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 bool ScheduleTreeOptimizer::isTileableBandNode( 339 __isl_keep isl_schedule_node *Node) { 340 if (isl_schedule_node_get_type(Node) != isl_schedule_node_band) 341 return false; 342 343 if (isl_schedule_node_n_children(Node) != 1) 344 return false; 345 346 if (!isl_schedule_node_band_get_permutable(Node)) 347 return false; 348 349 auto Space = isl_schedule_node_band_get_space(Node); 350 auto Dims = isl_space_dim(Space, isl_dim_set); 351 isl_space_free(Space); 352 353 if (Dims <= 1) 354 return false; 355 356 auto Child = isl_schedule_node_get_child(Node, 0); 357 auto Type = isl_schedule_node_get_type(Child); 358 isl_schedule_node_free(Child); 359 360 if (Type != isl_schedule_node_leaf) 361 return false; 362 363 return true; 364 } 365 366 __isl_give isl_schedule_node * 367 ScheduleTreeOptimizer::standardBandOpts(__isl_take isl_schedule_node *Node, 368 void *User) { 369 if (FirstLevelTiling) 370 Node = tileNode(Node, "1st level tiling", FirstLevelTileSizes, 371 FirstLevelDefaultTileSize); 372 373 if (SecondLevelTiling) 374 Node = tileNode(Node, "2nd level tiling", SecondLevelTileSizes, 375 SecondLevelDefaultTileSize); 376 377 if (RegisterTiling) { 378 auto *Ctx = isl_schedule_node_get_ctx(Node); 379 Node = tileNode(Node, "Register tiling", RegisterTileSizes, 380 RegisterDefaultTileSize); 381 Node = isl_schedule_node_band_set_ast_build_options( 382 Node, isl_union_set_read_from_str(Ctx, "{unroll[x]}")); 383 } 384 385 if (PollyVectorizerChoice == VECTORIZER_NONE) 386 return Node; 387 388 auto Space = isl_schedule_node_band_get_space(Node); 389 auto Dims = isl_space_dim(Space, isl_dim_set); 390 isl_space_free(Space); 391 392 for (int i = Dims - 1; i >= 0; i--) 393 if (isl_schedule_node_band_member_get_coincident(Node, i)) { 394 Node = prevectSchedBand(Node, i, PrevectorWidth); 395 break; 396 } 397 398 return Node; 399 } 400 401 /// @brief Check whether output dimensions of the map rely on the specified 402 /// input dimension. 403 /// 404 /// @param IslMap The isl map to be considered. 405 /// @param DimNum The number of an input dimension to be checked. 406 static bool isInputDimUsed(__isl_take isl_map *IslMap, unsigned DimNum) { 407 auto *CheckedAccessRelation = 408 isl_map_project_out(isl_map_copy(IslMap), isl_dim_in, DimNum, 1); 409 CheckedAccessRelation = 410 isl_map_insert_dims(CheckedAccessRelation, isl_dim_in, DimNum, 1); 411 auto *InputDimsId = isl_map_get_tuple_id(IslMap, isl_dim_in); 412 CheckedAccessRelation = 413 isl_map_set_tuple_id(CheckedAccessRelation, isl_dim_in, InputDimsId); 414 InputDimsId = isl_map_get_tuple_id(IslMap, isl_dim_out); 415 CheckedAccessRelation = 416 isl_map_set_tuple_id(CheckedAccessRelation, isl_dim_out, InputDimsId); 417 auto res = !isl_map_is_equal(CheckedAccessRelation, IslMap); 418 isl_map_free(CheckedAccessRelation); 419 isl_map_free(IslMap); 420 return res; 421 } 422 423 /// @brief Check if the SCoP statement could probably be optimized with 424 /// analytical modeling. 425 /// 426 /// containsMatrMult tries to determine whether the following conditions 427 /// are true: 428 /// 1. all memory accesses of the statement will have stride 0 or 1, 429 /// if we interchange loops (switch the variable used in the inner 430 /// loop to the outer loop). 431 /// 2. all memory accesses of the statement except from the last one, are 432 /// read memory access and the last one is write memory access. 433 /// 3. all subscripts of the last memory access of the statement don't contain 434 /// the variable used in the inner loop. 435 /// 436 /// @param PartialSchedule The PartialSchedule that contains a SCoP statement 437 /// to check. 