1 //===- TestLinalgTransforms.cpp - Test Linalg transformation patterns -----===// 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 file implements logic for testing Linalg transformations. 10 // 11 //===----------------------------------------------------------------------===// 12 13 #include "mlir/Dialect/Affine/IR/AffineOps.h" 14 #include "mlir/Dialect/Arithmetic/IR/Arithmetic.h" 15 #include "mlir/Dialect/GPU/GPUDialect.h" 16 #include "mlir/Dialect/Linalg/IR/Linalg.h" 17 #include "mlir/Dialect/Linalg/Passes.h" 18 #include "mlir/Dialect/Linalg/Transforms/HoistPadding.h" 19 #include "mlir/Dialect/Linalg/Transforms/Hoisting.h" 20 #include "mlir/Dialect/Linalg/Transforms/Transforms.h" 21 #include "mlir/Dialect/Linalg/Utils/Utils.h" 22 #include "mlir/Dialect/StandardOps/IR/Ops.h" 23 #include "mlir/Dialect/Vector/VectorOps.h" 24 #include "mlir/Pass/PassManager.h" 25 #include "mlir/Transforms/GreedyPatternRewriteDriver.h" 26 27 #include "llvm/ADT/SetVector.h" 28 #include "llvm/ADT/SmallVector.h" 29 30 using namespace mlir; 31 using namespace mlir::linalg; 32 33 namespace { 34 struct TestLinalgTransforms 35 : public PassWrapper<TestLinalgTransforms, FunctionPass> { 36 TestLinalgTransforms() = default; 37 TestLinalgTransforms(const TestLinalgTransforms &pass) : PassWrapper(pass) {} 38 39 void getDependentDialects(DialectRegistry ®istry) const override { 40 // clang-format off 41 registry.insert<AffineDialect, 42 memref::MemRefDialect, 43 scf::SCFDialect, 44 StandardOpsDialect, 45 vector::VectorDialect, 46 gpu::GPUDialect>(); 47 // clang-format on 48 } 49 StringRef getArgument() const final { 50 return "test-linalg-transform-patterns"; 51 } 52 StringRef getDescription() const final { 53 return "Test Linalg transformation patterns by applying them greedily."; 54 } 55 56 void runOnFunction() override; 57 58 Option<bool> testPatterns{*this, "test-patterns", 59 llvm::cl::desc("Test a mixed set of patterns"), 60 llvm::cl::init(false)}; 61 Option<bool> testMatmulToVectorPatterns1dTiling{ 62 *this, "test-matmul-to-vector-patterns-tile-1d", 63 llvm::cl::desc( 64 "Test a fused pass that applies patterns from matmul to vectors via " 65 "1-d tiling"), 66 llvm::cl::init(false)}; 67 Option<bool> testMatmulToVectorPatterns2dTiling{ 68 *this, "test-matmul-to-vector-patterns-tile-2d", 69 llvm::cl::desc( 70 "Test a fused pass that applies patterns from matmul to vectors via " 71 "2-d tiling"), 72 llvm::cl::init(false)}; 73 Option<bool> testPromotionOptions{*this, "test-linalg-promotion-options", 74 llvm::cl::desc("Test promotion options"), 75 llvm::cl::init(false)}; 76 Option<bool> testTileAndDistributionOptions{ 77 *this, "test-tile-and-distribute-options", 78 llvm::cl::desc("Test tile and distribute options"), 79 llvm::cl::init(false)}; 80 Option<bool> testVectorTransferForwardingPatterns{ 81 *this, "test-vector-transfer-forwarding-patterns", 82 llvm::cl::desc( 83 "Test a fused pass that forwards linalg.copy to vector.transfer"), 84 llvm::cl::init(false)}; 85 Option<bool> testGenericToVectorPattern{ 86 *this, "test-linalg-to-vector-patterns", 87 llvm::cl::desc("Test a set of patterns that rewrite a linalg contraction " 88 "in vector.contract form"), 89 llvm::cl::init(false)}; 90 Option<bool> testTilePattern{*this, "test-tile-pattern", 91 llvm::cl::desc("Test tile pattern"), 92 llvm::cl::init(false)}; 93 Option<bool> testTileScalarizeDynamicDims{ 94 *this, "test-tile-scalarize-dynamic-dims", 95 llvm::cl::desc("Test tiling of dynamic dims by 1"), 96 llvm::cl::init(false)}; 97 Option<bool> testTransformPadTensor{ 98 *this, "test-transform-pad-tensor", 99 llvm::cl::desc("Test transform pad tensor by copying