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//===- GPUToSPIRVPass.cpp - GPU to SPIR-V Passes --------------------------===//
//
// 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
//
//===----------------------------------------------------------------------===//
//
// This file implements a pass to convert a kernel function in the GPU Dialect
// into a spv.module operation.
//
//===----------------------------------------------------------------------===//
#include "mlir/Conversion/GPUToSPIRV/GPUToSPIRVPass.h"
#include "mlir/Conversion/ArithmeticToSPIRV/ArithmeticToSPIRV.h"
#include "mlir/Conversion/FuncToSPIRV/FuncToSPIRV.h"
#include "mlir/Conversion/GPUToSPIRV/GPUToSPIRV.h"
#include "mlir/Conversion/MemRefToSPIRV/MemRefToSPIRV.h"
#include "mlir/Dialect/GPU/IR/GPUDialect.h"
#include "mlir/Dialect/SPIRV/IR/SPIRVDialect.h"
#include "mlir/Dialect/SPIRV/IR/SPIRVOps.h"
#include "mlir/Dialect/SPIRV/Transforms/SPIRVConversion.h"
namespace mlir {
#define GEN_PASS_DEF_CONVERTGPUTOSPIRV
#include "mlir/Conversion/Passes.h.inc"
} // namespace mlir
using namespace mlir;
namespace {
/// Pass to lower GPU Dialect to SPIR-V. The pass only converts the gpu.func ops
/// inside gpu.module ops. i.e., the function that are referenced in
/// gpu.launch_func ops. For each such function
///
/// 1) Create a spirv::ModuleOp, and clone the function into spirv::ModuleOp
/// (the original function is still needed by the gpu::LaunchKernelOp, so cannot
/// replace it).
///
/// 2) Lower the body of the spirv::ModuleOp.
class GPUToSPIRVPass : public impl::ConvertGPUToSPIRVBase<GPUToSPIRVPass> {
public:
explicit GPUToSPIRVPass(bool mapMemorySpace)
: mapMemorySpace(mapMemorySpace) {}
void runOnOperation() override;
private:
bool mapMemorySpace;
};
} // namespace
void GPUToSPIRVPass::runOnOperation() {
MLIRContext *context = &getContext();
ModuleOp module = getOperation();
SmallVector<Operation *, 1> gpuModules;
OpBuilder builder(context);
module.walk([&](gpu::GPUModuleOp moduleOp) {
// Clone each GPU kernel module for conversion, given that the GPU
// launch op still needs the original GPU kernel module.
builder.setInsertionPoint(moduleOp.getOperation());
gpuModules.push_back(builder.clone(*moduleOp.getOperation()));
});
// Map MemRef memory space to SPIR-V storage class first if requested.
if (mapMemorySpace) {
std::unique_ptr<ConversionTarget> target =
spirv::getMemorySpaceToStorageClassTarget(*context);
spirv::MemorySpaceToStorageClassMap memorySpaceMap =
spirv::mapMemorySpaceToVulkanStorageClass;
spirv::MemorySpaceToStorageClassConverter converter(memorySpaceMap);
RewritePatternSet patterns(context);
spirv::populateMemorySpaceToStorageClassPatterns(converter, patterns);
if (failed(applyFullConversion(gpuModules, *target, std::move(patterns))))
return signalPassFailure();
}
auto targetAttr = spirv::lookupTargetEnvOrDefault(module);
std::unique_ptr<ConversionTarget> target =
SPIRVConversionTarget::get(targetAttr);
SPIRVTypeConverter typeConverter(targetAttr);
RewritePatternSet patterns(context);
populateGPUToSPIRVPatterns(typeConverter, patterns);
// TODO: Change SPIR-V conversion to be progressive and remove the following
// patterns.
mlir::arith::populateArithmeticToSPIRVPatterns(typeConverter, patterns);
populateMemRefToSPIRVPatterns(typeConverter, patterns);
populateFuncToSPIRVPatterns(typeConverter, patterns);
if (failed(applyFullConversion(gpuModules, *target, std::move(patterns))))
return signalPassFailure();
}
std::unique_ptr<OperationPass<ModuleOp>>
mlir::createConvertGPUToSPIRVPass(bool mapMemorySpace) {
return std::make_unique<GPUToSPIRVPass>(mapMemorySpace);
}
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