mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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69 lines
2.5 KiB
C++
69 lines
2.5 KiB
C++
/*
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* Copyright (c) 2020-2023, NVIDIA CORPORATION. All rights reserved.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#pragma once
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#if defined(USING_OSS_CUTLASS_ALLREDUCE_GEMM)
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#include "tensorrt_llm/kernels/cutlass_kernels/include/allreduce_gemm_runner.h"
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#else
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#include "allreduce_gemm_runner.h"
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#endif
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#include "tensorrt_llm/plugins/common/gemmPluginProfiler.h"
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#include "tensorrt_llm/plugins/common/plugin.h"
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namespace tensorrt_llm::plugins
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{
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/*
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* Used for tuning to find best GEMM configs for different problem shapes.
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* WARNING: Tuning GEMM+AR kernel may not be fully representable of real
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* multi-GPU workloads as tuning only runs on single-GPU.
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* IMPORTANT: TRT-LLM does not support deterministic tuning across ranks.
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* Because of this, we have to serialize/deserialize our own configuration file.
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*/
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#if defined(USING_OSS_CUTLASS_ALLREDUCE_GEMM)
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namespace cutlass_kernels = ::tensorrt_llm::kernels::opened_cutlass_kernels;
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#else
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namespace cutlass_kernels = ::tensorrt_llm::kernels::cutlass_kernels;
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#endif
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class GemmAllReducePluginProfiler
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: public GemmPluginProfiler<cutlass_kernels::GemmAllReduceImplInterface::LaunchConfig,
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std::shared_ptr<cutlass_kernels::GemmAllReduceImplInterface>, GemmIdCore, GemmIdCoreHash>
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{
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public:
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void serializeToOwnFile(GemmIdCore gemmId);
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void deserializeFromOwnFile(GemmIdCore gemmId, GemmDims problemShape);
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bool useProfiler();
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protected:
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////////////////////////////////////
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// GemmPluginProfiler methods
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////////////////////////////////////
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void runTactic(int m, int n, int k, cutlass_kernels::GemmAllReduceImplInterface::LaunchConfig const& tactic,
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char* workspace, cudaStream_t const& stream) override;
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void computeTmpSize(size_t maxM, size_t n, size_t k) override;
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std::vector<cutlass_kernels::GemmAllReduceImplInterface::LaunchConfig> getTactics(
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int m, int n, int k) const override;
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private:
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static std::string getCacheFileName(GemmIdCore gemmId);
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};
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} // namespace tensorrt_llm::plugins
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