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 static cl::opt<bool> 170 PMBasedOpts("polly-pattern-matching-based-opts", 171 cl::desc("Perform optimizations based on pattern matching"), 172 cl::init(false), cl::ZeroOrMore, cl::cat(PollyCategory)); 173 174 /// @brief Create an isl_union_set, which describes the isolate option based 175 /// on IsoalteDomain. 176 /// 177 /// @param IsolateDomain An isl_set whose last dimension is the only one that 178 /// should belong to the current band node. 179 static __isl_give isl_union_set * 180 getIsolateOptions(__isl_take isl_set *IsolateDomain) { 181 auto Dims = isl_set_dim(IsolateDomain, isl_dim_set); 182 auto *IsolateRelation = isl_map_from_domain(IsolateDomain); 183 IsolateRelation = isl_map_move_dims(IsolateRelation, isl_dim_out, 0, 184 isl_dim_in, Dims - 1, 1); 185 auto *IsolateOption = isl_map_wrap(IsolateRelation); 186 auto *Id = isl_id_alloc(isl_set_get_ctx(IsolateOption), "isolate", NULL); 187 return isl_union_set_from_set(isl_set_set_tuple_id(IsolateOption, Id)); 188 } 189 190 /// @brief Create an isl_union_set, which describes the atomic option for the 191 /// dimension of the current node. 192 /// 193 /// It may help to reduce the size of generated code. 194 /// 195 /// @param Ctx An isl_ctx, which is used to create the isl_union_set. 196 static __isl_give isl_union_set *getAtomicOptions(__isl_take isl_ctx *Ctx) { 197 auto *Space = isl_space_set_alloc(Ctx, 0, 1); 198 auto *AtomicOption = isl_set_universe(Space); 199 auto *Id = isl_id_alloc(Ctx, "atomic", NULL); 200 return isl_union_set_from_set(isl_set_set_tuple_id(AtomicOption, Id)); 201 } 202 203 /// @brief Make the last dimension of Set to take values 204 /// from 0 to VectorWidth - 1. 205 /// 206 /// @param Set A set, which should be modified. 207 /// @param VectorWidth A parameter, which determines the constraint. 208 static __isl_give isl_set *addExtentConstraints(__isl_take isl_set *Set, 209 int VectorWidth) { 210 auto Dims = isl_set_dim(Set, isl_dim_set); 211 auto Space = isl_set_get_space(Set); 212 auto *LocalSpace = isl_local_space_from_space(Space); 213 auto *ExtConstr = 214 isl_constraint_alloc_inequality(isl_local_space_copy(LocalSpace)); 215 ExtConstr = isl_constraint_set_constant_si(ExtConstr, 0); 216 ExtConstr = 217 isl_constraint_set_coefficient_si(ExtConstr, isl_dim_set, Dims - 1, 1); 218 Set = isl_set_add_constraint(Set, ExtConstr); 219 ExtConstr = isl_constraint_alloc_inequality(LocalSpace); 220 ExtConstr = isl_constraint_set_constant_si(ExtConstr, VectorWidth - 1); 221 ExtConstr = 222 isl_constraint_set_coefficient_si(ExtConstr, isl_dim_set, Dims - 1, -1); 223 return isl_set_add_constraint(Set, ExtConstr); 224 } 225 226 /// @brief Build the desired set of partial tile prefixes. 227 /// 228 /// We build a set of partial tile prefixes, which are prefixes of the vector 229 /// loop that have exactly VectorWidth iterations. 230 /// 231 /// 1. Get all prefixes of the vector loop. 232 /// 2. Extend it to a set, which has exactly VectorWidth iterations for 233 /// any prefix from the set that was built on the previous step. 234 /// 3. Subtract loop domain from it, project out the vector loop dimension and 235 /// get a set of prefixes, which don't have exactly VectorWidth iterations. 236 /// 4. Subtract it from all prefixes of the vector loop and get the desired 237 /// set. 238 /// 239 /// @param ScheduleRange A range of a map, which describes a prefix schedule 240 /// relation. 