438 static bool containsMatrMult(__isl_keep isl_map *PartialSchedule) { 439 auto InputDimsId = isl_map_get_tuple_id(PartialSchedule, isl_dim_in); 440 auto *ScpStmt = static_cast<ScopStmt *>(isl_id_get_user(InputDimsId)); 441 isl_id_free(InputDimsId); 442 if (ScpStmt->size() <= 1) 443 return false; 444 auto MemA = ScpStmt->begin(); 445 for (unsigned i = 0; i < ScpStmt->size() - 2 && MemA != ScpStmt->end(); 446 i++, MemA++) 447 if (!(*MemA)->isRead() || 448 ((*MemA)->isArrayKind() && 449 !((*MemA)->isStrideOne(isl_map_copy(PartialSchedule)) || 450 (*MemA)->isStrideZero(isl_map_copy(PartialSchedule))))) 451 return false; 452 MemA++; 453 if (!(*MemA)->isWrite() || !(*MemA)->isArrayKind() || 454 !((*MemA)->isStrideOne(isl_map_copy(PartialSchedule)) || 455 (*MemA)->isStrideZero(isl_map_copy(PartialSchedule)))) 456 return false; 457 auto DimNum = isl_map_dim(PartialSchedule, isl_dim_in); 458 return !isInputDimUsed((*MemA)->getAccessRelation(), DimNum - 1); 459 } 460 461 /// @brief Circular shift of output dimensions of the integer map. 462 /// 463 /// @param IslMap The isl map to be modified. 464 static __isl_give isl_map *circularShiftOutputDims(__isl_take isl_map *IslMap) { 465 auto DimNum = isl_map_dim(IslMap, isl_dim_out); 466 if (DimNum == 0) 467 return IslMap; 468 auto InputDimsId = isl_map_get_tuple_id(IslMap, isl_dim_in); 469 IslMap = isl_map_move_dims(IslMap, isl_dim_in, 0, isl_dim_out, DimNum - 1, 1); 470 IslMap = isl_map_move_dims(IslMap, isl_dim_out, 0, isl_dim_in, 0, 1); 471 return isl_map_set_tuple_id(IslMap, isl_dim_in, InputDimsId); 472 } 473 474 bool ScheduleTreeOptimizer::isMatrMultPattern( 475 __isl_keep isl_schedule_node *Node) { 476 auto *PartialSchedule = 477 isl_schedule_node_band_get_partial_schedule_union_map(Node); 478 if (isl_union_map_n_map(PartialSchedule) != 1) 479 return false; 480 auto *NewPartialSchedule = isl_map_from_union_map(PartialSchedule); 481 auto DimNum = isl_map_dim(NewPartialSchedule, isl_dim_in); 482 if (DimNum != 3) { 483 isl_map_free(NewPartialSchedule); 484 return false; 485 } 486 assert(isl_map_dim(NewPartialSchedule, isl_dim_out) == 3 && 487 "Each schedule dimension should be represented by a union piecewise" 488 "quasi-affine expression."); 489 NewPartialSchedule = circularShiftOutputDims(NewPartialSchedule); 490 if (containsMatrMult(NewPartialSchedule)) { 491 isl_map_free(NewPartialSchedule); 492 return true; 493 } 494 isl_map_free(NewPartialSchedule); 495 return false; 496 } 497 498 __isl_give isl_schedule_node * 499 ScheduleTreeOptimizer::optimizeBand(__isl_take isl_schedule_node *Node, 500 void *User) { 501 if (!isTileableBandNode(Node)) 502 return Node; 503 504 if (PMBasedOpts && isMatrMultPattern(Node)) 505 DEBUG(dbgs() << "The matrix multiplication pattern was detected\n"); 506 507 return standardBandOpts(Node, User); 508 } 509 510 __isl_give isl_schedule * 511 ScheduleTreeOptimizer::optimizeSchedule(__isl_take isl_schedule *Schedule) { 512 isl_schedule_node *Root = isl_schedule_get_root(Schedule); 513 Root = optimizeScheduleNode(Root); 514 isl_schedule_free(Schedule); 515 auto S = isl_schedule_node_get_schedule(Root); 516 isl_schedule_node_free(Root); 517 return S; 518 } 519 520 __isl_give isl_schedule_node *ScheduleTreeOptimizer::optimizeScheduleNode( 521 __isl_take isl_schedule_node *Node) { 522 Node = isl_schedule_node_map_descendant_bottom_up(Node, optimizeBand, NULL); 523 return Node; 524 } 525 526 bool ScheduleTreeOptimizer::isProfitableSchedule( 527 Scop &S, __isl_keep isl_union_map *NewSchedule) { 528 // To understand if the schedule has been optimized we check if the schedule 529 // has changed at all. 530 // TODO: We can improve this by tracking if any necessarily beneficial 531 // transformations have been performed. This can e.g. be tiling, loop 532 // interchange, or ...) We can track this either at the place where the 533 // transformation has been performed or, in case of automatic ILP based 534 // optimizations, by comparing (yet to be defined) performance metrics 535 // before/after the scheduling optimizer 536 // (e.g., #stride-one accesses) 