sink(Node.release())); 423 424 // Add SIMD markers to those vector statements. 425 InsertSimdMarkers SimdMarkerInserter; 426 Node = SimdMarkerInserter.visit(Node); 427 428 PrevectOpts++; 429 return Node.parent(); 430 } 431 432 static bool isSimpleInnermostBand(const isl::schedule_node &Node) { 433 assert(isl_schedule_node_get_type(Node.get()) == isl_schedule_node_band); 434 assert(isl_schedule_node_n_children(Node.get()) == 1); 435 436 auto ChildType = isl_schedule_node_get_type(Node.child(0).get()); 437 438 if (ChildType == isl_schedule_node_leaf) 439 return true; 440 441 if (ChildType != isl_schedule_node_sequence) 442 return false; 443 444 auto Sequence = Node.child(0); 445 446 for (int c = 0, nc = isl_schedule_node_n_children(Sequence.get()); c < nc; 447 ++c) { 448 auto Child = Sequence.child(c); 449 if (isl_schedule_node_get_type(Child.get()) != isl_schedule_node_filter) 450 return false; 451 if (isl_schedule_node_get_type(Child.child(0).get()) != 452 isl_schedule_node_leaf) 453 return false; 454 } 455 return true; 456 } 457 458 bool ScheduleTreeOptimizer::isTileableBandNode(isl::schedule_node Node) { 459 if (isl_schedule_node_get_type(Node.get()) != isl_schedule_node_band) 460 return false; 461 462 if (isl_schedule_node_n_children(Node.get()) != 1) 463 return false; 464 465 if (!isl_schedule_node_band_get_permutable(Node.get())) 466 return false; 467 468 auto Space = isl::manage(isl_schedule_node_band_get_space(Node.get())); 469 470 if (unsignedFromIslSize(Space.dim(isl::dim::set)) <= 1u) 471 return false; 472 473 return isSimpleInnermostBand(Node); 474 } 475 476 __isl_give isl::schedule_node 477 ScheduleTreeOptimizer::applyTileBandOpt(isl::schedule_node Node) { 478 if (FirstLevelTiling) { 479 Node = tileNode(Node, "1st level tiling", FirstLevelTileSizes, 480 FirstLevelDefaultTileSize); 481 FirstLevelTileOpts++; 482 } 483 484 if (SecondLevelTiling) { 485 Node = tileNode(Node, "2nd level tiling", SecondLevelTileSizes, 486 SecondLevelDefaultTileSize); 487 SecondLevelTileOpts++; 488 } 489 490 if (RegisterTiling) { 491 Node = 492 applyRegisterTiling(Node, RegisterTileSizes, RegisterDefaultTileSize); 493 RegisterTileOpts++; 494 } 495 496 return Node; 497 } 498 499 isl::schedule_node 500 ScheduleTreeOptimizer::applyPrevectBandOpt(isl::schedule_node Node) { 501 auto Space = isl::manage(isl_schedule_node_band_get_space(Node.get())); 502 int Dims = unsignedFromIslSize(Space.dim(isl::dim::set)); 503 504 for (int i = Dims - 1; i >= 0; i--) 505 if (Node.as<isl::schedule_node_band>().member_get_coincident(i)) { 506 Node = prevectSchedBand(Node, i, PrevectorWidth); 507 break; 508 } 509 510 return Node; 511 } 512 513 __isl_give isl_schedule_node * 514 ScheduleTreeOptimizer::optimizeBand(__isl_take isl_schedule_node *NodeArg, 515 void *User) { 516 const OptimizerAdditionalInfoTy *OAI = 517 static_cast<const OptimizerAdditionalInfoTy *>(User); 518 assert(OAI && "Expecting optimization options"); 519 520 isl::schedule_node Node = isl::manage(NodeArg); 521 if (!isTileableBandNode(Node)) 522 return Node.release(); 523 524 if (OAI->PatternOpts) { 525 isl::schedule_node PatternOptimizedSchedule = 526 tryOptimizeMatMulPattern(Node, OAI->TTI, OAI->D); 527 if (!PatternOptimizedSchedule.is_null()) { 528 MatMulOpts++; 529 return PatternOptimizedSchedule.release(); 530 } 531 } 532 533 if (OAI->Postopts) 534 Node = applyTileBandOpt(Node); 535 536 if (OAI->Prevect) { 537 // FIXME: Prevectorization requirements are different from those checked by 538 // isTileableBandNode. 