Files
llvm-project/mlir/lib/ExecutionEngine/RocmRuntimeWrappers.cpp
Jared Hoberock 4d33c692e9 [MLIR][GPU] Add cooperative launch support to gpu.launch_func (#190639)
Add a `cooperative` UnitAttr to `gpu.launch_func` that enables
cooperative kernel launch semantics. Cooperative launches guarantee that
all thread blocks in the grid are co-resident on the GPU simultaneously,
enabling grid-wide synchronization patterns.

## Implementation

When `cooperative` is set (with or without cluster sizes), the lowering
emits a call to the new `mgpuLaunchKernelCooperative` runtime function,
which uses `cuLaunchKernelEx` with a `CUlaunchConfig` and
`CU_LAUNCH_ATTRIBUTE_COOPERATIVE`. This API is guarded behind
`CUDA_VERSION >= 12000`. The HIP path funnels through
`hipModuleLaunchCooperativeKernel`.

## Changes

- **GPUOps.td**: add `cooperative` UnitAttr and assembly format keyword
- **SelectObjectAttr.cpp**: add `getKernelLaunchExFn()`, route
cooperative and/or cluster launches through `mgpuLaunchKernelEx`
- **CudaRuntimeWrappers.cpp**: implement `mgpuLaunchKernelCooperative`
via `cuLaunchKernelEx` or `hipModuleLaunchCooperativeKernel`, depending
on platform
- **GPUToLLVMConversion.cpp**: propagate cooperative attribute through
the legalization pattern
- **test/Dialect/GPU/ops.mlir**: round-trip tests for cooperative
keyword with and without clusters

## Context

MLIR currently has no support for cooperative kernel launches. Flang
works around this with a CUF-specific attribute (PRs #124325, #124362),
but there is no first-class support in the GPU dialect. This patch adds
it at the `gpu.launch_func` level so all frontends can use it.

