84 lines
2.3 KiB
C
84 lines
2.3 KiB
C
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/*
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* Copyright 2021 Blender Foundation
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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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CCL_NAMESPACE_BEGIN
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/* Parallel sum of array input_data with size n into output_sum.
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*
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* Adapted from "Optimizing Parallel Reduction in GPU", Mark Harris.
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*
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* This version adds multiple elements per thread sequentially. This reduces
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* the overall cost of the algorithm while keeping the work complexity O(n) and
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* the step complexity O(log n). (Brent's Theorem optimization) */
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#define GPU_PARALLEL_SUM_DEFAULT_BLOCK_SIZE 512
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template<uint blocksize, typename InputT, typename OutputT, typename ConvertOp>
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__device__ void gpu_parallel_sum(
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const InputT *input_data, const uint n, OutputT *output_sum, OutputT zero, ConvertOp convert)
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{
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extern ccl_gpu_shared OutputT shared_data[];
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const uint tid = ccl_gpu_thread_idx_x;
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const uint gridsize = blocksize * ccl_gpu_grid_dim_x();
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OutputT sum = zero;
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for (uint i = ccl_gpu_block_idx_x * blocksize + tid; i < n; i += gridsize) {
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sum += convert(input_data[i]);
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}
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shared_data[tid] = sum;
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ccl_gpu_syncthreads();
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if (blocksize >= 512 && tid < 256) {
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shared_data[tid] = sum = sum + shared_data[tid + 256];
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}
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ccl_gpu_syncthreads();
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if (blocksize >= 256 && tid < 128) {
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shared_data[tid] = sum = sum + shared_data[tid + 128];
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}
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ccl_gpu_syncthreads();
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if (blocksize >= 128 && tid < 64) {
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shared_data[tid] = sum = sum + shared_data[tid + 64];
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}
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ccl_gpu_syncthreads();
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if (blocksize >= 64 && tid < 32) {
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shared_data[tid] = sum = sum + shared_data[tid + 32];
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}
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ccl_gpu_syncthreads();
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if (tid < 32) {
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for (int offset = ccl_gpu_warp_size / 2; offset > 0; offset /= 2) {
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sum += ccl_shfl_down_sync(0xFFFFFFFF, sum, offset);
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}
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}
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if (tid == 0) {
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output_sum[ccl_gpu_block_idx_x] = sum;
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}
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}
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CCL_NAMESPACE_END
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