539 Node = applyPrevectBandOpt(Node); 540 } 541 542 return Node.release(); 543 } 544 545 isl::schedule 546 ScheduleTreeOptimizer::optimizeSchedule(isl::schedule Schedule, 547 const OptimizerAdditionalInfoTy *OAI) { 548 auto Root = Schedule.get_root(); 549 Root = optimizeScheduleNode(Root, OAI); 550 return Root.get_schedule(); 551 } 552 553 isl::schedule_node ScheduleTreeOptimizer::optimizeScheduleNode( 554 isl::schedule_node Node, const OptimizerAdditionalInfoTy *OAI) { 555 Node = isl::manage(isl_schedule_node_map_descendant_bottom_up( 556 Node.release(), optimizeBand, 557 const_cast<void *>(static_cast<const void *>(OAI)))); 558 return Node; 559 } 560 561 bool ScheduleTreeOptimizer::isProfitableSchedule(Scop &S, 562 isl::schedule NewSchedule) { 563 // To understand if the schedule has been optimized we check if the schedule 564 // has changed at all. 565 // TODO: We can improve this by tracking if any necessarily beneficial 566 // transformations have been performed. This can e.g. be tiling, loop 567 // interchange, or ...) We can track this either at the place where the 568 // transformation has been performed or, in case of automatic ILP based 569 // optimizations, by comparing (yet to be defined) performance metrics 570 // before/after the scheduling optimizer 571 // (e.g., #stride-one accesses) 572 // FIXME: A schedule tree whose union_map-conversion is identical to the 573 // original schedule map may still allow for parallelization, i.e. can still 574 // be profitable. 575 auto NewScheduleMap = NewSchedule.get_map(); 576 auto OldSchedule = S.getSchedule(); 577 assert(!OldSchedule.is_null() && 578 "Only IslScheduleOptimizer can insert extension nodes " 579 "that make Scop::getSchedule() return nullptr."); 580 bool changed = !OldSchedule.is_equal(NewScheduleMap); 581 return changed; 582 } 583 584 class IslScheduleOptimizerWrapperPass final : public ScopPass { 585 public: 586 static char ID; 587 588 explicit IslScheduleOptimizerWrapperPass() : ScopPass(ID) {} 589 590 /// Optimize the schedule of the SCoP @p S. 591 bool runOnScop(Scop &S) override; 592 593 /// Print the new schedule for the SCoP @p S. 594 void printScop(raw_ostream &OS, Scop &S) const override; 595 596 /// Register all analyses and transformation required. 597 void getAnalysisUsage(AnalysisUsage &AU) const override; 598 599 /// Release the internal memory. 600 void releaseMemory() override { 601 LastSchedule = {}; 602 IslCtx.reset(); 603 } 604 605 private: 606 std::shared_ptr<isl_ctx> IslCtx; 607 isl::schedule LastSchedule; 608 }; 609 610 char IslScheduleOptimizerWrapperPass::ID = 0; 611 612 #ifndef NDEBUG 613 static void printSchedule(llvm::raw_ostream &OS, const isl::schedule &Schedule, 614 StringRef Desc) { 615 isl::ctx Ctx = Schedule.ctx(); 616 isl_printer *P = isl_printer_to_str(Ctx.get()); 617 P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK); 618 P = isl_printer_print_schedule(P, Schedule.get()); 619 char *Str = isl_printer_get_str(P); 620 OS << Desc << ": \n" << Str << "\n"; 621 free(Str); 622 isl_printer_free(P); 623 } 624 #endif 625 626 /// Collect statistics for the schedule tree. 627 /// 628 /// @param Schedule The schedule tree to analyze. If not a schedule tree it is 629 /// ignored. 630 /// @param Version The version of the schedule tree that is analyzed. 631 /// 0 for the original schedule tree before any transformation. 632 /// 1 for the schedule tree after isl's rescheduling. 