mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
108 lines
3.2 KiB
C++
108 lines
3.2 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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#include <cassert>
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#include <cstring>
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#include <iostream>
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#include <memory>
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#include <tuple>
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#include <vector>
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#include <cublas_v2.h>
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#include <cuda_fp16.h>
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#include <cuda_runtime.h>
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#include "fused_multihead_attention_common.h"
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#include "fused_multihead_attention_v2.h"
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#include "tensorrt_llm/common/config.h"
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#include "tensorrt_llm/common/cudaUtils.h"
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#include "tmaDescriptor.h"
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TRTLLM_NAMESPACE_BEGIN
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namespace kernels
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{
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////////////////////////////////////////////////////////////////////////////////////////////////////
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// Workflow of fmha runner:
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// 1. check if FMHA kernels are supported statically.
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// 2. construct FMHA runner object with the fixed params.
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// 3. run the kernel (with all needed device pointers).
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class FusedMHARunnerV2
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{
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public:
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// Constructor.
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FusedMHARunnerV2(MHARunnerFixedParams fixedParams);
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// Deconstructor.
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~FusedMHARunnerV2() = default; // for pimpl
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// Check if any fmha kernel meets the requirements.
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bool isFmhaSupported();
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// Does FMHA need a separate Q and Kv input ?
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bool isSeparateQAndKvInput() const
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{
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return mFixedParams.attentionInputLayout != AttentionInputLayout::PACKED_QKV;
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}
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// Run the fmha kernel.
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void run(MHARunnerParams runnerParams);
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private:
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// Set the kernel params.
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void setupKernelParams(MHARunnerParams runnerParams);
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// Set the launch params to select kernels.
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void setupLaunchParams(MHARunnerParams runnerParams);
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// Set the tma descriptors.
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void setTmaDescriptors(MHARunnerParams runnerParams);
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// Check if it is a valid sequence length (only used by non-flash-attention kernels).
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bool isValidS(int s) const;
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// Get the kernel sequence that support the max sequence length (only used by non-flash-attention kernels).
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int getSFromMaxSeqLen(int const max_seq_len) const;
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private:
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// The attention fixed params (mostly related to the attention structure).
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MHARunnerFixedParams mFixedParams;
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// The attention input params (runtime-known parameters).
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MHARunnerParams mRunnerParams;
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// The launch params to select the specific fmha kernel.
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Launch_params mLaunchParams;
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// The kernel params.
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Fused_multihead_attention_params_v2 mKernelParams;
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// The SM version.
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int mSM = tensorrt_llm::common::getSMVersion();
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// The multiple processor count.
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int mMultiProcessorCount;
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// The L2 cache size.
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int mDeviceL2CacheSize;
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// The total device memory.
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size_t mTotalDeviceMemory;
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// The class that stores all the kernels.
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FusedMultiHeadAttentionXMMAKernelV2 const* xmmaKernel;
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};
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} // namespace kernels
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TRTLLM_NAMESPACE_END
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