with generic ops"), 100 llvm::cl::init(false)}; 101 Option<bool> testGeneralizePadTensor{ 102 *this, "test-generalize-pad-tensor", 103 llvm::cl::desc("Test transform pad tensor by copying with generic ops"), 104 llvm::cl::init(false)}; 105 Option<bool> testSwapSubTensorPadTensor{ 106 *this, "test-swap-subtensor-padtensor", 107 llvm::cl::desc("Test rewrite of subtensor(pad_tensor) into " 108 "pad_tensor(subtensor)"), 109 llvm::cl::init(false)}; 110 ListOption<int64_t> peeledLoops{ 111 *this, "peeled-loops", 112 llvm::cl::desc("Loops to be peeled when test-tile-pattern"), 113 llvm::cl::ZeroOrMore, llvm::cl::MiscFlags::CommaSeparated}; 114 ListOption<int64_t> tileSizes{ 115 *this, "tile-sizes", 116 llvm::cl::desc("Linalg tile sizes for test-tile-pattern"), 117 llvm::cl::ZeroOrMore, llvm::cl::MiscFlags::CommaSeparated}; 118 ListOption<unsigned> testTiledLoopPeeling{ 119 *this, "test-tiled-loop-peeling", 120 llvm::cl::desc("Test peeling of linalg.tiled_loop ops"), 121 llvm::cl::OneOrMore, llvm::cl::MiscFlags::CommaSeparated}; 122 Option<bool> skipPartial{ 123 *this, "skip-partial", 124 llvm::cl::desc("Skip loops inside partial iterations during peeling"), 125 llvm::cl::init(false)}; 126 Option<std::string> loopType{ 127 *this, "loop-type", 128 llvm::cl::desc("Specify the type of loops to generate: for, parallel or " 129 "tiled_loop"), 130 llvm::cl::init("for")}; 131 }; 132 } // namespace 133 134 static void applyPatterns(FuncOp funcOp) { 135 MLIRContext *ctx = funcOp.getContext(); 136 RewritePatternSet patterns(ctx); 137 138 //===--------------------------------------------------------------------===// 139 // Linalg tiling patterns. 140 //===--------------------------------------------------------------------===// 141 patterns.add<LinalgTilingPattern>( 142 MatmulOp::getOperationName(), ctx, 143 LinalgTilingOptions().setTileSizes({2000, 3000, 4000}), 144 LinalgTransformationFilter(StringAttr::get(ctx, "MEM"), 145 StringAttr::get(ctx, "L3"))); 146 patterns.add<LinalgTilingPattern>( 147 MatmulOp::getOperationName(), ctx, 148 LinalgTilingOptions().setTileSizes({200, 300, 400}), 149 LinalgTransformationFilter(StringAttr::get(ctx, "L3"), 150 StringAttr::get(ctx, "L2"))); 151 patterns.add<LinalgTilingPattern>( 152 MatmulOp::getOperationName(), ctx, 153 LinalgTilingOptions().setTileSizes({20, 30, 40}), 154 LinalgTransformationFilter(StringAttr::get(ctx, "L2"), 155 StringAttr::get(ctx, "L1"))); 156 patterns.add<LinalgTilingPattern>( 157 MatmulOp::getOperationName(), ctx, 158 LinalgTilingOptions().setTileSizes({2, 3, 4}), 159 LinalgTransformationFilter(StringAttr::get(ctx, "L1"), 160 StringAttr::get(ctx, "REG"))); 161 162 patterns.add<LinalgTilingPattern>( 163 MatvecOp::getOperationName(), ctx, 164 LinalgTilingOptions().setTileSizes({5, 6}).setLoopType( 165 LinalgTilingLoopType::ParallelLoops), 166 LinalgTransformationFilter(ArrayRef<StringAttr>{}, 167 StringAttr::get(ctx, "L1"))); 168 169 patterns.add<LinalgTilingPattern>( 170 DotOp::getOperationName(), ctx, LinalgTilingOptions().setTileSizes(8000), 171 LinalgTransformationFilter( 172 ArrayRef<StringAttr>{StringAttr::get(ctx, "MEM"), 173 StringAttr::get(ctx, "L3"), 174 StringAttr::get(ctx, "L2")}, 175 StringAttr::get(ctx, "REG"))); 176 177 //===--------------------------------------------------------------------===// 178 // Linalg tiling and permutation patterns. 