0670f855a7
This allow lowering to support scf.for and scf.if with results. As right now spv region operations don't have return value the results are demoted to Function memory. We create one allocation per result right before the region and store the yield values in it. Then we can load back the value from allocation to be able to use the results. Differential Revision: https://reviews.llvm.org/D82246
74 lines
2.9 KiB
C++
74 lines
2.9 KiB
C++
//===- ConvertGPUToSPIRVPass.cpp - GPU to SPIR-V dialect lowering 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/ConvertGPUToSPIRVPass.h"
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#include "../PassDetail.h"
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#include "mlir/Conversion/GPUToSPIRV/ConvertGPUToSPIRV.h"
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#include "mlir/Conversion/SCFToSPIRV/SCFToSPIRV.h"
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#include "mlir/Conversion/StandardToSPIRV/ConvertStandardToSPIRV.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/Dialect/SPIRV/SPIRVDialect.h"
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#include "mlir/Dialect/SPIRV/SPIRVLowering.h"
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#include "mlir/Dialect/SPIRV/SPIRVOps.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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spirv::SPIRVConversionTarget::get(targetAttr);
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SPIRVTypeConverter typeConverter(targetAttr);
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ScfToSPIRVContext scfContext;
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OwningRewritePatternList patterns;
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populateGPUToSPIRVPatterns(context, typeConverter, patterns);
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populateSCFToSPIRVPatterns(context, typeConverter,scfContext, patterns);
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populateStandardToSPIRVPatterns(context, typeConverter, patterns);
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if (failed(applyFullConversion(kernelModules, *target, 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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