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path: root/mlir/lib/Conversion/SCFToGPU/SCFToGPUPass.cpp
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//===- SCFToGPUPass.cpp - Convert a loop nest to a GPU kernel -----------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//

#include "mlir/Conversion/SCFToGPU/SCFToGPUPass.h"

#include "mlir/Conversion/SCFToGPU/SCFToGPU.h"
#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/GPU/IR/GPUDialect.h"
#include "mlir/Transforms/DialectConversion.h"

namespace mlir {
#define GEN_PASS_DEF_CONVERTAFFINEFORTOGPUPASS
#define GEN_PASS_DEF_CONVERTPARALLELLOOPTOGPUPASS
#include "mlir/Conversion/Passes.h.inc"
} // namespace mlir

using namespace mlir;
using namespace mlir::scf;

namespace {
// A pass that traverses top-level loops in the function and converts them to
// GPU launch operations.  Nested launches are not allowed, so this does not
// walk the function recursively to avoid considering nested loops.
struct ForLoopMapper
    : public impl::ConvertAffineForToGPUPassBase<ForLoopMapper> {
  using Base::Base;

  void runOnOperation() override {
    for (Operation &op : llvm::make_early_inc_range(
             getOperation().getFunctionBody().getOps())) {
      if (auto forOp = dyn_cast<affine::AffineForOp>(&op)) {
        if (failed(convertAffineLoopNestToGPULaunch(forOp, numBlockDims,
                                                    numThreadDims)))
          signalPassFailure();
      }
    }
  }
};

struct ParallelLoopToGpuPass
    : public impl::ConvertParallelLoopToGpuPassBase<ParallelLoopToGpuPass> {
  void runOnOperation() override {
    RewritePatternSet patterns(&getContext());
    populateParallelLoopToGPUPatterns(patterns);
    ConversionTarget target(getContext());
    target.markUnknownOpDynamicallyLegal([](Operation *) { return true; });
    configureParallelLoopToGPULegality(target);
    if (failed(applyPartialConversion(getOperation(), target,
                                      std::move(patterns))))
      signalPassFailure();
    finalizeParallelLoopToGPUConversion(getOperation());
  }
};

} // namespace