/* * Copyright (c) 2022-2024, 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 #include #include #include "tensorrt_llm/common/assert.h" #include "tensorrt_llm/common/cudaUtils.h" namespace tensorrt_llm::kernels { constexpr size_t WARP_SIZE = 32; constexpr size_t MAX_ALL_REDUCE_BLOCKS = 24; constexpr size_t MAX_RANKS_PER_NODE = 16; constexpr size_t DEFAULT_BLOCK_SIZE = 512; namespace reduce_fusion::details { static constexpr int kBytesPerAccess = 16; static constexpr int kWarpSize = 32; static constexpr int kMaxCtaSize = 1024; static constexpr int kClusterMaxSize = 8; static constexpr int kLamportTokenNumThreshold = 16; static constexpr int kLamportHiddenSizeThreshold = 256; }; // namespace reduce_fusion::details // Warning: python definition is in tensorrt_llm/functional.py // they must be kept in sync enum class AllReduceStrategyType : int8_t { NCCL = 0, MIN_LATENCY = 1, UB = 2, AUTO = 3, ONESHOT = 4, TWOSHOT = 5, LOWPRECISION = 6, }; enum class AllReduceStrategyConfig : int8_t { USE_MEMCPY = 1 << 0, PUSH_MODE = 1 << 1, }; enum class AllReduceFusionOp : int8_t { NONE = 0, RESIDUAL_RMS_NORM = 1, LAST_PROCESS_FOR_UB = 2, RESIDUAL_RMS_PREPOST_NORM = 3, RESIDUAL_RMS_NORM_QUANT_FP8 = 4, RESIDUAL_RMS_NORM_QUANT_NVFP4 = 5, RESIDUAL_RMS_NORM_OUT_QUANT_FP8 = 6, RESIDUAL_RMS_NORM_OUT_QUANT_NVFP4 = 7, MOE_ALLREDUCE_RESIDUAL_RMS_NORM = 8, }; inline std::ostream& operator<<(std::ostream& os, AllReduceFusionOp op) { switch (op) { case AllReduceFusionOp::NONE: os << "NONE"; break; case AllReduceFusionOp::RESIDUAL_RMS_NORM: os << "RESIDUAL_RMS_NORM"; break; case AllReduceFusionOp::LAST_PROCESS_FOR_UB: os << "LAST_PROCESS_FOR_UB"; break; case AllReduceFusionOp::RESIDUAL_RMS_PREPOST_NORM: os << "RESIDUAL_RMS_PREPOST_NORM"; break; case AllReduceFusionOp::RESIDUAL_RMS_NORM_QUANT_FP8: os << "RESIDUAL_RMS_NORM_QUANT_FP8"; break; case AllReduceFusionOp::RESIDUAL_RMS_NORM_QUANT_NVFP4: os << "RESIDUAL_RMS_NORM_QUANT_NVFP4"; break; case AllReduceFusionOp::RESIDUAL_RMS_NORM_OUT_QUANT_FP8: os << "RESIDUAL_RMS_NORM_OUT_QUANT_FP8"; break; case AllReduceFusionOp::RESIDUAL_RMS_NORM_OUT_QUANT_NVFP4: os << "RESIDUAL_RMS_NORM_OUT_QUANT_NVFP4"; break; case AllReduceFusionOp::MOE_ALLREDUCE_RESIDUAL_RMS_NORM: os << "MOE_ALLREDUCE_RESIDUAL_RMS_NORM"; break; default: os << "UNKNOWN"; break; } return os; } inline std::string toString(AllReduceFusionOp op) { std::ostringstream oss; oss << op; return oss.str(); } struct AllReduceFusionParams { AllReduceFusionParams() : bias_buffer(nullptr) , residual_buffer(nullptr) , weight_buffer(nullptr) , weight_buffer_pre_residual_norm(nullptr) , intermediate_buffer(nullptr) { } // gemm bias void const* bias_buffer; // residuial add void const* residual_buffer; // rms norm int hidden_size; // equal to normalized_shape void const* weight_buffer; // norm elem-wise affine gamma void const* weight_buffer_pre_residual_norm; // for gemma norm before residual float eps; // new residual void* intermediate_buffer; void* lamport_peer_comm_buffer_ptrs[MAX_RANKS_PER_NODE * 3]; }; struct AllReduceParams { size_t elts_total; size_t elts_per_rank; size_t elts_per_block; size_t rank_offset; size_t ranks_per_node; size_t local_rank; uint32_t barrier_flag; uint32_t* peer_barrier_ptrs_in[MAX_RANKS_PER_NODE]; uint32_t* peer_barrier_ptrs_out[MAX_RANKS_PER_NODE]; void* peer_comm_buffer_ptrs[MAX_RANKS_PER_NODE]; void* local_output_buffer_ptr; void const* local_input_buffer_ptr; AllReduceFusionParams fusion_params; static AllReduceParams deserialize(int64_t* buffer, size_t tpSize, size_t tpRank, nvinfer1::DataType dataType, int token_num, int hidden_size, AllReduceFusionOp op); }; bool configurationSupported(AllReduceStrategyType algo, size_t msg_size, size_t n_ranks, nvinfer1::DataType type); void customAllReduce(kernels::AllReduceParams& params, nvinfer1::DataType dataType, AllReduceStrategyType strat, AllReduceStrategyConfig config, AllReduceFusionOp fusionOp, cudaStream_t stream); void residualRmsNorm( kernels::AllReduceParams& params, nvinfer1::DataType dataType, cudaStream_t stream, AllReduceFusionOp fusionOp); void lamportInitialize(void* buffer, size_t size, nvinfer1::DataType dataType, cudaStream_t stream); } // namespace tensorrt_llm::kernels