241 static __isl_give isl_set * 242 getPartialTilePrefixes(__isl_take isl_set *ScheduleRange, int VectorWidth) { 243 auto Dims = isl_set_dim(ScheduleRange, isl_dim_set); 244 auto *LoopPrefixes = isl_set_project_out(isl_set_copy(ScheduleRange), 245 isl_dim_set, Dims - 1, 1); 246 auto *ExtentPrefixes = 247 isl_set_add_dims(isl_set_copy(LoopPrefixes), isl_dim_set, 1); 248 ExtentPrefixes = addExtentConstraints(ExtentPrefixes, VectorWidth); 249 auto *BadPrefixes = isl_set_subtract(ExtentPrefixes, ScheduleRange); 250 BadPrefixes = isl_set_project_out(BadPrefixes, isl_dim_set, Dims - 1, 1); 251 return isl_set_subtract(LoopPrefixes, BadPrefixes); 252 } 253 254 __isl_give isl_schedule_node *ScheduleTreeOptimizer::isolateFullPartialTiles( 255 __isl_take isl_schedule_node *Node, int VectorWidth) { 256 assert(isl_schedule_node_get_type(Node) == isl_schedule_node_band); 257 Node = isl_schedule_node_child(Node, 0); 258 Node = isl_schedule_node_child(Node, 0); 259 auto *SchedRelUMap = isl_schedule_node_get_prefix_schedule_relation(Node); 260 auto *ScheduleRelation = isl_map_from_union_map(SchedRelUMap); 261 auto *ScheduleRange = isl_map_range(ScheduleRelation); 262 auto *IsolateDomain = getPartialTilePrefixes(ScheduleRange, VectorWidth); 263 auto *AtomicOption = getAtomicOptions(isl_set_get_ctx(IsolateDomain)); 264 auto *IsolateOption = getIsolateOptions(IsolateDomain); 265 Node = isl_schedule_node_parent(Node); 266 Node = isl_schedule_node_parent(Node); 267 auto *Options = isl_union_set_union(IsolateOption, AtomicOption); 268 Node = isl_schedule_node_band_set_ast_build_options(Node, Options); 269 return Node; 270 } 271 272 __isl_give isl_schedule_node * 273 ScheduleTreeOptimizer::prevectSchedBand(__isl_take isl_schedule_node *Node, 274 unsigned DimToVectorize, 275 int VectorWidth) { 276 assert(isl_schedule_node_get_type(Node) == isl_schedule_node_band); 277 278 auto Space = isl_schedule_node_band_get_space(Node); 279 auto ScheduleDimensions = isl_space_dim(Space, isl_dim_set); 280 isl_space_free(Space); 281 assert(DimToVectorize < ScheduleDimensions); 282 283 if (DimToVectorize > 0) { 284 Node = isl_schedule_node_band_split(Node, DimToVectorize); 285 Node = isl_schedule_node_child(Node, 0); 286 } 287 if (DimToVectorize < ScheduleDimensions - 1) 288 Node = isl_schedule_node_band_split(Node, 1); 289 Space = isl_schedule_node_band_get_space(Node); 290 auto Sizes = isl_multi_val_zero(Space); 291 auto Ctx = isl_schedule_node_get_ctx(Node); 292 Sizes = 293 isl_multi_val_set_val(Sizes, 0, isl_val_int_from_si(Ctx, VectorWidth)); 294 Node = isl_schedule_node_band_tile(Node, Sizes); 295 Node = isolateFullPartialTiles(Node, VectorWidth); 296 Node = isl_schedule_node_child(Node, 0); 297 // Make sure the "trivially vectorizable loop" is not unrolled. Otherwise, 298 // we will have troubles to match it in the backend. 