diff options
Diffstat (limited to 'mlir/tools/mlir-cuda-runner/cuda-runtime-wrappers.cpp')
-rw-r--r-- | mlir/tools/mlir-cuda-runner/cuda-runtime-wrappers.cpp | 106 |
1 files changed, 106 insertions, 0 deletions
diff --git a/mlir/tools/mlir-cuda-runner/cuda-runtime-wrappers.cpp b/mlir/tools/mlir-cuda-runner/cuda-runtime-wrappers.cpp new file mode 100644 index 00000000000..9f1591b5a8c --- /dev/null +++ b/mlir/tools/mlir-cuda-runner/cuda-runtime-wrappers.cpp @@ -0,0 +1,106 @@ +//===- cuda-runtime-wrappers.cpp - MLIR CUDA runner wrapper library -------===// +// +// 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 +// +//===----------------------------------------------------------------------===// +// +// 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 "llvm/Support/raw_ostream.h" + +#include "cuda.h" + +namespace { +int32_t reportErrorIfAny(CUresult result, const char *where) { + if (result != CUDA_SUCCESS) { + llvm::errs() << "CUDA failed with " << result << " in " << where << "\n"; + } + return result; +} +} // anonymous namespace + +extern "C" int32_t mcuModuleLoad(void **module, void *data) { + int32_t err = reportErrorIfAny( + cuModuleLoadData(reinterpret_cast<CUmodule *>(module), data), + "ModuleLoad"); + return err; +} + +extern "C" int32_t mcuModuleGetFunction(void **function, void *module, + const char *name) { + return reportErrorIfAny( + cuModuleGetFunction(reinterpret_cast<CUfunction *>(function), + reinterpret_cast<CUmodule>(module), name), + "GetFunction"); +} + +// 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" int32_t mcuLaunchKernel(void *function, intptr_t gridX, + intptr_t gridY, intptr_t gridZ, + intptr_t blockX, intptr_t blockY, + intptr_t blockZ, int32_t smem, void *stream, + void **params, void **extra) { + return reportErrorIfAny( + cuLaunchKernel(reinterpret_cast<CUfunction>(function), gridX, gridY, + gridZ, blockX, blockY, blockZ, smem, + reinterpret_cast<CUstream>(stream), params, extra), + "LaunchKernel"); +} + +extern "C" void *mcuGetStreamHelper() { + CUstream stream; + reportErrorIfAny(cuStreamCreate(&stream, CU_STREAM_DEFAULT), "StreamCreate"); + return stream; +} + +extern "C" int32_t mcuStreamSynchronize(void *stream) { + return reportErrorIfAny( + cuStreamSynchronize(reinterpret_cast<CUstream>(stream)), "StreamSync"); +} + +/// 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 mcuMemHostRegister(void *ptr, uint64_t sizeBytes) { + reportErrorIfAny(cuMemHostRegister(ptr, sizeBytes, /*flags=*/0), + "MemHostRegister"); +} + +// A struct that corresponds to how MLIR represents memrefs. +template <typename T, int N> struct MemRefType { + T *basePtr; + T *data; + int64_t offset; + int64_t sizes[N]; + int64_t strides[N]; +}; + +// Allows to register a MemRef with the CUDA runtime. Initializes array with +// value. Helpful until we have transfer functions implemented. +template <typename T, int N> +void mcuMemHostRegisterMemRef(const MemRefType<T, N> *arg, T value) { + auto count = std::accumulate(arg->sizes, arg->sizes + N, 1, + std::multiplies<int64_t>()); + std::fill_n(arg->data, count, value); + mcuMemHostRegister(arg->data, count * sizeof(T)); +} +extern "C" void +mcuMemHostRegisterMemRef1dFloat(const MemRefType<float, 1> *arg) { + mcuMemHostRegisterMemRef(arg, 1.23f); +} +extern "C" void +mcuMemHostRegisterMemRef3dFloat(const MemRefType<float, 3> *arg) { + mcuMemHostRegisterMemRef(arg, 1.23f); +} |