TensorRT-LLMs/cpp/tensorrt_llm/kernels/trtllmGenKernels/fmha/fmhaRunner.h
zhhuang-nv 94e6167879
optimize cudaMemGetInfo for TllmGenFmhaRunner (#3907)
Signed-off-by: Zhen Huang <145532724+zhhuang-nv@users.noreply.github.com>
2025-04-29 14:17:07 +08:00

63 lines
1.7 KiB
C++

/*
* Copyright (c) 2020-2023, 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_runtime.h>
#include "fmhaKernels.h"
#include "fmhaRunnerParams.h"
#include "tensorrt_llm/kernels/multiHeadAttentionCommon.h"
namespace tensorrt_llm
{
namespace kernels
{
class TllmGenFmhaRunner
{
public:
// Constructor.
explicit TllmGenFmhaRunner(Data_type dtypeQ, Data_type dtypeKv, Data_type dtypeOut);
TllmGenFmhaRunner() = default;
// Check if fmha is supported.
bool isSupported(TllmGenFmhaRunnerParams const& runnerParams) const;
// Check if fmha is supported with additional info.
std::pair<bool, std::string> isSupportedWithInfo(TllmGenFmhaRunnerParams const& runnerParams) const;
// Get the total device memory.
size_t getTotalDeviceMemory() const;
// Run the fmha kernel.
void run(TllmGenFmhaRunnerParams const&);
private:
// The input/output datatype.
Data_type mDtypeQ, mDtypeKv, mDtypeOut;
// The SM version.
int mSM;
// The total device memory.
size_t mTotalDeviceMemory;
// The class that stores all the kernels.
TllmGenFmhaKernel const* mKernel;
};
} // namespace kernels
} // namespace tensorrt_llm