299 Node = isl_schedule_node_band_set_ast_build_options( 300 Node, isl_union_set_read_from_str(Ctx, "{ unroll[x]: 1 = 0 }")); 301 Node = isl_schedule_node_band_sink(Node); 302 Node = isl_schedule_node_child(Node, 0); 303 if (isl_schedule_node_get_type(Node) == isl_schedule_node_leaf) 304 Node = isl_schedule_node_parent(Node); 305 isl_id *LoopMarker = isl_id_alloc(Ctx, "SIMD", nullptr); 306 Node = isl_schedule_node_insert_mark(Node, LoopMarker); 307 return Node; 308 } 309 310 __isl_give isl_schedule_node * 311 ScheduleTreeOptimizer::tileNode(__isl_take isl_schedule_node *Node, 312 const char *Identifier, ArrayRef<int> TileSizes, 313 int DefaultTileSize) { 314 auto Ctx = isl_schedule_node_get_ctx(Node); 315 auto Space = isl_schedule_node_band_get_space(Node); 316 auto Dims = isl_space_dim(Space, isl_dim_set); 317 auto Sizes = isl_multi_val_zero(Space); 318 std::string IdentifierString(Identifier); 319 for (unsigned i = 0; i < Dims; i++) { 320 auto tileSize = i < TileSizes.size() ? TileSizes[i] : DefaultTileSize; 321 Sizes = isl_multi_val_set_val(Sizes, i, isl_val_int_from_si(Ctx, tileSize)); 322 } 323 auto TileLoopMarkerStr = IdentifierString + " - Tiles"; 324 isl_id *TileLoopMarker = 325 isl_id_alloc(Ctx, TileLoopMarkerStr.c_str(), nullptr); 326 Node = isl_schedule_node_insert_mark(Node, TileLoopMarker); 327 Node = isl_schedule_node_child(Node, 0); 328 Node = isl_schedule_node_band_tile(Node, Sizes); 329 Node = isl_schedule_node_child(Node, 0); 330 auto PointLoopMarkerStr = IdentifierString + " - Points"; 331 isl_id *PointLoopMarker = 332 isl_id_alloc(Ctx, PointLoopMarkerStr.c_str(), nullptr); 333 Node = isl_schedule_node_insert_mark(Node, PointLoopMarker); 334 Node = isl_schedule_node_child(Node, 0); 335 return Node; 336 } 337 338 __isl_give isl_schedule_node * 339 ScheduleTreeOptimizer::applyRegisterTiling(__isl_take isl_schedule_node *Node, 340 llvm::ArrayRef<int> TileSizes, 341 int DefaultTileSize) { 342 auto *Ctx = isl_schedule_node_get_ctx(Node); 343 Node = tileNode(Node, "Register tiling", TileSizes, DefaultTileSize); 344 Node = isl_schedule_node_band_set_ast_build_options( 345 Node, isl_union_set_read_from_str(Ctx, "{unroll[x]}")); 346 return Node; 347 } 348 349 bool ScheduleTreeOptimizer::isTileableBandNode( 350 __isl_keep isl_schedule_node *Node) { 351 if (isl_schedule_node_get_type(Node) != isl_schedule_node_band) 352 return false; 353 354 if (isl_schedule_node_n_children(Node) != 1) 355 return false; 356 357 if (!isl_schedule_node_band_get_permutable(Node)) 358 return false; 359 360 auto Space = isl_schedule_node_band_get_space(Node); 361 auto Dims = isl_space_dim(Space, isl_dim_set); 362 isl_space_free(Space); 363 364 if (Dims <= 1) 365 return false; 366 367 auto Child = isl_schedule_node_get_child(Node, 0); 368 auto Type = isl_schedule_node_get_type(Child); 369 isl_schedule_node_free(Child); 370 371 if (Type != isl_schedule_node_leaf) 372 return false; 373 374 return true; 375 } 376 377 __isl_give isl_schedule_node * 378 ScheduleTreeOptimizer::standardBandOpts(__isl_take isl_schedule_node *Node, 379 void *User) { 380 if (FirstLevelTiling) 381 Node = tileNode(Node, "1st level tiling", FirstLevelTileSizes, 382 FirstLevelDefaultTileSize); 383 384 if (SecondLevelTiling) 385 Node = tileNode(Node, "2nd level tiling", SecondLevelTileSizes, 386 SecondLevelDefaultTileSize); 387 388 if (RegisterTiling) 389 Node = 390 applyRegisterTiling(Node, RegisterTileSizes, RegisterDefaultTileSize); 391 392 if (PollyVectorizerChoice == VECTORIZER_NONE) 393 return Node; 394 395 auto Space = isl_schedule_node_band_get_space(Node); 396 auto Dims = isl_space_dim(Space, isl_dim_set); 397 isl_space_free(Space); 398 399 for (int i = Dims - 1; i >= 0; i--) 400 if (isl_schedule_node_band_member_get_coincident(Node, i)) { 401 Node = prevectSchedBand(Node, i, PrevectorWidth); 402 break; 403 } 404 405 return Node; 406 } 407 408 /// @brief Check whether output dimensions of the map rely on the specified 409 /// input dimension. 