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[CUDA codegen] add vectorization infrastructure
Enable vectorization for element-wise ops
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135
iree/compiler/Conversion/LinalgToNVVM/VectorizationPass.cpp
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| // Copyright 2021 Google LLC | ||
| // | ||
| // Licensed under the Apache License, Version 2.0 (the "License"); | ||
| // you may not use this file except in compliance with the License. | ||
| // You may obtain a copy of the License at | ||
| // | ||
| // https://www.apache.org/licenses/LICENSE-2.0 | ||
| // | ||
| // Unless required by applicable law or agreed to in writing, software | ||
| // distributed under the License is distributed on an "AS IS" BASIS, | ||
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| // See the License for the specific language governing permissions and | ||
| // limitations under the License. | ||
|
|
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| #include "iree/compiler/Conversion/CodegenUtils/FunctionUtils.h" | ||
| #include "iree/compiler/Conversion/CodegenUtils/MarkerUtils.h" | ||
| #include "iree/compiler/Conversion/CodegenUtils/TransformUtils.h" | ||
| #include "iree/compiler/Conversion/Common/Transforms.h" | ||
| #include "iree/compiler/Conversion/LinalgToNVVM/Passes.h" | ||
| #include "mlir/Conversion/StandardToSPIRV/StandardToSPIRV.h" | ||
| #include "mlir/Dialect/Linalg/Transforms/Hoisting.h" | ||
| #include "mlir/Dialect/Vector/VectorOps.h" | ||
| #include "mlir/Dialect/Vector/VectorTransforms.h" | ||
| #include "mlir/Transforms/GreedyPatternRewriteDriver.h" | ||
| #include "mlir/Transforms/Passes.h" | ||
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| namespace mlir { | ||
| namespace iree_compiler { | ||
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| //====---------------------------------------------------------------------===// | ||
| // Patterns for vectorization | ||
| //====---------------------------------------------------------------------===// | ||
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| static void populateVectorizationPatterns(OwningRewritePatternList &patterns) { | ||
| linalg::insertVectorizationPatterns<linalg::FillOp, linalg::GenericOp, | ||
| linalg::ContractionOpInterface>( | ||
| patterns, linalg::LinalgVectorizationOptions(), | ||
| linalg::LinalgTransformationFilter( | ||
| Identifier::get(getVectorizeMarker(), patterns.getContext()))); | ||
| } | ||
|
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| static Optional<SmallVector<int64_t, 4>> getNativeVectorSize(Operation *op) { | ||
| if ((OpTrait::hasElementwiseMappableTraits(op) && op->getNumResults() == 1)) { | ||
| if (auto vecType = op->getResultTypes()[0].dyn_cast<VectorType>()) { | ||
| // Map elementwise ops to vec4. | ||
| SmallVector<int64_t, 4> nativeSize(vecType.getRank(), 1); | ||
| nativeSize.back() = 4; | ||
| return nativeSize; | ||
| } | ||
| } else if (auto vt = dyn_cast<VectorTransferOpInterface>(op)) { | ||
| auto rank = vt.getVectorType().getRank(); | ||
| SmallVector<int64_t, 4> nativeSize(rank, 1); | ||
| nativeSize.back() = 4; | ||
| return nativeSize; | ||
| } | ||
| return llvm::None; | ||
| } | ||
|
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| static void populateVectorUnrollPatterns(OwningRewritePatternList &patterns) { | ||
| patterns.add<vector::UnrollVectorPattern>( | ||
| patterns.getContext(), | ||
| vector::UnrollVectorOptions().setNativeShapeFn(getNativeVectorSize)); | ||
| } | ||
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| namespace { | ||
| struct VectorizationPass | ||
| : public PassWrapper<VectorizationPass, OperationPass<FuncOp>> { | ||
| void getDependentDialects(DialectRegistry ®istry) const override { | ||
| registry.insert<vector::VectorDialect>(); | ||
| } | ||
| void runOnOperation() override { | ||
| auto funcOp = getOperation(); | ||
| MLIRContext *context = &getContext(); | ||
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| { | ||
| // Step 1. Vectorize | ||
| OwningRewritePatternList vectorizationPatterns(context); | ||
| populateVectorizationPatterns(vectorizationPatterns); | ||
| (void)applyPatternsAndFoldGreedily(funcOp, | ||
| std::move(vectorizationPatterns)); | ||
| } | ||
| // TODO: This should be a folding of Add into Contract in core but while | ||
| // they live in different dialects, it is not possible without unnatural | ||
| // dependencies. | ||
| funcOp.walk([&](Operation *op) { | ||
| if (auto contract = canonicalizeContractionAdd(op)) | ||
| op->replaceAllUsesWith(contract); | ||
| }); | ||
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| { | ||
| // Step 2. Unroll the vetors to native size and canonicalize. | ||
| OwningRewritePatternList vectorUnrollPatterns(context); | ||
| populateVectorUnrollPatterns(vectorUnrollPatterns); | ||
| (void)applyPatternsAndFoldGreedily(funcOp, | ||
| std::move(vectorUnrollPatterns)); | ||
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| OwningRewritePatternList canonicalizationPatterns1(funcOp.getContext()); | ||
| vector::populateVectorToVectorCanonicalizationPatterns( | ||
| canonicalizationPatterns1); | ||
| vector::populateVectorToVectorTransformationPatterns( | ||
| canonicalizationPatterns1); | ||
| (void)applyPatternsAndFoldGreedily(funcOp, | ||
| std::move(canonicalizationPatterns1)); | ||
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| OwningRewritePatternList canonicalizationPatterns2(funcOp.getContext()); | ||
| vector::populateVectorSlicesLoweringPatterns(canonicalizationPatterns2); | ||
| (void)applyPatternsAndFoldGreedily(funcOp, | ||
| std::move(canonicalizationPatterns2)); | ||
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| linalg::hoistRedundantVectorTransfers(funcOp); | ||
| } | ||
| { | ||
| // Step 3. Canonicalize the transfer ops generated. | ||
| RewritePatternSet vectorToLoopsPatterns(context); | ||
| VectorTransferToSCFOptions vectorToSCFOptions; | ||
| vectorToSCFOptions.setUnroll(true); | ||
| populateVectorToSCFConversionPatterns(vectorToLoopsPatterns, | ||
| vectorToSCFOptions); | ||
| populateStdLegalizationPatternsForSPIRVLowering(vectorToLoopsPatterns); | ||
| (void)applyPatternsAndFoldGreedily(funcOp, | ||
| std::move(vectorToLoopsPatterns)); | ||
| } | ||
| } | ||
| }; | ||
| } // namespace | ||
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| std::unique_ptr<OperationPass<FuncOp>> createVectorizationPass() { | ||
| return std::make_unique<VectorizationPass>(); | ||
| } | ||
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| static PassRegistration<VectorizationPass> pass( | ||
| "iree-codegen-cuda-vectorization", "Pass to convert linalg into Vector."); | ||
|
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||
| } // namespace iree_compiler | ||
| } // namespace mlir |
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