mlir-cuda-runner.cpp
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//===- mlir-cpu-runner.cpp - MLIR CPU Execution Driver---------------------===//
//
// Part of the MLIR 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 is a command line utility that executes an MLIR file on the GPU by
// translating MLIR to NVVM/LVVM IR before JIT-compiling and executing the
// latter.
//
//===----------------------------------------------------------------------===//
#include "llvm/ADT/STLExtras.h"
#include "mlir/Conversion/GPUToCUDA/GPUToCUDAPass.h"
#include "mlir/Conversion/GPUToNVVM/GPUToNVVMPass.h"
#include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVM.h"
#include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVMPass.h"
#include "mlir/Dialect/GPU/GPUDialect.h"
#include "mlir/Dialect/GPU/Passes.h"
#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
#include "mlir/Dialect/LLVMIR/NVVMDialect.h"
#include "mlir/IR/Function.h"
#include "mlir/IR/Module.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Pass/PassManager.h"
#include "mlir/Support/JitRunner.h"
#include "mlir/Transforms/DialectConversion.h"
#include "cuda.h"
using namespace mlir;
inline void emit_cuda_error(const llvm::Twine &message, const char *buffer,
CUresult error, Location loc) {
emitError(loc, message.concat(" failed with error code ")
.concat(llvm::Twine{error})
.concat("[")
.concat(buffer)
.concat("]"));
}
#define RETURN_ON_CUDA_ERROR(expr, msg) \
{ \
auto _cuda_error = (expr); \
if (_cuda_error != CUDA_SUCCESS) { \
emit_cuda_error(msg, jitErrorBuffer, _cuda_error, loc); \
return {}; \
} \
}
OwnedCubin compilePtxToCubin(const std::string ptx, Location loc,
StringRef name) {
char jitErrorBuffer[4096] = {0};
RETURN_ON_CUDA_ERROR(cuInit(0), "cuInit");
// Linking requires a device context.
CUdevice device;
RETURN_ON_CUDA_ERROR(cuDeviceGet(&device, 0), "cuDeviceGet");
CUcontext context;
RETURN_ON_CUDA_ERROR(cuCtxCreate(&context, 0, device), "cuCtxCreate");
CUlinkState linkState;
CUjit_option jitOptions[] = {CU_JIT_ERROR_LOG_BUFFER,
CU_JIT_ERROR_LOG_BUFFER_SIZE_BYTES};
void *jitOptionsVals[] = {jitErrorBuffer,
reinterpret_cast<void *>(sizeof(jitErrorBuffer))};
RETURN_ON_CUDA_ERROR(cuLinkCreate(2, /* number of jit options */
jitOptions, /* jit options */
jitOptionsVals, /* jit option values */
&linkState),
"cuLinkCreate");
RETURN_ON_CUDA_ERROR(
cuLinkAddData(linkState, CUjitInputType::CU_JIT_INPUT_PTX,
const_cast<void *>(static_cast<const void *>(ptx.c_str())),
ptx.length(), name.data(), /* kernel name */
0, /* number of jit options */
nullptr, /* jit options */
nullptr /* jit option values */
),
"cuLinkAddData");
void *cubinData;
size_t cubinSize;
RETURN_ON_CUDA_ERROR(cuLinkComplete(linkState, &cubinData, &cubinSize),
"cuLinkComplete");
char *cubinAsChar = static_cast<char *>(cubinData);
OwnedCubin result =
std::make_unique<std::vector<char>>(cubinAsChar, cubinAsChar + cubinSize);
// This will also destroy the cubin data.
RETURN_ON_CUDA_ERROR(cuLinkDestroy(linkState), "cuLinkDestroy");
return result;
}
static LogicalResult runMLIRPasses(ModuleOp m) {
PassManager pm(m.getContext());
applyPassManagerCLOptions(pm);
pm.addPass(createGpuKernelOutliningPass());
auto &kernelPm = pm.nest<ModuleOp>();
kernelPm.addPass(createLowerGpuOpsToNVVMOpsPass());
kernelPm.addPass(createConvertGPUKernelToCubinPass(&compilePtxToCubin));
pm.addPass(createLowerToLLVMPass());
pm.addPass(createConvertGpuLaunchFuncToCudaCallsPass());
return pm.run(m);
}
int main(int argc, char **argv) {
registerPassManagerCLOptions();
return mlir::JitRunnerMain(argc, argv, &runMLIRPasses);
}