633 /// 2 for the schedule tree after optimizations are applied 634 /// (tiling, pattern matching) 635 static void walkScheduleTreeForStatistics(isl::schedule Schedule, int Version) { 636 auto Root = Schedule.get_root(); 637 if (Root.is_null()) 638 return; 639 640 isl_schedule_node_foreach_descendant_top_down( 641 Root.get(), 642 [](__isl_keep isl_schedule_node *nodeptr, void *user) -> isl_bool { 643 isl::schedule_node Node = isl::manage_copy(nodeptr); 644 int Version = *static_cast<int *>(user); 645 646 switch (isl_schedule_node_get_type(Node.get())) { 647 case isl_schedule_node_band: { 648 NumBands[Version]++; 649 if (isl_schedule_node_band_get_permutable(Node.get()) == 650 isl_bool_true) 651 NumPermutable[Version]++; 652 653 int CountMembers = isl_schedule_node_band_n_member(Node.get()); 654 NumBandMembers[Version] += CountMembers; 655 for (int i = 0; i < CountMembers; i += 1) { 656 if (Node.as<isl::schedule_node_band>().member_get_coincident(i)) 657 NumCoincident[Version]++; 658 } 659 break; 660 } 661 662 case isl_schedule_node_filter: 663 NumFilters[Version]++; 664 break; 665 666 case isl_schedule_node_extension: 667 NumExtension[Version]++; 668 break; 669 670 default: 671 break; 672 } 673 674 return isl_bool_true; 675 }, 676 &Version); 677 } 678 679 static bool runIslScheduleOptimizer( 680 Scop &S, 681 function_ref<const Dependences &(Dependences::AnalysisLevel)> GetDeps, 682 TargetTransformInfo *TTI, OptimizationRemarkEmitter *ORE, 683 isl::schedule &LastSchedule) { 684 685 // Skip SCoPs in case they're already optimised by PPCGCodeGeneration 686 if (S.isToBeSkipped()) 687 return false; 688 689 // Skip empty SCoPs but still allow code generation as it will delete the 690 // loops present but not needed. 691 if (S.getSize() == 0) { 692 S.markAsOptimized(); 693 return false; 694 } 695 696 ScopsProcessed++; 697 698 // Schedule without optimizations. 699 isl::schedule Schedule = S.getScheduleTree(); 700 walkScheduleTreeForStatistics(S.getScheduleTree(), 0); 701 LLVM_DEBUG(printSchedule(dbgs(), Schedule, "Original schedule tree")); 702 703 bool HasUserTransformation = false; 704 if (PragmaBasedOpts) { 705 isl::schedule ManuallyTransformed = applyManualTransformations( 706 &S, Schedule, GetDeps(Dependences::AL_Statement), ORE); 707 if (ManuallyTransformed.is_null()) { 708 LLVM_DEBUG(dbgs() << "Error during manual optimization\n"); 709 return false; 710 } 711 712 if (ManuallyTransformed.get() != Schedule.get()) { 713 // User transformations have precedence over other transformations. 714 HasUserTransformation = true; 715 Schedule = std::move(ManuallyTransformed); 716 LLVM_DEBUG( 717 printSchedule(dbgs(), Schedule, "After manual transformations")); 718 } 719 } 720 721 // Only continue if either manual transformations have been applied or we are 722 // allowed to apply heuristics. 723 // TODO: Detect disabled heuristics and no user-directed transformation 724 // metadata earlier in ScopDetection. 725 if (!HasUserTransformation && S.hasDisableHeuristicsHint()) { 726 LLVM_DEBUG(dbgs() << "Heuristic optimizations disabled by metadata\n"); 727 return false; 728 } 729 730 // Get dependency analysis. 731 const Dependences &D = GetDeps(Dependences::AL_Statement); 732 if (D.getSharedIslCtx() != S.getSharedIslCtx()) { 733 LLVM_DEBUG(dbgs() << "DependenceInfo for another SCoP/isl_ctx\n"); 734 return false; 735 } 736 if (!D.hasValidDependences()) { 737 LLVM_DEBUG(dbgs() << "Dependency information not available\n"); 738 return false; 739 } 740 741 // Apply ISL's algorithm only if not overriden by the user. Note that 742 // post-rescheduling optimizations (tiling, pattern-based, prevectorization) 743 // rely on the coincidence/permutable annotations on schedule tree bands that 744 // are added by the rescheduling analyzer. Therefore, disabling the 745 // rescheduler implicitly also disables these optimizations. 