179 //===--------------------------------------------------------------------===// 180 patterns.add<LinalgTilingPattern>( 181 MatmulOp::getOperationName(), ctx, 182 LinalgTilingOptions() 183 .setTileSizes({2000, 3000, 4000}) 184 .setInterchange({1, 2, 0}), 185 LinalgTransformationFilter(StringAttr::get(ctx, "__with_perm__"), 186 StringAttr::get(ctx, "L2__with_perm__"))); 187 patterns.add<LinalgTilingPattern>( 188 MatmulOp::getOperationName(), ctx, 189 LinalgTilingOptions() 190 .setTileSizes({200, 300, 400}) 191 .setInterchange({1, 0, 2}), 192 LinalgTransformationFilter(StringAttr::get(ctx, "L2__with_perm__"), 193 StringAttr::get(ctx, "L1__with_perm__"))); 194 patterns.add<LinalgTilingPattern>( 195 MatmulOp::getOperationName(), ctx, 196 LinalgTilingOptions().setTileSizes({20, 30, 40}), 197 LinalgTransformationFilter(StringAttr::get(ctx, "L1__with_perm__"), 198 StringAttr::get(ctx, "REG__with_perm__"))); 199 200 patterns.add<LinalgTilingPattern>( 201 MatvecOp::getOperationName(), ctx, 202 LinalgTilingOptions().setTileSizes({5, 6}).setInterchange({1, 0}), 203 LinalgTransformationFilter(StringAttr::get(ctx, "__with_perm__"), 204 StringAttr::get(ctx, "L1__with_perm__"))); 205 206 patterns.add<LinalgTilingPattern>( 207 MatmulOp::getOperationName(), ctx, 208 LinalgTilingOptions() 209 .setTileSizes({16, 8, 4}) 210 .setInterchange({1, 2, 0}) 211 .setLoopType(LinalgTilingLoopType::ParallelLoops), 212 LinalgTransformationFilter( 213 StringAttr::get(ctx, "par__with_perm__"), 214 StringAttr::get(ctx, "after_par__with_perm__"))); 215 216 //===--------------------------------------------------------------------===// 217 // Linalg to loops patterns. 218 //===--------------------------------------------------------------------===// 219 patterns.add<LinalgLoweringPattern<DotOp>>( 220 ctx, 221 /*loweringType=*/LinalgLoweringType::Loops, 222 LinalgTransformationFilter(StringAttr::get(ctx, "REG"))); 223 224 //===--------------------------------------------------------------------===// 225 // Linalg distribution patterns. 226 //===--------------------------------------------------------------------===// 227 LinalgLoopDistributionOptions distributionOptions; 228 229 //===--------------------------------------------------------------------===// 230 // Linalg to vector contraction patterns. 231 //===--------------------------------------------------------------------===// 232 patterns.add<LinalgVectorizationPattern>( 233 ctx, LinalgTransformationFilter(StringAttr::get(ctx, "VECTORIZE")) 234 .addOpFilter<MatmulOp, FillOp, CopyOp, GenericOp>()); 235 236 //===--------------------------------------------------------------------===// 237 // Linalg generic interchange pattern. 238 //===--------------------------------------------------------------------===// 239 patterns.add<GenericOpInterchangePattern>( 240 ctx, 241 /*interchangeVector=*/ArrayRef<unsigned>{1, 2, 0}, 242 LinalgTransformationFilter(ArrayRef<StringAttr>{}, 243 StringAttr::get(ctx, "PERMUTED"))); 244 245 //===--------------------------------------------------------------------===// 246 // Linalg subview operands promotion. 247 //===--------------------------------------------------------------------===// 248 patterns.add<LinalgPromotionPattern<MatmulOp>>( 249 ctx, LinalgPromotionOptions().setUseFullTileBuffersByDefault(true), 250 LinalgTransformationFilter(StringAttr::get(ctx, "_promote_views_"), 251 StringAttr::get(ctx, "_views_promoted_"))); 252 patterns.add<LinalgPromotionPattern<MatmulOp>>( 253 ctx, 254 LinalgPromotionOptions() 255 .setOperandsToPromote({0}) 256 .setUseFullTileBuffersByDefault(true), 257 LinalgTransformationFilter( 258 StringAttr::get(ctx, "_promote_first_view_"), 259 StringAttr::get(ctx, "_first_view_promoted_"))); 260 patterns.add<LinalgPromotionPattern<FillOp>>( 261 ctx, 262 LinalgPromotionOptions() 263 .setOperandsToPromote({1}) 264 .setUseFullTileBuffers({false, true}) 265 .setAlignment(32), 266 LinalgTransformationFilter( 267 StringAttr::get(ctx, "_promote_views_aligned_"), 268 StringAttr::get(ctx, "_views_aligned_promoted_"))); 269 270 (void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns)); 271 272 // Drop the marker. 