3ba66435d9
StandardToSPIRV currently contains an assortment of patterns converting from different dialects to SPIRV. This commit splits up StandardToSPIRV into separate conversions for each of the dialects involved (some of which already exist). Differential Revision: https://reviews.llvm.org/D120767
78 lines
3.0 KiB
C++
78 lines
3.0 KiB
C++
//===- GPUToSPIRVPass.cpp - GPU to SPIR-V Passes --------------------------===//
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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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//
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// This file implements a pass to convert a kernel function in the GPU Dialect
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// into a spv.module operation.
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//
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//===----------------------------------------------------------------------===//
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#include "mlir/Conversion/GPUToSPIRV/GPUToSPIRVPass.h"
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#include "../PassDetail.h"
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#include "mlir/Conversion/ArithmeticToSPIRV/ArithmeticToSPIRV.h"
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#include "mlir/Conversion/FuncToSPIRV/FuncToSPIRV.h"
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#include "mlir/Conversion/GPUToSPIRV/GPUToSPIRV.h"
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#include "mlir/Conversion/MemRefToSPIRV/MemRefToSPIRV.h"
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#include "mlir/Dialect/GPU/GPUDialect.h"
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#include "mlir/Dialect/SPIRV/IR/SPIRVDialect.h"
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#include "mlir/Dialect/SPIRV/IR/SPIRVOps.h"
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#include "mlir/Dialect/SPIRV/Transforms/SPIRVConversion.h"
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using namespace mlir;
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namespace {
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/// Pass to lower GPU Dialect to SPIR-V. The pass only converts the gpu.func ops
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/// inside gpu.module ops. i.e., the function that are referenced in
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/// gpu.launch_func ops. For each such function
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///
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/// 1) Create a spirv::ModuleOp, and clone the function into spirv::ModuleOp
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/// (the original function is still needed by the gpu::LaunchKernelOp, so cannot
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/// replace it).
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///
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/// 2) Lower the body of the spirv::ModuleOp.
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struct GPUToSPIRVPass : public ConvertGPUToSPIRVBase<GPUToSPIRVPass> {
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void runOnOperation() override;
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};
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} // namespace
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void GPUToSPIRVPass::runOnOperation() {
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MLIRContext *context = &getContext();
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ModuleOp module = getOperation();
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SmallVector<Operation *, 1> kernelModules;
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OpBuilder builder(context);
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module.walk([&builder, &kernelModules](gpu::GPUModuleOp moduleOp) {
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// For each kernel module (should be only 1 for now, but that is not a
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// requirement here), clone the module for conversion because the
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// gpu.launch function still needs the kernel module.
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builder.setInsertionPoint(moduleOp.getOperation());
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kernelModules.push_back(builder.clone(*moduleOp.getOperation()));
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});
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auto targetAttr = spirv::lookupTargetEnvOrDefault(module);
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std::unique_ptr<ConversionTarget> target =
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SPIRVConversionTarget::get(targetAttr);
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SPIRVTypeConverter typeConverter(targetAttr);
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RewritePatternSet patterns(context);
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populateGPUToSPIRVPatterns(typeConverter, patterns);
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// TODO: Change SPIR-V conversion to be progressive and remove the following
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// patterns.
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mlir::arith::populateArithmeticToSPIRVPatterns(typeConverter, patterns);
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populateMemRefToSPIRVPatterns(typeConverter, patterns);
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populateFuncToSPIRVPatterns(typeConverter, patterns);
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if (failed(applyFullConversion(kernelModules, *target, std::move(patterns))))
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return signalPassFailure();
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}
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std::unique_ptr<OperationPass<ModuleOp>> mlir::createConvertGPUToSPIRVPass() {
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return std::make_unique<GPUToSPIRVPass>();
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}
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