TensorRT-LLMs/cpp/tensorrt_llm/kernels/trtllmGenKernels/gemm/KernelRunner.h
Dom Brown a8310b01dc
feat: trtllm-gen fp4 GEMM for pytorch workflow (#3423)
* feat: trtllm-gen fp4 GEMM

Signed-off-by: Dom Brown <3886319+DomBrown@users.noreply.github.com>

* Clean up

Signed-off-by: Dom Brown <3886319+DomBrown@users.noreply.github.com>

* Remove incorrect header

Signed-off-by: Dom Brown <3886319+DomBrown@users.noreply.github.com>

* Reviewer comment

Signed-off-by: Dom Brown <3886319+DomBrown@users.noreply.github.com>

---------

Signed-off-by: Dom Brown <3886319+DomBrown@users.noreply.github.com>
2025-04-11 02:28:07 +08:00

49 lines
1.4 KiB
C++

/*
* Copyright (c) 2020-2025, NVIDIA CORPORATION. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#pragma once
#include <cuda.h>
#include "trtllmGen_export/GemmOptions.h"
#include "trtllmGen_export/trtllm/gen/DtypeDecl.h"
namespace tensorrt_llm
{
namespace kernels
{
namespace tg = trtllm::gen;
class TrtllmGenGemmRunner
{
public:
explicit TrtllmGenGemmRunner(tg::Dtype eltType, tg::Dtype outputType);
[[nodiscard]] size_t getWorkspaceSizeInBytes(
int32_t m, int32_t n, int32_t k, tg::Dtype eltType, tg::Dtype outputType) const;
void run(int32_t m, int32_t n, int32_t k, void const* a, float const* aScale, void const* b, float const* bScale,
void* c, float* cScale, void* workspace, CUstream stream, int device);
private:
tg::Dtype mEltType;
tg::Dtype mOutputType;
gemm::GemmConfig const* mGemmConfig;
};
} // namespace kernels
} // namespace tensorrt_llm