746 if (!EnableReschedule) { 747 LLVM_DEBUG(dbgs() << "Skipping rescheduling due to command line option\n"); 748 } else if (HasUserTransformation) { 749 LLVM_DEBUG( 750 dbgs() << "Skipping rescheduling due to manual transformation\n"); 751 } else { 752 // Build input data. 753 int ValidityKinds = 754 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW; 755 int ProximityKinds; 756 757 if (OptimizeDeps == "all") 758 ProximityKinds = 759 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW; 760 else if (OptimizeDeps == "raw") 761 ProximityKinds = Dependences::TYPE_RAW; 762 else { 763 errs() << "Do not know how to optimize for '" << OptimizeDeps << "'" 764 << " Falling back to optimizing all dependences.\n"; 765 ProximityKinds = 766 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW; 767 } 768 769 isl::union_set Domain = S.getDomains(); 770 771 if (Domain.is_null()) 772 return false; 773 774 isl::union_map Validity = D.getDependences(ValidityKinds); 775 isl::union_map Proximity = D.getDependences(ProximityKinds); 776 777 // Simplify the dependences by removing the constraints introduced by the 778 // domains. This can speed up the scheduling time significantly, as large 779 // constant coefficients will be removed from the dependences. The 780 // introduction of some additional dependences reduces the possible 781 // transformations, but in most cases, such transformation do not seem to be 782 // interesting anyway. In some cases this option may stop the scheduler to 783 // find any schedule. 784 if (SimplifyDeps == "yes") { 785 Validity = Validity.gist_domain(Domain); 786 Validity = Validity.gist_range(Domain); 787 Proximity = Proximity.gist_domain(Domain); 788 Proximity = Proximity.gist_range(Domain); 789 } else if (SimplifyDeps != "no") { 790 errs() 791 << "warning: Option -polly-opt-simplify-deps should either be 'yes' " 792 "or 'no'. Falling back to default: 'yes'\n"; 793 } 794 795 LLVM_DEBUG(dbgs() << "\n\nCompute schedule from: "); 796 LLVM_DEBUG(dbgs() << "Domain := " << Domain << ";\n"); 797 LLVM_DEBUG(dbgs() << "Proximity := " << Proximity << ";\n"); 798 LLVM_DEBUG(dbgs() << "Validity := " << Validity << ";\n"); 799 800 int IslMaximizeBands; 801 if (MaximizeBandDepth == "yes") { 802 IslMaximizeBands = 1; 803 } else if (MaximizeBandDepth == "no") { 804 IslMaximizeBands = 0; 805 } else { 806 errs() 807 << "warning: Option -polly-opt-maximize-bands should either be 'yes'" 808 " or 'no'. Falling back to default: 'yes'\n"; 809 IslMaximizeBands = 1; 810 } 811 812 int IslOuterCoincidence; 813 if (OuterCoincidence == "yes") { 814 IslOuterCoincidence = 1; 815 } else if (OuterCoincidence == "no") { 816 IslOuterCoincidence = 0; 817 } else { 818 errs() << "warning: Option -polly-opt-outer-coincidence should either be " 819 "'yes' or 'no'. Falling back to default: 'no'\n"; 820 IslOuterCoincidence = 0; 821 } 822 823 isl_ctx *Ctx = S.getIslCtx().get(); 824 825 isl_options_set_schedule_outer_coincidence(Ctx, IslOuterCoincidence); 826 isl_options_set_schedule_maximize_band_depth(Ctx, IslMaximizeBands); 827 isl_options_set_schedule_max_constant_term(Ctx, MaxConstantTerm); 828 isl_options_set_schedule_max_coefficient(Ctx, MaxCoefficient); 829 isl_options_set_tile_scale_tile_loops(Ctx, 0); 830 831 auto OnErrorStatus = isl_options_get_on_error(Ctx); 832 isl_options_set_on_error(Ctx, ISL_ON_ERROR_CONTINUE); 833 834 auto SC = isl::schedule_constraints::on_domain(Domain); 835 SC = SC.set_proximity(Proximity); 836 SC = SC.set_validity(Validity); 837 SC = SC.set_coincidence(Validity); 838 Schedule = SC.compute_schedule(); 839 isl_options_set_on_error(Ctx, OnErrorStatus); 840 841 ScopsRescheduled++; 842 LLVM_DEBUG(printSchedule(dbgs(), Schedule, "After rescheduling")); 843 } 844 845 walkScheduleTreeForStatistics(Schedule, 1); 846 847 // In cases the scheduler is not able to optimize the code, we just do not 848 // touch the schedule. 