TensorRT-LLMs/cpp/tensorrt_llm/kernels/trtllmGenKernels/gemmGatedAct/KernelRunner.h
xiweny 0fdc6c7278
[TRTLLM-4629] [feat] trtllm-gen kernels support sm103 (#7570)
Signed-off-by: Xiwen Yu <13230610+VALLIS-NERIA@users.noreply.github.com>
2025-09-07 10:04:10 +08:00

60 lines
1.8 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 <optional>
#include "trtllmGen_gatedAct_export/trtllm/gen/DtypeDecl.h"
namespace tensorrt_llm
{
namespace kernels
{
struct TrtllmGenGemmGatedActRunnerOptions
{
gemmGatedAct::trtllm::gen::Dtype eltType;
gemmGatedAct::trtllm::gen::Dtype outputType;
bool deepSeekFp8{false};
bool transposeMmaOutput{false};
};
class TrtllmGenGemmGatedActRunner
{
public:
explicit TrtllmGenGemmGatedActRunner(TrtllmGenGemmGatedActRunnerOptions const& options);
[[nodiscard]] size_t getWorkspaceSizeInBytes(int32_t m, int32_t n, int32_t k);
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, float* cScaleGate, void* workspace, CUstream stream, int device);
void run(int32_t m, int32_t n, int32_t k, void const* a, void const* b, void* c, float* cScale, float* cScaleGate,
void* workspace, CUstream stream, int device);
private:
void selectGemmConfig(int32_t m, int32_t n, int32_t k);
private:
TrtllmGenGemmGatedActRunnerOptions mOptions;
std::optional<int> mSelectedConfigIndex;
std::vector<int32_t> mPassingConfigIndices;
};
} // namespace kernels
} // namespace tensorrt_llm