2023-05-14 22:19:19 -07:00
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/*
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* Adapted from https://github.com/NVIDIA/FasterTransformer/blob/release/v5.3_tag/src/fastertransformer/kernels/reduce_kernel_utils.cuh
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2023-06-17 03:07:40 -07:00
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* Copyright (c) 2023, The vLLM team.
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2023-05-14 22:19:19 -07:00
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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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2023-05-03 13:40:13 -07:00
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#pragma once
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2023-12-08 15:16:52 +08:00
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#include "cuda_compat.h"
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2023-06-17 03:07:40 -07:00
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namespace vllm {
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2023-05-03 13:40:13 -07:00
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template<typename T>
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__inline__ __device__ T warpReduceSum(T val) {
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#pragma unroll
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for (int mask = WARP_SIZE/2; mask > 0; mask >>= 1)
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2023-12-08 15:16:52 +08:00
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val += VLLM_SHFL_XOR_SYNC(val, mask);
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2023-05-03 13:40:13 -07:00
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return val;
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}
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2024-03-12 04:14:07 +08:00
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__inline__ __device__ constexpr int _calculateLaneMask(int warp_size) {
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return warp_size - 1;
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}
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__inline__ __device__ constexpr int _calculateWidShift(int warp_size) {
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return 5 + (warp_size >> 6);
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}
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2023-05-03 13:40:13 -07:00
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/* Calculate the sum of all elements in a block */
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template<typename T>
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__inline__ __device__ T blockReduceSum(T val) {
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static __shared__ T shared[WARP_SIZE];
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constexpr auto LANE_MASK = _calculateLaneMask(WARP_SIZE);
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constexpr auto WID_SHIFT = _calculateWidShift(WARP_SIZE);
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int lane = threadIdx.x & LANE_MASK;
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int wid = threadIdx.x >> WID_SHIFT;
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2023-05-03 13:40:13 -07:00
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val = warpReduceSum<T>(val);
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if (lane == 0)
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shared[wid] = val;
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__syncthreads();
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// Modify from blockDim.x << 5 to blockDim.x / 32. to prevent
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// blockDim.x is not divided by 32
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val = (threadIdx.x < (blockDim.x / (WARP_SIZE * 1.0f))) ? shared[lane] : (T)(0.0f);
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val = warpReduceSum<T>(val);
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return val;
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}
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2023-06-17 03:07:40 -07:00
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} // namespace vllm
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