273 funcOp.walk([](LinalgOp op) { 274 op->removeAttr(LinalgTransforms::kLinalgTransformMarker); 275 }); 276 } 277 278 static void fillL1TilingAndMatmulToVectorPatterns( 279 FuncOp funcOp, StringRef startMarker, 280 SmallVectorImpl<RewritePatternSet> &patternsVector) { 281 MLIRContext *ctx = funcOp.getContext(); 282 patternsVector.emplace_back( 283 ctx, std::make_unique<LinalgTilingPattern>( 284 MatmulOp::getOperationName(), ctx, 285 LinalgTilingOptions() 286 .setTileSizes({8, 12, 16}) 287 .setInterchange({1, 0, 2}), 288 LinalgTransformationFilter(StringAttr::get(ctx, startMarker), 289 StringAttr::get(ctx, "L1")))); 290 291 patternsVector.emplace_back( 292 ctx, 293 std::make_unique<LinalgPromotionPattern<MatmulOp>>( 294 ctx, LinalgPromotionOptions().setUseFullTileBuffersByDefault(true), 295 LinalgTransformationFilter(StringAttr::get(ctx, "L1"), 296 StringAttr::get(ctx, "VEC")))); 297 298 patternsVector.emplace_back( 299 ctx, std::make_unique<LinalgVectorizationPattern>( 300 MatmulOp::getOperationName(), ctx, LinalgVectorizationOptions(), 301 LinalgTransformationFilter(StringAttr::get(ctx, "VEC")))); 302 patternsVector.back().add<LinalgVectorizationPattern>( 303 ctx, LinalgTransformationFilter().addOpFilter<FillOp, CopyOp>()); 304 } 305 306 //===----------------------------------------------------------------------===// 307 // Test promotion callbacks 308 //===----------------------------------------------------------------------===// 309 310 // Allocation call back 311 static Optional<Value> allocCallBackFn(OpBuilder &b, memref::SubViewOp subView, 312 ArrayRef<Value> boundingSubViewSize, 313 DataLayout &layout) { 314 SmallVector<int64_t, 4> shape(boundingSubViewSize.size(), -1); 315 return b 316 .create<memref::AllocOp>( 317 subView.getLoc(), 318 MemRefType::get(shape, subView.getType().getElementType(), 319 /*affineMapComposition =*/{}, 3), 320 boundingSubViewSize) 321 .getResult(); 322 } 323 324 // Deallocation callback 325 static LogicalResult deallocCallBackFn(OpBuilder &b, Value buffer) { 326 b.create<memref::DeallocOp>(buffer.getLoc(), buffer); 327 return success(); 328 } 329 330 // Copy in call back 331 static LogicalResult copyCallBackFn(OpBuilder &b, Value src, Value dst, 332 bool isOutput) { 333 auto floatType = src.getType().cast<MemRefType>().getElementType(); 334 if (!floatType.isa<FloatType>()) 335 return failure(); 336 if (!isOutput) { 337 Value cst = b.create<arith::ConstantOp>(src.getLoc(), 338 FloatAttr::get(floatType, 42.0)); 339 b.create<FillOp>(src.getLoc(), cst, dst); 340 } 341 b.create<CopyOp>(src.getLoc(), src, dst); 342 return success(); 343 } 344 345 static void fillPromotionCallBackPatterns(MLIRContext *ctx, 346 RewritePatternSet &patterns) { 347 patterns.add<LinalgTilingPattern>( 348 MatmulOp::getOperationName(), ctx, 349 LinalgTilingOptions().setTileSizes({16, 16, 16}), 350 LinalgTransformationFilter(StringAttr::get(ctx, "START"), 351 StringAttr::get(ctx, "PROMOTE"))); 352 patterns.add<LinalgPromotionPattern<MatmulOp>>( 353 ctx, 354 LinalgPromotionOptions() 355 .setOperandsToPromote({0, 2}) 356 .setUseFullTileBuffers({false, false}) 357 .setAllocationDeallocationFns(allocCallBackFn, deallocCallBackFn) 358 .setCopyInOutFns( 359 [](OpBuilder &b, Value src, Value dst) -> LogicalResult { 360 return copyCallBackFn(b, src, dst, false); 361 }, 362 [](OpBuilder &b, Value src, Value dst) -> LogicalResult { 363 return copyCallBackFn(b, src, dst, true); 364 }), 365 LinalgTransformationFilter(StringAttr::get(ctx, "PROMOTE"))); 366 } 367 368 template <typename IdOp, typename NProcsOp> 369 static SmallVector<ProcInfo, 2> 370 getGpuProcIds(OpBuilder &b, Location loc, ArrayRef<Range> parallelLoopRanges) { 371 size_t count = std::min<size_t>(3, parallelLoopRanges.size()); 372 SmallVector<ProcInfo, 2> procInfo(count); 373 const char *xyz[] = {"x", "y", "z"}; 374 Type indexType = b.getIndexType(); 375 for (unsigned i = 0; i < count; ++i) { 376 procInfo[count - 1 - i] = { 377 b.create<IdOp>(loc, indexType, b.getStringAttr(xyz[i])), 378 b.create<NProcsOp>(loc, indexType, b.getStringAttr(xyz[i]))}; 379 } 380 return procInfo; 381 } 382 383 static void fillTileAndDistributePatterns(MLIRContext *context, 384 RewritePatternSet &patterns) { 385 { 386 LinalgLoopDistributionOptions cyclicNprocsEqNiters; 387 cyclicNprocsEqNiters.distributionMethod.resize( 388 2, DistributionMethod::CyclicNumProcsEqNumIters); 389 cyclicNprocsEqNiters.procInfo = 390 getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>; 391 patterns.add<LinalgTilingPattern>( 392 MatmulOp::getOperationName(), context, 393 LinalgTilingOptions() 394 .setTileSizes({8, 8, 4}) 395 .setLoopType(LinalgTilingLoopType::ParallelLoops) 396 .setDistributionOptions(cyclicNprocsEqNiters), 397 LinalgTransformationFilter( 398 StringAttr::get(context, "distribute1"), 399 StringAttr::get(context, "after_distribute1"))); 400 } 401 402 { 403 LinalgLoopDistributionOptions cyclicNprocsGeNiters; 404 cyclicNprocsGeNiters.distributionMethod.resize( 405 2, DistributionMethod::CyclicNumProcsGeNumIters); 406 cyclicNprocsGeNiters.procInfo = 407 getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>; 408 patterns.add<LinalgTilingPattern>( 409 MatmulOp::getOperationName(), context, 410 LinalgTilingOptions() 411 .setTileSizes({8, 8, 4}) 412 .setLoopType(LinalgTilingLoopType::ParallelLoops) 413 .setDistributionOptions(cyclicNprocsGeNiters), 414 LinalgTransformationFilter( 415 StringAttr::get(context, "distribute2"), 416 StringAttr::get(context, "after_distribute2"))); 417 } 418 419 { 420 LinalgLoopDistributionOptions cyclicNprocsDefault; 421 cyclicNprocsDefault.distributionMethod.resize(2, 422 DistributionMethod::Cyclic); 423 cyclicNprocsDefault.procInfo = 424 getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>; 425 patterns.add<LinalgTilingPattern>( 426 MatmulOp::getOperationName(), context, 427 LinalgTilingOptions() 428 .setTileSizes({8, 8, 4}) 429 .setLoopType(LinalgTilingLoopType::ParallelLoops) 430 .setDistributionOptions(cyclicNprocsDefault), 431 LinalgTransformationFilter( 432 StringAttr::get(context, "distribute3"), 433 StringAttr::get(context, "after_distribute3"))); 434 } 435 436 { 437 LinalgLoopDistributionOptions cyclicNprocsMixed1; 438 cyclicNprocsMixed1.distributionMethod = { 439 DistributionMethod::CyclicNumProcsEqNumIters, 440 DistributionMethod::CyclicNumProcsGeNumIters}; 441 cyclicNprocsMixed1.procInfo = getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>; 442 patterns.add<LinalgTilingPattern>( 443 MatmulOp::getOperationName(), context, 444 LinalgTilingOptions() 445 .setTileSizes({8, 8, 4}) 446 .setLoopType(LinalgTilingLoopType::ParallelLoops) 447 .setDistributionOptions(cyclicNprocsMixed1), 448 LinalgTransformationFilter( 449 StringAttr::get(context, "distribute4"), 450 StringAttr::get(context, "after_distribute4"))); 451 } 452 453 { 454 LinalgLoopDistributionOptions cyclicNprocsMixed2; 455 cyclicNprocsMixed2.distributionMethod = { 456 DistributionMethod::CyclicNumProcsGeNumIters, 457 DistributionMethod::Cyclic}; 458 cyclicNprocsMixed2.procInfo = getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>; 