Cleanup: remove some unused Cycles GPU code
To make porting to other architectures easier, clarifying that this does not need to be supported. The unused parallel_reduce implementation assumed warp size 32, but is easy to update if we ever need it in the future.
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@ -50,7 +50,6 @@ set(SRC_KERNEL_DEVICE_GPU_HEADERS
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device/gpu/kernel.h
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device/gpu/parallel_active_index.h
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device/gpu/parallel_prefix_sum.h
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device/gpu/parallel_reduce.h
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device/gpu/parallel_sorted_index.h
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device/gpu/work_stealing.h
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)
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@ -72,7 +72,6 @@ typedef unsigned long long uint64_t;
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#define ccl_gpu_syncthreads() __syncthreads()
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#define ccl_gpu_ballot(predicate) __ballot_sync(0xFFFFFFFF, predicate)
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#define ccl_gpu_shfl_down_sync(mask, var, detla) __shfl_down_sync(mask, var, detla)
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/* GPU texture objects */
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@ -1,74 +0,0 @@
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/* SPDX-License-Identifier: Apache-2.0
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* Copyright 2021-2022 Blender Foundation */
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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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#ifdef __HIP__
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# define GPU_PARALLEL_SUM_DEFAULT_BLOCK_SIZE 1024
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#else
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# define GPU_PARALLEL_SUM_DEFAULT_BLOCK_SIZE 512
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#endif
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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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@ -71,7 +71,6 @@ typedef unsigned long long uint64_t;
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#define ccl_gpu_syncthreads() __syncthreads()
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#define ccl_gpu_ballot(predicate) __ballot(predicate)
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#define ccl_gpu_shfl_down_sync(mask, var, detla) __shfl_down(var, detla)
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/* GPU texture objects */
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typedef hipTextureObject_t ccl_gpu_tex_object;
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@ -74,7 +74,6 @@ typedef unsigned long long uint64_t;
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#define ccl_gpu_syncthreads() __syncthreads()
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#define ccl_gpu_ballot(predicate) __ballot_sync(0xFFFFFFFF, predicate)
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#define ccl_gpu_shfl_down_sync(mask, var, detla) __shfl_down_sync(mask, var, detla)
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/* GPU texture objects */
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