410 /// 411 /// @param IslMap The isl map to be considered. 412 /// @param DimNum The number of an input dimension to be checked. 413 static bool isInputDimUsed(__isl_take isl_map *IslMap, unsigned DimNum) { 414 auto *CheckedAccessRelation = 415 isl_map_project_out(isl_map_copy(IslMap), isl_dim_in, DimNum, 1); 416 CheckedAccessRelation = 417 isl_map_insert_dims(CheckedAccessRelation, isl_dim_in, DimNum, 1); 418 auto *InputDimsId = isl_map_get_tuple_id(IslMap, isl_dim_in); 419 CheckedAccessRelation = 420 isl_map_set_tuple_id(CheckedAccessRelation, isl_dim_in, InputDimsId); 421 InputDimsId = isl_map_get_tuple_id(IslMap, isl_dim_out); 422 CheckedAccessRelation = 423 isl_map_set_tuple_id(CheckedAccessRelation, isl_dim_out, InputDimsId); 424 auto res = !isl_map_is_equal(CheckedAccessRelation, IslMap); 425 isl_map_free(CheckedAccessRelation); 426 isl_map_free(IslMap); 427 return res; 428 } 429 430 /// @brief Check if the SCoP statement could probably be optimized with 431 /// analytical modeling. 432 /// 433 /// containsMatrMult tries to determine whether the following conditions 434 /// are true: 435 /// 1. all memory accesses of the statement will have stride 0 or 1, 436 /// if we interchange loops (switch the variable used in the inner 437 /// loop to the outer loop). 438 /// 2. all memory accesses of the statement except from the last one, are 439 /// read memory access and the last one is write memory access. 440 /// 3. all subscripts of the last memory access of the statement don't contain 441 /// the variable used in the inner loop. 442 /// 443 /// @param PartialSchedule The PartialSchedule that contains a SCoP statement 444 /// to check. 445 static bool containsMatrMult(__isl_keep isl_map *PartialSchedule) { 446 auto InputDimsId = isl_map_get_tuple_id(PartialSchedule, isl_dim_in); 447 auto *ScpStmt = static_cast<ScopStmt *>(isl_id_get_user(InputDimsId)); 448 isl_id_free(InputDimsId); 449 if (ScpStmt->size() <= 1) 450 return false; 451 auto MemA = ScpStmt->begin(); 452 for (unsigned i = 0; i < ScpStmt->size() - 2 && MemA != ScpStmt->end(); 453 i++, MemA++) 454 if (!(*MemA)->isRead() || 455 ((*MemA)->isArrayKind() && 456 !((*MemA)->isStrideOne(isl_map_copy(PartialSchedule)) || 457 (*MemA)->isStrideZero(isl_map_copy(PartialSchedule))))) 458 return false; 459 MemA++; 460 if (!(*MemA)->isWrite() || !(*MemA)->isArrayKind() || 461 !((*MemA)->isStrideOne(isl_map_copy(PartialSchedule)) || 462 (*MemA)->isStrideZero(isl_map_copy(PartialSchedule)))) 463 return false; 464 auto DimNum = isl_map_dim(PartialSchedule, isl_dim_in); 465 return !isInputDimUsed((*MemA)->getAccessRelation(), DimNum - 1); 466 } 467 468 /// @brief Circular shift of output dimensions of the integer map. 469 /// 470 /// @param IslMap The isl map to be modified. 471 static __isl_give isl_map *circularShiftOutputDims(__isl_take isl_map *IslMap) { 472 auto DimNum = isl_map_dim(IslMap, isl_dim_out); 473 if (DimNum == 0) 474 return IslMap; 475 auto InputDimsId = isl_map_get_tuple_id(IslMap, isl_dim_in); 476 IslMap = isl_map_move_dims(IslMap, isl_dim_in, 0, isl_dim_out, DimNum - 1, 1); 477 IslMap = isl_map_move_dims(IslMap, isl_dim_out, 0, isl_dim_in, 0, 1); 478 return isl_map_set_tuple_id(IslMap, isl_dim_in, InputDimsId); 479 } 480 481 bool ScheduleTreeOptimizer::isMatrMultPattern( 482 __isl_keep isl_schedule_node *Node) { 483 auto *PartialSchedule = 484 isl_schedule_node_band_get_partial_schedule_union_map(Node); 485 if (isl_union_map_n_map(PartialSchedule) != 1) 486 return false; 487 auto *NewPartialSchedule = isl_map_from_union_map(PartialSchedule); 488 auto DimNum = isl_map_dim(NewPartialSchedule, isl_dim_in); 489 if (DimNum != 3) { 490 isl_map_free(NewPartialSchedule); 491 return false; 492 } 493 assert(isl_map_dim(NewPartialSchedule, isl_dim_out) == 3 && 494 "Each schedule dimension should be represented by a union piecewise" 495 "quasi-affine expression."); 496 NewPartialSchedule = circularShiftOutputDims(NewPartialSchedule); 497 if (containsMatrMult(NewPartialSchedule)) { 498 isl_map_free(NewPartialSchedule); 499 return true; 500 } 501 isl_map_free(NewPartialSchedule); 502 return false; 503 } 504 505 __isl_give isl_schedule_node * 506 ScheduleTreeOptimizer::optimizeBand(__isl_take isl_schedule_node *Node, 507 void *User) { 508 if (!isTileableBandNode(Node)) 509 return Node; 510 511 if (PMBasedOpts && isMatrMultPattern(Node)) 512 DEBUG(dbgs() << "The matrix multiplication pattern was detected\n"); 513 514 return standardBandOpts(Node, User); 515 } 516 517 __isl_give isl_schedule * 518 ScheduleTreeOptimizer::optimizeSchedule(__isl_take isl_schedule *Schedule) { 519 isl_schedule_node *Root = isl_schedule_get_root(Schedule); 520 Root = optimizeScheduleNode(Root); 521 isl_schedule_free(Schedule); 522 auto S = isl_schedule_node_get_schedule(Root); 523 isl_schedule_node_free(Root); 524 return S; 525 } 526 527 __isl_give isl_schedule_node *ScheduleTreeOptimizer::optimizeScheduleNode( 528 __isl_take isl_schedule_node *Node) { 529 Node = isl_schedule_node_map_descendant_bottom_up(Node, optimizeBand, NULL); 530 return Node; 531 } 532 533 bool ScheduleTreeOptimizer::isProfitableSchedule( 534 Scop &S, __isl_keep isl_union_map *NewSchedule) { 535 // To understand if the schedule has been optimized we check if the schedule 536 // has changed at all. 537 // TODO: We can improve this by tracking if any necessarily beneficial 538 // transformations have been performed. This can e.g. be tiling, loop 539 // interchange, or ...) We can track this either at the place where the 540 // transformation has been performed or, in case of automatic ILP based 541 // optimizations, by comparing (yet to be defined) performance metrics 542 // before/after the scheduling optimizer 543 // (e.g., #stride-one accesses) 544 isl_union_map *OldSchedule = S.getSchedule(); 545 bool changed = !isl_union_map_is_equal(OldSchedule, NewSchedule); 546 isl_union_map_free(OldSchedule); 547 return changed; 548 } 549 550 namespace { 551 class IslScheduleOptimizer : public ScopPass { 552 public: 553 static char ID; 554 explicit IslScheduleOptimizer() : ScopPass(ID) { LastSchedule = nullptr; } 555 556 ~IslScheduleOptimizer() { isl_schedule_free(LastSchedule); } 557 558 /// @brief Optimize the schedule of the SCoP @p S. 559 bool runOnScop(Scop &S) override; 560 561 /// @brief Print the new schedule for the SCoP @p S. 562 void printScop(raw_ostream &OS, Scop &S) const override; 563 564 /// @brief Register all analyses and transformation required. 565 void getAnalysisUsage(AnalysisUsage &AU) const override; 566 567 /// @brief Release the internal memory. 