67d0d7ac0a
The patch introduces the required changes to update the pass declarations and definitions to use the new autogenerated files and allow dropping the old infrastructure. Reviewed By: mehdi_amini, rriddle Differential Review: https://reviews.llvm.org/D132838
83 lines
2.9 KiB
C++
83 lines
2.9 KiB
C++
//===- SCFToGPUPass.cpp - Convert a loop nest to a GPU kernel -----------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/Conversion/SCFToGPU/SCFToGPUPass.h"
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#include "mlir/Conversion/SCFToGPU/SCFToGPU.h"
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#include "mlir/Dialect/Affine/IR/AffineOps.h"
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#include "mlir/Dialect/Arithmetic/IR/Arithmetic.h"
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#include "mlir/Dialect/Complex/IR/Complex.h"
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#include "mlir/Dialect/GPU/IR/GPUDialect.h"
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#include "mlir/Dialect/SCF/IR/SCF.h"
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#include "mlir/Pass/Pass.h"
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#include "mlir/Transforms/DialectConversion.h"
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#include "llvm/ADT/ArrayRef.h"
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#include "llvm/Support/CommandLine.h"
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namespace mlir {
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#define GEN_PASS_DEF_CONVERTAFFINEFORTOGPU
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#define GEN_PASS_DEF_CONVERTPARALLELLOOPTOGPU
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#include "mlir/Conversion/Passes.h.inc"
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} // namespace mlir
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using namespace mlir;
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using namespace mlir::scf;
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namespace {
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// A pass that traverses top-level loops in the function and converts them to
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// GPU launch operations. Nested launches are not allowed, so this does not
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// walk the function recursively to avoid considering nested loops.
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struct ForLoopMapper : public impl::ConvertAffineForToGPUBase<ForLoopMapper> {
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ForLoopMapper() = default;
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ForLoopMapper(unsigned numBlockDims, unsigned numThreadDims) {
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this->numBlockDims = numBlockDims;
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this->numThreadDims = numThreadDims;
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}
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void runOnOperation() override {
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for (Operation &op :
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llvm::make_early_inc_range(getOperation().getBody().getOps())) {
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if (auto forOp = dyn_cast<AffineForOp>(&op)) {
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if (failed(convertAffineLoopNestToGPULaunch(forOp, numBlockDims,
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numThreadDims)))
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signalPassFailure();
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}
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}
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}
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};
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struct ParallelLoopToGpuPass
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: public impl::ConvertParallelLoopToGpuBase<ParallelLoopToGpuPass> {
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void runOnOperation() override {
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RewritePatternSet patterns(&getContext());
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populateParallelLoopToGPUPatterns(patterns);
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ConversionTarget target(getContext());
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target.markUnknownOpDynamicallyLegal([](Operation *) { return true; });
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configureParallelLoopToGPULegality(target);
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if (failed(applyPartialConversion(getOperation(), target,
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std::move(patterns))))
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signalPassFailure();
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finalizeParallelLoopToGPUConversion(getOperation());
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}
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};
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} // namespace
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std::unique_ptr<InterfacePass<FunctionOpInterface>>
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mlir::createAffineForToGPUPass(unsigned numBlockDims, unsigned numThreadDims) {
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return std::make_unique<ForLoopMapper>(numBlockDims, numThreadDims);
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}
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std::unique_ptr<InterfacePass<FunctionOpInterface>>
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mlir::createAffineForToGPUPass() {
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return std::make_unique<ForLoopMapper>();
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}
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std::unique_ptr<Pass> mlir::createParallelLoopToGpuPass() {
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return std::make_unique<ParallelLoopToGpuPass>();
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}
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