459 patterns.add<LinalgTilingPattern>( 460 MatmulOp::getOperationName(), context, 461 LinalgTilingOptions() 462 .setTileSizes({8, 8, 4}) 463 .setLoopType(LinalgTilingLoopType::ParallelLoops) 464 .setDistributionOptions(cyclicNprocsMixed2), 465 LinalgTransformationFilter( 466 StringAttr::get(context, "distribute5"), 467 StringAttr::get(context, "after_distribute5"))); 468 } 469 470 { 471 LinalgLoopDistributionOptions cyclicNprocsMixed3; 472 cyclicNprocsMixed3.distributionMethod = { 473 DistributionMethod::Cyclic, 474 DistributionMethod::CyclicNumProcsEqNumIters}; 475 cyclicNprocsMixed3.procInfo = getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>; 476 477 patterns.add<LinalgTilingPattern>( 478 MatmulOp::getOperationName(), context, 479 LinalgTilingOptions() 480 .setTileSizes({8, 8, 4}) 481 .setLoopType(LinalgTilingLoopType::ParallelLoops) 482 .setDistributionOptions(cyclicNprocsMixed3), 483 LinalgTransformationFilter( 484 StringAttr::get(context, "distribute6"), 485 StringAttr::get(context, "after_distribute6"))); 486 } 487 488 { 489 LinalgLoopDistributionOptions cyclicNprocsEqNiters; 490 cyclicNprocsEqNiters.distributionMethod.resize(2, 491 DistributionMethod::Cyclic); 492 cyclicNprocsEqNiters.procInfo = 493 getGpuProcIds<gpu::BlockIdOp, gpu::GridDimOp>; 494 patterns.add<LinalgTilingPattern>( 495 MatmulOp::getOperationName(), context, 496 LinalgTilingOptions() 497 .setTileSizes({8, 8, 4}) 498 .setLoopType(LinalgTilingLoopType::Loops) 499 .setDistributionOptions(cyclicNprocsEqNiters), 500 LinalgTransformationFilter( 501 StringAttr::get(context, "tensors_distribute1"), 502 StringAttr::get(context, "tensors_after_distribute1"))); 503 } 504 } 505 506 static void 507 applyMatmulToVectorPatterns(FuncOp funcOp, 508 bool testMatmulToVectorPatterns1dTiling, 509 bool testMatmulToVectorPatterns2dTiling) { 510 MLIRContext *ctx = funcOp.getContext(); 511 SmallVector<RewritePatternSet, 4> stage1Patterns; 512 if (testMatmulToVectorPatterns1dTiling) { 513 fillL1TilingAndMatmulToVectorPatterns(funcOp, "START", stage1Patterns); 514 } else if (testMatmulToVectorPatterns2dTiling) { 515 stage1Patterns.emplace_back( 516 ctx, std::make_unique<LinalgTilingPattern>( 517 MatmulOp::getOperationName(), ctx, 518 LinalgTilingOptions() 519 .setTileSizes({768, 264, 768}) 520 .setInterchange({1, 2, 0}), 521 LinalgTransformationFilter(StringAttr::get(ctx, "START"), 522 StringAttr::get(ctx, "L2")))); 523 fillL1TilingAndMatmulToVectorPatterns(funcOp, "L2", stage1Patterns); 524 } 525 { 526 // Canonicalization patterns 527 RewritePatternSet canonicalizationPatterns(funcOp.getContext()); 528 vector::populateVectorTransferPermutationMapLoweringPatterns( 529 canonicalizationPatterns); 530 vector::populateVectorReductionToContractPatterns(canonicalizationPatterns); 531 stage1Patterns.push_back(std::move(canonicalizationPatterns)); 532 } 533 SmallVector<FrozenRewritePatternSet, 4> frozenStage1Patterns; 534 llvm::move(stage1Patterns, std::back_inserter(frozenStage1Patterns)); 535 FrozenRewritePatternSet stage2Patterns = 536 getLinalgTilingCanonicalizationPatterns(ctx); 537 (void)applyStagedPatterns(funcOp, frozenStage1Patterns, stage2Patterns); 538 } 539 540 static void applyVectorTransferForwardingPatterns(FuncOp funcOp) { 541 RewritePatternSet forwardPattern(funcOp.getContext()); 542 forwardPattern.add<LinalgCopyVTRForwardingPattern>(funcOp.getContext()); 543 forwardPattern.add<LinalgCopyVTWForwardingPattern>(funcOp.getContext()); 544 (void)applyPatternsAndFoldGreedily(funcOp, std::move(forwardPattern)); 545 } 546 547 static void applyLinalgToVectorPatterns(FuncOp funcOp) { 548 RewritePatternSet