568 void releaseMemory() override { 569 isl_schedule_free(LastSchedule); 570 LastSchedule = nullptr; 571 } 572 573 private: 574 isl_schedule *LastSchedule; 575 }; 576 } 577 578 char IslScheduleOptimizer::ID = 0; 579 580 bool IslScheduleOptimizer::runOnScop(Scop &S) { 581 582 // Skip empty SCoPs but still allow code generation as it will delete the 583 // loops present but not needed. 584 if (S.getSize() == 0) { 585 S.markAsOptimized(); 586 return false; 587 } 588 589 const Dependences &D = 590 getAnalysis<DependenceInfo>().getDependences(Dependences::AL_Statement); 591 592 if (!D.hasValidDependences()) 593 return false; 594 595 isl_schedule_free(LastSchedule); 596 LastSchedule = nullptr; 597 598 // Build input data. 599 int ValidityKinds = 600 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW; 601 int ProximityKinds; 602 603 if (OptimizeDeps == "all") 604 ProximityKinds = 605 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW; 606 else if (OptimizeDeps == "raw") 607 ProximityKinds = Dependences::TYPE_RAW; 608 else { 609 errs() << "Do not know how to optimize for '" << OptimizeDeps << "'" 610 << " Falling back to optimizing all dependences.\n"; 611 ProximityKinds = 612 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW; 613 } 614 615 isl_union_set *Domain = S.getDomains(); 616 617 if (!Domain) 618 return false; 619 620 isl_union_map *Validity = D.getDependences(ValidityKinds); 621 isl_union_map *Proximity = D.getDependences(ProximityKinds); 622 623 // Simplify the dependences by removing the constraints introduced by the 624 // domains. This can speed up the scheduling time significantly, as large 625 // constant coefficients will be removed from the dependences. The 626 // introduction of some additional dependences reduces the possible 627 // transformations, but in most cases, such transformation do not seem to be 628 // interesting anyway. In some cases this option may stop the scheduler to 629 // find any schedule. 630 if (SimplifyDeps == "yes") { 631 Validity = isl_union_map_gist_domain(Validity, isl_union_set_copy(Domain)); 632 Validity = isl_union_map_gist_range(Validity, isl_union_set_copy(Domain)); 633 Proximity = 634 isl_union_map_gist_domain(Proximity, isl_union_set_copy(Domain)); 635 Proximity = isl_union_map_gist_range(Proximity, isl_union_set_copy(Domain)); 636 } else if (SimplifyDeps != "no") { 637 errs() << "warning: Option -polly-opt-simplify-deps should either be 'yes' " 638 "or 'no'. Falling back to default: 'yes'\n"; 639 } 640 641 DEBUG(dbgs() << "\n\nCompute schedule from: "); 642 DEBUG(dbgs() << "Domain := " << stringFromIslObj(Domain) << ";\n"); 643 DEBUG(dbgs() << "Proximity := " << stringFromIslObj(Proximity) << ";\n"); 644 DEBUG(dbgs() << "Validity := " << stringFromIslObj(Validity) << ";\n"); 645 646 unsigned IslSerializeSCCs; 647 648 if (FusionStrategy == "max") { 649 IslSerializeSCCs = 0; 650 } else if (FusionStrategy == "min") { 651 IslSerializeSCCs = 1; 652 } else { 653 errs() << "warning: Unknown fusion strategy. Falling back to maximal " 654 "fusion.