TensorRT-LLMs/cpp/tensorrt_llm/kernels/contextFusedMultiHeadAttention/fmhaRunner.h
Kaiyu Xie be9cd719f7
Update TensorRT-LLM (#2094)
* Update TensorRT-LLM

---------

Co-authored-by: akhoroshev <arthoroshev@gmail.com>
Co-authored-by: Fabian Joswig <fjosw@users.noreply.github.com>
Co-authored-by: Tayef Shah <tayefshah@gmail.com>
Co-authored-by: lfz941 <linfanzai941@gmail.com>
2024-08-07 16:44:43 +08:00

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/*
* 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 <cassert>
#include <cstring>
#include <iostream>
#include <memory>
#include <tuple>
#include <vector>
#include <cublas_v2.h>
#include <cuda_fp16.h>
#include <cuda_runtime.h>
#include "fused_multihead_attention_common.h"
#include "fused_multihead_attention_v2.h"
#include "tensorrt_llm/common/cudaUtils.h"
#include "tmaDescriptor.h"
namespace tensorrt_llm
{
namespace kernels
{
////////////////////////////////////////////////////////////////////////////////////////////////////
// Workflow of fmha runner:
// 1. check if FMHA kernels are supported statically.
// 2. construct FMHA runner object with the fixed params.
// 3. run the kernel (with all needed device pointers).
class FusedMHARunnerV2
{
public:
// Constructor.
FusedMHARunnerV2(MHARunnerFixedParams fixedParams);
// Deconstructor.
~FusedMHARunnerV2() = default; // for pimpl
// Check if any fmha kernel meets the requirements.
bool isFmhaSupported();
// Run the fmha kernel.
void run(MHARunnerParams runnerParams);
private:
// Set the kernel params.
void setupKernelParams(MHARunnerParams runnerParams);
// Set the launch params to select kernels.
void setupLaunchParams(MHARunnerParams runnerParams);
// Set the tma descriptors for packed qkv input.
void setPackedQkvTmaDescriptors(MHARunnerParams runnerParams);
// Set the tma descriptors for separate q and kv input.
void setSeparateQKvTmaDescriptors(MHARunnerParams runnerParams);
// Check if it is a valid sequence length (only used by non-flash-attention kernels).
bool isValidS(int s) const;
// Get the kernel sequence that support the max sequence length (only used by non-flash-attention kernels).
int getSFromMaxSeqLen(int const max_seq_len) const;
private:
// The attention fixed params (mostly related to the attention structure).
MHARunnerFixedParams mFixedParams;
// The attention input params (runtime-known parameters).
MHARunnerParams mRunnerParams;
// The launch params to select the specific fmha kernel.
Launch_params mLaunchParams;
// The kernel params.
Fused_multihead_attention_params_v2 mKernelParams;
// The SM version.
int mSM = tensorrt_llm::common::getSMVersion();
// The multiple processor count.
int mMultiProcessorCount;
// The L2 cache size.
int mDeviceL2CacheSize;
// The total device memory.
size_t mTotalDeviceMemory;
// The class that stores all the kernels.
FusedMultiHeadAttentionXMMAKernelV2 const* xmmaKernel;
};
} // namespace kernels
} // namespace tensorrt_llm