537 isl_union_map *OldSchedule = S.getSchedule(); 538 bool changed = !isl_union_map_is_equal(OldSchedule, NewSchedule); 539 isl_union_map_free(OldSchedule); 540 return changed; 541 } 542 543 namespace { 544 class IslScheduleOptimizer : public ScopPass { 545 public: 546 static char ID; 547 explicit IslScheduleOptimizer() : ScopPass(ID) { LastSchedule = nullptr; } 548 549 ~IslScheduleOptimizer() { isl_schedule_free(LastSchedule); } 550 551 /// @brief Optimize the schedule of the SCoP @p S. 552 bool runOnScop(Scop &S) override; 553 554 /// @brief Print the new schedule for the SCoP @p S. 555 void printScop(raw_ostream &OS, Scop &S) const override; 556 557 /// @brief Register all analyses and transformation required. 558 void getAnalysisUsage(AnalysisUsage &AU) const override; 559 560 /// @brief Release the internal memory. 561 void releaseMemory() override { 562 isl_schedule_free(LastSchedule); 563 LastSchedule = nullptr; 564 } 565 566 private: 567 isl_schedule *LastSchedule; 568 }; 569 } 570 571 char IslScheduleOptimizer::ID = 0; 572 573 bool IslScheduleOptimizer::runOnScop(Scop &S) { 574 575 // Skip empty SCoPs but still allow code generation as it will delete the 576 // loops present but not needed. 577 if (S.getSize() == 0) { 578 S.markAsOptimized(); 579 return false; 580 } 581 582 const Dependences &D = 583 getAnalysis<DependenceInfo>().getDependences(Dependences::AL_Statement); 584 585 if (!D.hasValidDependences()) 586 return false; 587 588 isl_schedule_free(LastSchedule); 589 LastSchedule = nullptr; 590 591 // Build input data. 592 int ValidityKinds = 593 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW; 594 int ProximityKinds; 595 596 if (OptimizeDeps == "all") 597 ProximityKinds = 598 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW; 599 else if (OptimizeDeps == "raw") 600 ProximityKinds = Dependences::TYPE_RAW; 601 else { 602 errs() << "Do not know how to optimize for '" << OptimizeDeps << "'" 603 << " Falling back to optimizing all dependences.\n"; 604 ProximityKinds = 605 Dependences::TYPE_RAW | Dependences::TYPE_WAR | Dependences::TYPE_WAW; 606 } 607 608 isl_union_set *Domain = S.getDomains(); 609 610 if (!Domain) 611 return false; 612 613 isl_union_map *Validity = D.getDependences(ValidityKinds); 614 isl_union_map *Proximity = D.getDependences(ProximityKinds); 615 616 // Simplify the dependences by removing the constraints introduced by the 617 // domains. This can speed up the scheduling time significantly, as large 618 // constant coefficients will be removed from the dependences. The 619 // introduction of some additional dependences reduces the possible 620 // transformations, but in most cases, such transformation do not seem to be 621 // interesting anyway. In some cases this option may stop the scheduler to 622 // find any schedule. 623 if (SimplifyDeps == "yes") { 624 Validity = isl_union_map_gist_domain(Validity, isl_union_set_copy(Domain)); 625 Validity = isl_union_map_gist_range(Validity, isl_union_set_copy(Domain)); 626 Proximity = 627 isl_union_map_gist_domain(Proximity, isl_union_set_copy(Domain)); 628 Proximity = isl_union_map_gist_range(Proximity, isl_union_set_copy(Domain)); 629 } else if (SimplifyDeps != "no") { 630 errs() << "warning: Option -polly-opt-simplify-deps should either be 'yes' " 631 "or 'no'. Falling back to default: 'yes'\n"; 632 } 633 634 DEBUG(dbgs() << "\n\nCompute schedule from: "); 635 DEBUG(dbgs() << "Domain := " << stringFromIslObj(Domain) << ";\n"); 636 DEBUG(dbgs() << "Proximity := " << stringFromIslObj(Proximity) << ";\n"); 637 DEBUG(dbgs() << "Validity := " << stringFromIslObj(Validity) << ";\n"); 638 639 unsigned IslSerializeSCCs; 640 641 if (FusionStrategy == "max") { 642 IslSerializeSCCs = 0; 643 } else if (FusionStrategy == "min") { 644 IslSerializeSCCs = 1; 645 } else { 646 errs() << "warning: Unknown fusion strategy. Falling back to maximal " 647 "fusion.