\n"; 655 IslSerializeSCCs = 0; 656 } 657 658 int IslMaximizeBands; 659 660 if (MaximizeBandDepth == "yes") { 661 IslMaximizeBands = 1; 662 } else if (MaximizeBandDepth == "no") { 663 IslMaximizeBands = 0; 664 } else { 665 errs() << "warning: Option -polly-opt-maximize-bands should either be 'yes'" 666 " or 'no'. Falling back to default: 'yes'\n"; 667 IslMaximizeBands = 1; 668 } 669 670 int IslOuterCoincidence; 671 672 if (OuterCoincidence == "yes") { 673 IslOuterCoincidence = 1; 674 } else if (OuterCoincidence == "no") { 675 IslOuterCoincidence = 0; 676 } else { 677 errs() << "warning: Option -polly-opt-outer-coincidence should either be " 678 "'yes' or 'no'. Falling back to default: 'no'\n"; 679 IslOuterCoincidence = 0; 680 } 681 682 isl_options_set_schedule_outer_coincidence(S.getIslCtx(), 683 IslOuterCoincidence); 684 isl_options_set_schedule_serialize_sccs(S.getIslCtx(), IslSerializeSCCs); 685 isl_options_set_schedule_maximize_band_depth(S.getIslCtx(), IslMaximizeBands); 686 isl_options_set_schedule_max_constant_term(S.getIslCtx(), MaxConstantTerm); 687 isl_options_set_schedule_max_coefficient(S.getIslCtx(), MaxCoefficient); 688 isl_options_set_tile_scale_tile_loops(S.getIslCtx(), 0); 689 690 isl_options_set_on_error(S.getIslCtx(), ISL_ON_ERROR_CONTINUE); 691 692 isl_schedule_constraints *ScheduleConstraints; 693 ScheduleConstraints = isl_schedule_constraints_on_domain(Domain); 694 ScheduleConstraints = 695 isl_schedule_constraints_set_proximity(ScheduleConstraints, Proximity); 696 ScheduleConstraints = isl_schedule_constraints_set_validity( 697 ScheduleConstraints, isl_union_map_copy(Validity)); 698 ScheduleConstraints = 699 isl_schedule_constraints_set_coincidence(ScheduleConstraints, Validity); 700 isl_schedule *Schedule; 701 Schedule = isl_schedule_constraints_compute_schedule(ScheduleConstraints); 702 isl_options_set_on_error(S.getIslCtx(), ISL_ON_ERROR_ABORT); 703 704 // In cases the scheduler is not able to optimize the code, we just do not 705 // touch the schedule. 706 if (!Schedule) 707 return false; 708 709 DEBUG({ 710 auto *P = isl_printer_to_str(S.getIslCtx()); 711 P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK); 712 P = isl_printer_print_schedule(P, Schedule); 713 dbgs() << "NewScheduleTree: \n" << isl_printer_get_str(P) << "\n"; 714 isl_printer_free(P); 715 }); 716 717 isl_schedule *NewSchedule = ScheduleTreeOptimizer::optimizeSchedule(Schedule); 718 isl_union_map *NewScheduleMap = isl_schedule_get_map(NewSchedule); 719 720 if (!ScheduleTreeOptimizer::isProfitableSchedule(S, NewScheduleMap)) { 721 isl_union_map_free(NewScheduleMap); 722 isl_schedule_free(NewSchedule); 723 return false; 724 } 725 726 S.setScheduleTree(NewSchedule); 727 S.markAsOptimized(); 728 729 isl_union_map_free(NewScheduleMap); 730 return false; 731 } 732 733 void IslScheduleOptimizer::printScop(raw_ostream &OS, Scop &) const { 734 isl_printer *p; 735 char *ScheduleStr; 736 737 OS << "Calculated schedule:\n"; 738 739 if (!LastSchedule) { 740 OS << "n/a\n"; 741 return; 742 } 743 744 p = isl_printer_to_str(isl_schedule_get_ctx(LastSchedule)); 745 p = isl_printer_print_schedule(p, LastSchedule); 746 ScheduleStr = isl_printer_get_str(p); 747 isl_printer_free(p); 748 749 OS << ScheduleStr << "\n"; 750 } 751 752 void IslScheduleOptimizer::getAnalysisUsage(AnalysisUsage &AU) const { 753 ScopPass::getAnalysisUsage(AU); 754 AU.addRequired<DependenceInfo>(); 755 } 756 757 Pass *polly::createIslScheduleOptimizerPass() { 758 return new IslScheduleOptimizer(); 759 } 760 761 INITIALIZE_PASS_BEGIN(IslScheduleOptimizer, "polly-opt-isl", 762 "Polly - Optimize schedule of SCoP", false, false); 763 INITIALIZE_PASS_DEPENDENCY(DependenceInfo); 764 INITIALIZE_PASS_DEPENDENCY(ScopInfoRegionPass); 765 INITIALIZE_PASS_END(IslScheduleOptimizer, "polly-opt-isl", 766 "Polly - Optimize schedule of SCoP", false, false) 767