Assisted-by: Claude (Anthropic)
2026-04-29 11:33:22 +02:00

232 lines
8.8 KiB
C++

//===- RocmRuntimeWrappers.cpp - MLIR ROCM runtime 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 ROCM 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 "hip/hip_runtime.h"
#define HIP_REPORT_IF_ERROR(expr) \
[](hipError_t result) { \
if (!result) \
return; \
const char *name = hipGetErrorName(result); \
if (!name) \
name = "<unknown>"; \
fprintf(stderr, "'%s' failed with '%s'\n", #expr, name); \
}(expr)
thread_local static int32_t defaultDevice = 0;
extern "C" hipModule_t mgpuModuleLoad(void *data, size_t /*gpuBlobSize*/) {
hipModule_t module = nullptr;
HIP_REPORT_IF_ERROR(hipModuleLoadData(&module, data));
return module;
}
extern "C" hipModule_t mgpuModuleLoadJIT(void *data, int optLevel,
size_t /*assmeblySize*/) {
assert(false && "This function is not available in HIP.");
return nullptr;
}
extern "C" void mgpuModuleUnload(hipModule_t module) {
HIP_REPORT_IF_ERROR(hipModuleUnload(module));
}
extern "C" hipFunction_t mgpuModuleGetFunction(hipModule_t module,
const char *name) {
hipFunction_t function = nullptr;
HIP_REPORT_IF_ERROR(hipModuleGetFunction(&function, module, name));
return function;
}
// The wrapper uses intptr_t instead of ROCM'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(hipFunction_t function, intptr_t gridX,
intptr_t gridY, intptr_t gridZ,
intptr_t blockX, intptr_t blockY,
intptr_t blockZ, int32_t smem,
hipStream_t stream, void **params,
void **extra, size_t /*paramsCount*/) {
HIP_REPORT_IF_ERROR(hipModuleLaunchKernel(function, gridX, gridY, gridZ,
blockX, blockY, blockZ, smem,
stream, params, extra));
}
// Cooperative launch entry point. The cluster dimensions are accepted to
// match the CUDA wrapper signature, but HIP does not support thread block
// clusters; passing nonzero cluster dimensions is a usage error.
extern "C" void mgpuLaunchKernelCooperative(
hipFunction_t function, intptr_t gridX, intptr_t gridY, intptr_t gridZ,
intptr_t clusterX, intptr_t clusterY, intptr_t clusterZ, intptr_t blockX,
intptr_t blockY, intptr_t blockZ, int32_t smem, hipStream_t stream,
void **params, void ** /*extra*/) {
if (clusterX != 0 || clusterY != 0 || clusterZ != 0) {
fprintf(stderr,
"mgpuLaunchKernelCooperative: HIP does not support thread block "
"clusters (got cluster=%ld,%ld,%ld)\n",
clusterX, clusterY, clusterZ);
abort();
}
HIP_REPORT_IF_ERROR(
hipModuleLaunchCooperativeKernel(function, gridX, gridY, gridZ, blockX,
blockY, blockZ, smem, stream, params));
}
extern "C" hipStream_t mgpuStreamCreate() {
hipStream_t stream = nullptr;
HIP_REPORT_IF_ERROR(hipStreamCreate(&stream));
return stream;
}
extern "C" void mgpuStreamDestroy(hipStream_t stream) {
HIP_REPORT_IF_ERROR(hipStreamDestroy(stream));
}
extern "C" void mgpuStreamSynchronize(hipStream_t stream) {
return HIP_REPORT_IF_ERROR(hipStreamSynchronize(stream));
}
extern "C" void mgpuStreamWaitEvent(hipStream_t stream, hipEvent_t event) {
HIP_REPORT_IF_ERROR(hipStreamWaitEvent(stream, event, /*flags=*/0));
}
extern "C" hipEvent_t mgpuEventCreate() {
hipEvent_t event = nullptr;
HIP_REPORT_IF_ERROR(hipEventCreateWithFlags(&event, hipEventDisableTiming));
return event;
}
extern "C" void mgpuEventDestroy(hipEvent_t event) {
HIP_REPORT_IF_ERROR(hipEventDestroy(event));
}
extern "C" void mgpuEventSynchronize(hipEvent_t event) {
HIP_REPORT_IF_ERROR(hipEventSynchronize(event));
}
extern "C" void mgpuEventRecord(hipEvent_t event, hipStream_t stream) {
HIP_REPORT_IF_ERROR(hipEventRecord(event, stream));
}
extern "C" void *mgpuMemAlloc(uint64_t sizeBytes, hipStream_t /*stream*/,
bool /*isHostShared*/) {
void *ptr;
HIP_REPORT_IF_ERROR(hipMalloc(&ptr, sizeBytes));
return ptr;
}
extern "C" void mgpuMemFree(void *ptr, hipStream_t /*stream*/) {
HIP_REPORT_IF_ERROR(hipFree(ptr));
}
extern "C" void mgpuMemcpy(void *dst, void *src, size_t sizeBytes,
hipStream_t stream) {
HIP_REPORT_IF_ERROR(
hipMemcpyAsync(dst, src, sizeBytes, hipMemcpyDefault, stream));
}
extern "C" void mgpuMemset32(void *dst, int value, size_t count,
hipStream_t stream) {
HIP_REPORT_IF_ERROR(hipMemsetD32Async(reinterpret_cast<hipDeviceptr_t>(dst),
value, count, stream));
}
extern "C" void mgpuMemset16(void *dst, int short value, size_t count,
hipStream_t stream) {
HIP_REPORT_IF_ERROR(hipMemsetD16Async(reinterpret_cast<hipDeviceptr_t>(dst),
value, count, stream));
}
/// Helper functions for writing mlir example code
// Allows to register byte array with the ROCM runtime. Helpful until we have
// transfer functions implemented.
extern "C" void mgpuMemHostRegister(void *ptr, uint64_t sizeBytes) {
HIP_REPORT_IF_ERROR(hipHostRegister(ptr, sizeBytes, /*flags=*/0));
}
// Allows to register a MemRef with the ROCm 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::ArrayRef(denseStrides));
auto ptr = descriptor->data + descriptor->offset * elementSizeBytes;
mgpuMemHostRegister(ptr, sizeBytes);
}
// Allows to unregister byte array with the ROCM runtime. Helpful until we have
// transfer functions implemented.
extern "C" void mgpuMemHostUnregister(void *ptr) {
HIP_REPORT_IF_ERROR(hipHostUnregister(ptr));
}
// Allows to unregister a MemRef with the ROCm runtime. Helpful until we have
// transfer functions implemented.
extern "C" void
mgpuMemHostUnregisterMemRef(int64_t rank,
StridedMemRefType<char, 1> *descriptor,
int64_t elementSizeBytes) {
auto ptr = descriptor->data + descriptor->offset * elementSizeBytes;
mgpuMemHostUnregister(ptr);
}
template <typename T>
void mgpuMemGetDevicePointer(T *hostPtr, T **devicePtr) {
HIP_REPORT_IF_ERROR(hipSetDevice(0));
HIP_REPORT_IF_ERROR(
hipHostGetDevicePointer((void **)devicePtr, hostPtr, /*flags=*/0));
}
extern "C" StridedMemRefType<float, 1>
mgpuMemGetDeviceMemRef1dFloat(float *allocated, float *aligned, int64_t offset,
int64_t size, int64_t stride) {
float *devicePtr = nullptr;
mgpuMemGetDevicePointer(aligned, &devicePtr);
return {devicePtr, devicePtr, offset, {size}, {stride}};
}
extern "C" StridedMemRefType<int32_t, 1>
mgpuMemGetDeviceMemRef1dInt32(int32_t *allocated, int32_t *aligned,
int64_t offset, int64_t size, int64_t stride) {
int32_t *devicePtr = nullptr;
mgpuMemGetDevicePointer(aligned, &devicePtr);
return {devicePtr, devicePtr, offset, {size}, {stride}};
}
extern "C" void mgpuSetDefaultDevice(int32_t device) {
defaultDevice = device;
HIP_REPORT_IF_ERROR(hipSetDevice(device));
}