cuda-runtime-wrappers.cpp
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//===- cuda-runtime-wrappers.cpp - MLIR CUDA runner wrapper library -------===//
//
// 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
//
//===----------------------------------------------------------------------===//
//
// Implements C wrappers around the CUDA library for easy linking in ORC jit.
// Also adds some debugging helpers that are helpful when writing MLIR code to
// run on GPUs.
//
//===----------------------------------------------------------------------===//
#include <cassert>
#include <numeric>
#include "mlir/ExecutionEngine/CRunnerUtils.h"
#include "llvm/ADT/ArrayRef.h"
#include "llvm/Support/raw_ostream.h"
#include "cuda.h"
#define CUDA_REPORT_IF_ERROR(expr) \
[](CUresult result) { \
if (!result) \
return; \
const char *name = nullptr; \
cuGetErrorName(result, &name); \
if (!name) \
name = "<unknown>"; \
llvm::errs() << "'" << #expr << "' failed with '" << name << "'\n"; \
}(expr)
extern "C" CUmodule mgpuModuleLoad(void *data) {
CUmodule module = nullptr;
CUDA_REPORT_IF_ERROR(cuModuleLoadData(&module, data));
return module;
}
extern "C" CUfunction mgpuModuleGetFunction(CUmodule module, const char *name) {
CUfunction function = nullptr;
CUDA_REPORT_IF_ERROR(cuModuleGetFunction(&function, module, name));
return function;
}
// The wrapper uses intptr_t instead of CUDA's unsigned int to match
// the type of MLIR's index type. This avoids the need for casts in the
// generated MLIR code.
extern "C" void mgpuLaunchKernel(CUfunction function, intptr_t gridX,
intptr_t gridY, intptr_t gridZ,
intptr_t blockX, intptr_t blockY,
intptr_t blockZ, int32_t smem, CUstream stream,
void **params, void **extra) {
CUDA_REPORT_IF_ERROR(cuLaunchKernel(function, gridX, gridY, gridZ, blockX,
blockY, blockZ, smem, stream, params,
extra));
}
extern "C" CUstream mgpuStreamCreate() {
CUstream stream = nullptr;
CUDA_REPORT_IF_ERROR(cuStreamCreate(&stream, CU_STREAM_NON_BLOCKING));
return stream;
}
extern "C" void mgpuStreamSynchronize(CUstream stream) {
CUDA_REPORT_IF_ERROR(cuStreamSynchronize(stream));
}
/// Helper functions for writing mlir example code
// Allows to register byte array with the CUDA runtime. Helpful until we have
// transfer functions implemented.
extern "C" void mgpuMemHostRegister(void *ptr, uint64_t sizeBytes) {
CUDA_REPORT_IF_ERROR(cuMemHostRegister(ptr, sizeBytes, /*flags=*/0));
}
// Allows to register a MemRef with the CUDA runtime. Helpful until we have
// transfer functions implemented.
extern "C" void
mgpuMemHostRegisterMemRef(int64_t rank, StridedMemRefType<char, 1> *descriptor,
int64_t elementSizeBytes) {
llvm::SmallVector<int64_t, 4> denseStrides(rank);
llvm::ArrayRef<int64_t> sizes(descriptor->sizes, rank);
llvm::ArrayRef<int64_t> strides(sizes.end(), rank);
std::partial_sum(sizes.rbegin(), sizes.rend(), denseStrides.rbegin(),
std::multiplies<int64_t>());
auto sizeBytes = denseStrides.front() * elementSizeBytes;
// Only densely packed tensors are currently supported.
std::rotate(denseStrides.begin(), denseStrides.begin() + 1,
denseStrides.end());
denseStrides.back() = 1;
assert(strides == llvm::makeArrayRef(denseStrides));
auto ptr = descriptor->data + descriptor->offset * elementSizeBytes;
mgpuMemHostRegister(ptr, sizeBytes);
}