47f175b09b
These passes generally don't rely on any special aspects of FuncOp, and moving allows for these passes to be used in many more situations. The passes that obviously weren't relying on invariants guaranteed by a "function" were updated to be generic pass, the rest were updated to be FunctionOpinterface InterfacePasses. The test updates are NFC switching from implicit nesting (-pass -pass2) form to the -pass-pipeline form (generic passes do not implicitly nest as op-specific passes do). Differential Revision: https://reviews.llvm.org/D121190
77 lines
2.8 KiB
C++
77 lines
2.8 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 "../PassDetail.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/GPUDialect.h"
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#include "mlir/Dialect/SCF/SCF.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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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 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 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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