72c65b698e
TestDialect has many operations and they all live in ::mlir namespace. Sometimes it is not clear whether the ops used in the code for the test passes belong to Standard or to Test dialects. Also, with this change it is easier to understand what test passes registered in mlir-opt are actually passes in mlir/test. Differential Revision: https://reviews.llvm.org/D90794
45 lines
1.5 KiB
C++
45 lines
1.5 KiB
C++
//===- TestConvertGPUKernelToCubin.cpp - Test gpu kernel cubin lowering ---===//
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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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#include "mlir/Conversion/GPUCommon/GPUCommonPass.h"
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#include "mlir/Pass/Pass.h"
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#include "mlir/Pass/PassManager.h"
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#include "mlir/Target/NVVMIR.h"
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#include "llvm/Support/TargetSelect.h"
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using namespace mlir;
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#if MLIR_CUDA_CONVERSIONS_ENABLED
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static OwnedBlob compilePtxToCubinForTesting(const std::string &, Location,
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StringRef) {
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const char data[] = "CUBIN";
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return std::make_unique<std::vector<char>>(data, data + sizeof(data) - 1);
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}
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namespace mlir {
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namespace test {
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void registerTestConvertGPUKernelToCubinPass() {
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PassPipelineRegistration<>(
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"test-kernel-to-cubin",
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"Convert all kernel functions to CUDA cubin blobs",
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[](OpPassManager &pm) {
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// Initialize LLVM NVPTX backend.
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LLVMInitializeNVPTXTarget();
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LLVMInitializeNVPTXTargetInfo();
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LLVMInitializeNVPTXTargetMC();
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LLVMInitializeNVPTXAsmPrinter();
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pm.addPass(createConvertGPUKernelToBlobPass(
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translateModuleToNVVMIR, compilePtxToCubinForTesting,
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"nvptx64-nvidia-cuda", "sm_35", "+ptx60", "nvvm.cubin"));
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});
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}
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} // namespace test
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} // namespace mlir
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#endif
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