849 if (Schedule.is_null()) 850 return false; 851 852 if (GreedyFusion) { 853 isl::union_map Validity = D.getDependences( 854 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW); 855 Schedule = applyGreedyFusion(Schedule, Validity); 856 assert(!Schedule.is_null()); 857 } 858 859 // Apply post-rescheduling optimizations (if enabled) and/or prevectorization. 860 const OptimizerAdditionalInfoTy OAI = { 861 TTI, const_cast<Dependences *>(&D), 862 /*PatternOpts=*/!HasUserTransformation && PMBasedOpts, 863 /*Postopts=*/!HasUserTransformation && EnablePostopts, 864 /*Prevect=*/PollyVectorizerChoice != VECTORIZER_NONE}; 865 if (OAI.PatternOpts || OAI.Postopts || OAI.Prevect) { 866 Schedule = ScheduleTreeOptimizer::optimizeSchedule(Schedule, &OAI); 867 Schedule = hoistExtensionNodes(Schedule); 868 LLVM_DEBUG(printSchedule(dbgs(), Schedule, "After post-optimizations")); 869 walkScheduleTreeForStatistics(Schedule, 2); 870 } 871 872 // Skip profitability check if user transformation(s) have been applied. 873 if (!HasUserTransformation && 874 !ScheduleTreeOptimizer::isProfitableSchedule(S, Schedule)) 875 return false; 876 877 auto ScopStats = S.getStatistics(); 878 ScopsOptimized++; 879 NumAffineLoopsOptimized += ScopStats.NumAffineLoops; 880 NumBoxedLoopsOptimized += ScopStats.NumBoxedLoops; 881 LastSchedule = Schedule; 882 883 S.setScheduleTree(Schedule); 884 S.markAsOptimized(); 885 886 if (OptimizedScops) 887 errs() << S; 888 889 return false; 890 } 891 892 bool IslScheduleOptimizerWrapperPass::runOnScop(Scop &S) { 893 releaseMemory(); 894 895 Function &F = S.getFunction(); 896 IslCtx = S.getSharedIslCtx(); 897 898 auto getDependences = 899 [this](Dependences::AnalysisLevel) -> const Dependences & { 900 return getAnalysis<DependenceInfo>().getDependences( 901 Dependences::AL_Statement); 902 }; 903 OptimizationRemarkEmitter &ORE = 904 getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE(); 905 TargetTransformInfo *TTI = 906 &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F); 907 return runIslScheduleOptimizer(S, getDependences, TTI, &ORE, LastSchedule); 908 } 909 910 static void runScheduleOptimizerPrinter(raw_ostream &OS, 911 isl::schedule LastSchedule) { 912 isl_printer *p; 913 char *ScheduleStr; 914 915 OS << "Calculated schedule:\n"; 916 917 if (LastSchedule.is_null()) { 918 OS << "n/a\n"; 919 return; 920 } 921 922 p = isl_printer_to_str(LastSchedule.ctx().get()); 923 p = isl_printer_set_yaml_style(p, ISL_YAML_STYLE_BLOCK); 924 p = isl_printer_print_schedule(p, LastSchedule.get()); 925 ScheduleStr = isl_printer_get_str(p); 926 isl_printer_free(p); 927 928 OS << ScheduleStr << "\n"; 929 930 free(ScheduleStr); 931 } 932 933 void IslScheduleOptimizerWrapperPass::printScop(raw_ostream &OS, Scop &) const { 934 runScheduleOptimizerPrinter(OS, LastSchedule); 935 } 936 937 void IslScheduleOptimizerWrapperPass::getAnalysisUsage( 938 AnalysisUsage &AU) const { 939 ScopPass::getAnalysisUsage(AU); 940 AU.addRequired<DependenceInfo>(); 941 AU.addRequired<TargetTransformInfoWrapperPass>(); 942 AU.addRequired<OptimizationRemarkEmitterWrapperPass>(); 943 944 AU.addPreserved<DependenceInfo>(); 945 AU.addPreserved<OptimizationRemarkEmitterWrapperPass>(); 946 } 947 948 } // namespace 949 950 Pass *polly::createIslScheduleOptimizerWrapperPass() { 951 return new IslScheduleOptimizerWrapperPass(); 952 } 953 954 INITIALIZE_PASS_BEGIN(IslScheduleOptimizerWrapperPass, "polly-opt-isl", 955 "Polly - Optimize schedule of SCoP", false, false); 956 INITIALIZE_PASS_DEPENDENCY(DependenceInfo); 