\n"; 648 IslSerializeSCCs = 0; 649 } 650 651 int IslMaximizeBands; 652 653 if (MaximizeBandDepth == "yes") { 654 IslMaximizeBands = 1; 655 } else if (MaximizeBandDepth == "no") { 656 IslMaximizeBands = 0; 657 } else { 658 errs() << "warning: Option -polly-opt-maximize-bands should either be 'yes'" 659 " or 'no'. Falling back to default: 'yes'\n"; 660 IslMaximizeBands = 1; 661 } 662 663 int IslOuterCoincidence; 664 665 if (OuterCoincidence == "yes") { 666 IslOuterCoincidence = 1; 667 } else if (OuterCoincidence == "no") { 668 IslOuterCoincidence = 0; 669 } else { 670 errs() << "warning: Option -polly-opt-outer-coincidence should either be " 671 "'yes' or 'no'. Falling back to default: 'no'\n"; 672 IslOuterCoincidence = 0; 673 } 674 675 isl_options_set_schedule_outer_coincidence(S.getIslCtx(), 676 IslOuterCoincidence); 677 isl_options_set_schedule_serialize_sccs(S.getIslCtx(), IslSerializeSCCs); 678 isl_options_set_schedule_maximize_band_depth(S.getIslCtx(), IslMaximizeBands); 679 isl_options_set_schedule_max_constant_term(S.getIslCtx(), MaxConstantTerm); 680 isl_options_set_schedule_max_coefficient(S.getIslCtx(), MaxCoefficient); 681 isl_options_set_tile_scale_tile_loops(S.getIslCtx(), 0); 682 683 isl_options_set_on_error(S.getIslCtx(), ISL_ON_ERROR_CONTINUE); 684 685 isl_schedule_constraints *ScheduleConstraints; 686 ScheduleConstraints = isl_schedule_constraints_on_domain(Domain); 687 ScheduleConstraints = 688 isl_schedule_constraints_set_proximity(ScheduleConstraints, Proximity); 689 ScheduleConstraints = isl_schedule_constraints_set_validity( 690 ScheduleConstraints, isl_union_map_copy(Validity)); 691 ScheduleConstraints = 692 isl_schedule_constraints_set_coincidence(ScheduleConstraints, Validity); 693 isl_schedule *Schedule; 694 Schedule = isl_schedule_constraints_compute_schedule(ScheduleConstraints); 695 isl_options_set_on_error(S.getIslCtx(), ISL_ON_ERROR_ABORT); 696 697 // In cases the scheduler is not able to optimize the code, we just do not 698 // touch the schedule. 699 if (!Schedule) 700 return false; 701 702 DEBUG({ 703 auto *P = isl_printer_to_str(S.getIslCtx()); 704 P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK); 705 P = isl_printer_print_schedule(P, Schedule); 706 dbgs() << "NewScheduleTree: \n" << isl_printer_get_str(P) << "\n"; 707 isl_printer_free(P); 708 }); 709 710 isl_schedule *NewSchedule = ScheduleTreeOptimizer::optimizeSchedule(Schedule); 711 isl_union_map *NewScheduleMap = isl_schedule_get_map(NewSchedule); 712 713 if (!ScheduleTreeOptimizer::isProfitableSchedule(S, NewScheduleMap)) { 714 isl_union_map_free(NewScheduleMap); 715 isl_schedule_free(NewSchedule); 716 return false; 717 } 718 719 S.setScheduleTree(NewSchedule); 720 S.markAsOptimized(); 721 722 isl_union_map_free(NewScheduleMap); 723 return false; 724 } 725 726 void IslScheduleOptimizer::printScop(raw_ostream &OS, Scop &) const { 727 isl_printer *p; 728 char *ScheduleStr; 729 730 OS << "Calculated schedule:\n"; 731 732 if (!LastSchedule) { 733 OS << "n/a\n"; 734 return; 735 } 736 737 p = isl_printer_to_str(isl_schedule_get_ctx(LastSchedule)); 738 p = isl_printer_print_schedule(p, LastSchedule); 739 ScheduleStr = isl_printer_get_str(p); 740 isl_printer_free(p); 741 742 OS << ScheduleStr << "\n"; 743 } 744 745 void IslScheduleOptimizer::getAnalysisUsage(AnalysisUsage &AU) const { 746 ScopPass::getAnalysisUsage(AU); 747 AU.addRequired<DependenceInfo>(); 748 } 749 750 Pass *polly::createIslScheduleOptimizerPass() { 751 return new IslScheduleOptimizer(); 752 } 753 754 INITIALIZE_PASS_BEGIN(IslScheduleOptimizer, "polly-opt-isl", 755 "Polly - Optimize schedule of SCoP", false, false); 756 INITIALIZE_PASS_DEPENDENCY(DependenceInfo); 757 INITIALIZE_PASS_DEPENDENCY(ScopInfoRegionPass); 758 INITIALIZE_PASS_END(IslScheduleOptimizer, "polly-opt-isl", 759 "Polly - Optimize schedule of SCoP", false, false) 760