/* * 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" #include "tensorrt_llm/common/tensor.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 = 8; constexpr size_t DEFAULT_BLOCK_SIZE = 1024; // Warning: python definition is in tensorrt_llm/functional.py // they must be kept in sync enum class AllReduceStrategyType : int8_t { NCCL = 0, ONESHOT = 1, TWOSHOT = 2, AUTO = 3, }; enum class AllReduceStrategyConfig : int8_t { USE_MEMCPY = 1 << 0, PUSH_MODE = 1 << 1, }; 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, rank, 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; static AllReduceParams deserialize(int32_t const* buffer, size_t tpSize, size_t tpRank, uint32_t flag_value); }; 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, cudaStream_t stream); } // namespace tensorrt_llm::kernels