Expose AffineToGPUPass for use with PassManager

Originally, AffineToGPUPass was created and registered in the source file
mainly for testing purposes.  Provide a factory function that constructs
AffineToGPU pass to make it usable in pass pipelines.

PiperOrigin-RevId: 255902831
This commit is contained in:
Alex Zinenko 2019-07-01 00:47:58 -07:00 committed by jpienaar
parent 8c47e2ed5c
commit d046b2ddec
2 changed files with 56 additions and 4 deletions

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@ -0,0 +1,35 @@
//===- AffineToGPUPass.h - Pass converting loops to GPU kernels -*- C++ -*-===//
//
// Copyright 2019 The MLIR Authors.
//
// 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
//
// http://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.
// =============================================================================
#ifndef MLIR_CONVERSION_AFFINETOGPU_AFFINETOGPUPASS_H_
#define MLIR_CONVERSION_AFFINETOGPU_AFFINETOGPUPASS_H_
namespace mlir {
class FunctionPassBase;
/// Create a pass that converts loop nests into GPU kernels. It considers
/// top-level affine.for operations as roots of loop nests and converts them
/// to the gpu.launch operations if possible.
///
/// No check on the size of the block or grid, or on the validity of
/// parallelization is performed, it is under the responsibility of the caller
/// to strip-mine the loops and to perform the dependence analysis before
/// calling the conversion.
FunctionPassBase *createSimpleAffineToGPUPass(unsigned numBlockDims,
unsigned numThreadDims);
} // namespace mlir
#endif // MLIR_CONVERSION_AFFINETOGPU_AFFINETOGPUPASS_H_

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@ -15,6 +15,7 @@
// limitations under the License.
// =============================================================================
#include "mlir/Conversion/AffineToGPU/AffineToGPUPass.h"
#include "mlir/AffineOps/AffineOps.h"
#include "mlir/Conversion/AffineToGPU/AffineToGPU.h"
#include "mlir/Pass/Pass.h"
@ -40,17 +41,33 @@ namespace {
// GPU launch operations. Nested launches are not allowed, so this does not
// walk the function recursively to avoid considering nested loops.
struct AffineForGPUMapper : public FunctionPass<AffineForGPUMapper> {
AffineForGPUMapper(unsigned numBlockDims, unsigned numThreadDims)
: numBlockDims(numBlockDims), numThreadDims(numThreadDims) {}
void runOnFunction() override {
for (Block &block : getFunction())
for (Operation &op : llvm::make_early_inc_range(block))
if (auto forOp = dyn_cast<AffineForOp>(&op))
if (failed(convertAffineLoopNestToGPULaunch(
forOp, clNumBlockDims.getValue(),
clNumThreadDims.getValue())))
if (failed(convertAffineLoopNestToGPULaunch(forOp, numBlockDims,
numThreadDims)))
signalPassFailure();
}
unsigned numBlockDims;
unsigned numThreadDims;
};
struct AffineForGPUMapperCLI : public AffineForGPUMapper {
AffineForGPUMapperCLI()
: AffineForGPUMapper(clNumBlockDims.getValue(),
clNumThreadDims.getValue()) {}
};
} // namespace
static PassRegistration<AffineForGPUMapper>
FunctionPassBase *mlir::createSimpleAffineToGPUPass(unsigned numBlockDims,
unsigned numThreadDims) {
return new AffineForGPUMapper(numBlockDims, numThreadDims);
}
static PassRegistration<AffineForGPUMapperCLI>
registration(PASS_NAME, "Convert top-level affine loops to GPU kernels");