patterns(funcOp.getContext()); 549 patterns.add<LinalgVectorizationPattern>( 550 funcOp.getContext(), 551 LinalgTransformationFilter() 552 .addOpFilter<ContractionOpInterface, FillOp, CopyOp, GenericOp>()); 553 populatePadTensorOpVectorizationPatterns(patterns); 554 populateConvolutionVectorizationPatterns(patterns); 555 (void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns)); 556 } 557 558 static void applyPadTensorToGenericPatterns(FuncOp funcOp) { 559 RewritePatternSet patterns(funcOp.getContext()); 560 patterns.add<PadTensorOpTransformationPattern>(funcOp.getContext()); 561 (void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns)); 562 } 563 564 static void applyGeneralizePadTensorPatterns(FuncOp funcOp) { 565 RewritePatternSet patterns(funcOp.getContext()); 566 patterns.add<GeneralizePadTensorOpPattern>(funcOp.getContext()); 567 (void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns)); 568 } 569 570 static void applyExtractSliceOfPadTensorSwapPattern(FuncOp funcOp) { 571 RewritePatternSet patterns(funcOp.getContext()); 572 patterns.add<ExtractSliceOfPadTensorSwapPattern>(funcOp.getContext()); 573 (void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns)); 574 } 575 576 static void applyTilePattern(FuncOp funcOp, const std::string &loopType, 577 ArrayRef<int64_t> tileSizes, 578 ArrayRef<int64_t> peeledLoops, 579 bool scalarizeDynamicDims) { 580 MLIRContext *context = funcOp.getContext(); 581 RewritePatternSet tilingPattern(context); 582 LinalgTilingLoopType type = 583 llvm::StringSwitch<LinalgTilingLoopType>(loopType) 584 .Case("for", LinalgTilingLoopType::Loops) 585 .Case("affine", LinalgTilingLoopType::AffineLoops) 586 .Case("parallel", LinalgTilingLoopType::ParallelLoops) 587 .Case("tiled_loop", LinalgTilingLoopType::TiledLoops); 588 auto linalgTilingOptions = linalg::LinalgTilingOptions() 589 .setPeeledLoops(peeledLoops) 590 .setLoopType(type); 591 if (scalarizeDynamicDims) { 592 linalgTilingOptions.scalarizeDynamicDims(); 593 assert(tileSizes.empty() && 594 "tileSizes and scalarizeDynamicDims is mutually exclusive"); 595 } else { 596 linalgTilingOptions.setTileSizes(tileSizes); 597 } 598 linalg::LinalgTransformationFilter f(StringAttr::get(context, "tile")); 599 TilingPatterns<linalg::MatmulOp, linalg::GenericOp>::insert( 600 tilingPattern, linalgTilingOptions, f); 601 (void)applyPatternsAndFoldGreedily(funcOp, std::move(tilingPattern)); 602 } 603 604 static constexpr char kPeeledLoopsLabel[] = "__peeled_loops__"; 605 static constexpr char kPartialIterationLabel[] = "__partial_iteration__"; 606 607 namespace { 608 /// Peel TiledLoopOps, i.e., split them into two loops: One loop where the 609 /// `idx`-th loop contains only "full" iterations and a second loop for the 610 /// remaining partial iteration (if any). 611 struct TiledLoopPeelingPattern : public OpRewritePattern<TiledLoopOp> { 612 TiledLoopPeelingPattern(MLIRContext *ctx, int64_t idx, bool skipPartial) 613 : OpRewritePattern<TiledLoopOp>(ctx), idx(idx), skipPartial(skipPartial) { 614 } 615 616 LogicalResult matchAndRewrite(TiledLoopOp loopOp, 617 PatternRewriter &rewriter) const override { 618 SmallVector<int64_t> peeledLoops; 619 if (loopOp->hasAttr(kPeeledLoopsLabel)) { 620 auto attr = loopOp->getAttr(kPeeledLoopsLabel).cast<ArrayAttr>(); 621 peeledLoops = 622 llvm::to_vector<4>(llvm::map_range(attr, [](Attribute attr) { 623 return attr.cast<IntegerAttr>().getInt(); 624 })); 625 // Check if the loop was already peeled. 626 if (llvm::find(peeledLoops, idx) != peeledLoops.end()) 627 return failure(); 628 } 629 if (skipPartial && loopOp->hasAttr(kPartialIterationLabel)) 630 // No peeling of loop nests with a partial iteration. 