957 INITIALIZE_PASS_DEPENDENCY(ScopInfoRegionPass); 958 INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass); 959 INITIALIZE_PASS_DEPENDENCY(OptimizationRemarkEmitterWrapperPass); 960 INITIALIZE_PASS_END(IslScheduleOptimizerWrapperPass, "polly-opt-isl", 961 "Polly - Optimize schedule of SCoP", false, false) 962 963 static llvm::PreservedAnalyses 964 runIslScheduleOptimizerUsingNPM(Scop &S, ScopAnalysisManager &SAM, 965 ScopStandardAnalysisResults &SAR, SPMUpdater &U, 966 raw_ostream *OS) { 967 DependenceAnalysis::Result &Deps = SAM.getResult<DependenceAnalysis>(S, SAR); 968 auto GetDeps = [&Deps](Dependences::AnalysisLevel) -> const Dependences & { 969 return Deps.getDependences(Dependences::AL_Statement); 970 }; 971 OptimizationRemarkEmitter ORE(&S.getFunction()); 972 TargetTransformInfo *TTI = &SAR.TTI; 973 isl::schedule LastSchedule; 974 bool Modified = runIslScheduleOptimizer(S, GetDeps, TTI, &ORE, LastSchedule); 975 if (OS) { 976 *OS << "Printing analysis 'Polly - Optimize schedule of SCoP' for region: '" 977 << S.getName() << "' in function '" << S.getFunction().getName() 978 << "':\n"; 979 runScheduleOptimizerPrinter(*OS, LastSchedule); 980 } 981 982 if (!Modified) 983 return PreservedAnalyses::all(); 984 985 PreservedAnalyses PA; 986 PA.preserveSet<AllAnalysesOn<Module>>(); 987 PA.preserveSet<AllAnalysesOn<Function>>(); 988 PA.preserveSet<AllAnalysesOn<Loop>>(); 989 return PA; 990 } 991 992 llvm::PreservedAnalyses 993 IslScheduleOptimizerPass::run(Scop &S, ScopAnalysisManager &SAM, 994 ScopStandardAnalysisResults &SAR, SPMUpdater &U) { 995 return runIslScheduleOptimizerUsingNPM(S, SAM, SAR, U, nullptr); 996 } 997 998 llvm::PreservedAnalyses 999 IslScheduleOptimizerPrinterPass::run(Scop &S, ScopAnalysisManager &SAM, 1000 ScopStandardAnalysisResults &SAR, 1001 SPMUpdater &U) { 1002 return runIslScheduleOptimizerUsingNPM(S, SAM, SAR, U, &OS); 1003 } 1004 1005 //===----------------------------------------------------------------------===// 1006 1007 namespace { 1008 /// Print result from IslScheduleOptimizerWrapperPass. 1009 class IslScheduleOptimizerPrinterLegacyPass final : public ScopPass { 1010 public: 1011 static char ID; 1012 1013 IslScheduleOptimizerPrinterLegacyPass() 1014 : IslScheduleOptimizerPrinterLegacyPass(outs()) {} 1015 explicit IslScheduleOptimizerPrinterLegacyPass(llvm::raw_ostream &OS) 1016 : ScopPass(ID), OS(OS) {} 1017 1018 bool runOnScop(Scop &S) override { 1019 IslScheduleOptimizerWrapperPass &P = 1020 getAnalysis<IslScheduleOptimizerWrapperPass>(); 1021 1022 OS << "Printing analysis '" << P.getPassName() << "' for region: '" 1023 << S.getRegion().getNameStr() << "' in function '" 1024 << S.getFunction().getName() << "':\n"; 1025 P.printScop(OS, S); 1026 1027 return false; 1028 } 1029 1030 void getAnalysisUsage(AnalysisUsage &AU) const override { 1031 ScopPass::getAnalysisUsage(AU); 1032 AU.addRequired<IslScheduleOptimizerWrapperPass>(); 1033 AU.setPreservesAll(); 1034 } 1035 1036 private: 1037 llvm::raw_ostream &OS; 1038 }; 1039 1040 char IslScheduleOptimizerPrinterLegacyPass::ID = 0; 1041 } // namespace 1042 1043 Pass *polly::createIslScheduleOptimizerPrinterLegacyPass(raw_ostream &OS) { 1044 return new IslScheduleOptimizerPrinterLegacyPass(OS); 1045 } 1046 1047 INITIALIZE_PASS_BEGIN(IslScheduleOptimizerPrinterLegacyPass, 1048 "polly-print-opt-isl", 1049 "Polly - Print optimizer schedule of SCoP", false, false); 1050 INITIALIZE_PASS_DEPENDENCY(IslScheduleOptimizerWrapperPass) 1051 INITIALIZE_PASS_END(IslScheduleOptimizerPrinterLegacyPass, 1052 "polly-print-opt-isl", 1053 "Polly - Print optimizer schedule of SCoP", false, false) 1054