631 return failure(); 632 633 if (static_cast<int64_t>(loopOp.iterator_types().size()) <= idx) 634 return failure(); 635 636 // Peel loop and canonicalize. 637 TiledLoopOp result; 638 if (failed(linalg::peelAndCanonicalizeTiledLoop(rewriter, loopOp, idx, 639 result))) 640 return failure(); 641 642 // Apply label, so that the same loop is not rewritten a second time. 643 peeledLoops.push_back(idx); 644 rewriter.updateRootInPlace(loopOp, [&]() { 645 loopOp->setAttr(kPeeledLoopsLabel, rewriter.getI64ArrayAttr(peeledLoops)); 646 }); 647 result->setAttr(kPeeledLoopsLabel, rewriter.getI64ArrayAttr(peeledLoops)); 648 result->setAttr(kPartialIterationLabel, rewriter.getUnitAttr()); 649 650 return success(); 651 } 652 653 /// Index of loop to peel. 654 int64_t idx; 655 656 /// If set to true, do not peel TiledLoopOps with a partial iteration. 657 bool skipPartial; 658 }; 659 } // namespace 660 661 static void applyTiledLoopPeelingPattern(FuncOp funcOp, 662 ArrayRef<unsigned> loops, 663 bool skipPartial) { 664 MLIRContext *ctx = funcOp.getContext(); 665 RewritePatternSet patterns(ctx); 666 for (unsigned idx : loops) 667 patterns.add<TiledLoopPeelingPattern>(ctx, idx, skipPartial); 668 (void)applyPatternsAndFoldGreedily(funcOp, std::move(patterns)); 669 670 // Drop the markers. 671 funcOp.walk([](TiledLoopOp op) { 672 op->removeAttr(kPeeledLoopsLabel); 673 op->removeAttr(kPartialIterationLabel); 674 }); 675 } 676 677 /// Apply transformations specified as patterns. 678 void TestLinalgTransforms::runOnFunction() { 679 auto lambda = [&](void *) { 680 getFunction().walk([](LinalgOp op) { 681 op->removeAttr(LinalgTransforms::kLinalgTransformMarker); 682 }); 683 }; 684 std::unique_ptr<void, decltype(lambda)> cleanupGuard{(void *)1, lambda}; 685 686 if (testPromotionOptions) { 687 RewritePatternSet patterns(&getContext()); 688 fillPromotionCallBackPatterns(&getContext(), patterns); 689 (void)applyPatternsAndFoldGreedily(getFunction(), std::move(patterns)); 690 return; 691 } 692 if (testTileAndDistributionOptions) { 693 RewritePatternSet patterns(&getContext()); 694 fillTileAndDistributePatterns(&getContext(), patterns); 695 (void)applyPatternsAndFoldGreedily(getFunction(), std::move(patterns)); 696 return; 697 } 698 if (testPatterns) 699 return applyPatterns(getFunction()); 700 if (testMatmulToVectorPatterns1dTiling || testMatmulToVectorPatterns2dTiling) 701 return applyMatmulToVectorPatterns(getFunction(), 702 testMatmulToVectorPatterns1dTiling, 703 testMatmulToVectorPatterns2dTiling); 704 if (testVectorTransferForwardingPatterns) 705 return applyVectorTransferForwardingPatterns(getFunction()); 706 if (testGenericToVectorPattern) 707 return applyLinalgToVectorPatterns(getFunction()); 708 if (testTransformPadTensor) 709 return applyPadTensorToGenericPatterns(getFunction()); 710 if (testGeneralizePadTensor) 711 return applyGeneralizePadTensorPatterns(getFunction()); 712 if (testSwapSubTensorPadTensor) 713 return applyExtractSliceOfPadTensorSwapPattern(getFunction()); 714 if (testTiledLoopPeeling.hasValue()) 715 return applyTiledLoopPeelingPattern(getFunction(), testTiledLoopPeeling, 716 skipPartial); 717 if (testTilePattern) 718 return applyTilePattern(getFunction(), loopType, tileSizes, peeledLoops, 719 /*scalarizeDynamicDims=*/false); 720 if (testTileScalarizeDynamicDims) 721 return applyTilePattern(getFunction(), loopType, tileSizes, 722 /*peeledLoops=*/{}, /*scalarizeDynamicDims=*/true); 723 } 724 725 namespace mlir { 726 namespace test { 727 void registerTestLinalgTransforms() { 728 PassRegistration<TestLinalgTransforms>(); 729 } 730 } // namespace test 731 } // namespace mlir 732