The standard `threading::parallel_for` function tries to split the range into uniformly sized subranges. This is great if each element takes approximately the same amount of time to compute. However, there are also situations where the time required to do the work for a single index differs significantly between different indices. In such a case, it's better to split the tasks into segments while taking the size of each task into account. This patch implements `threading::parallel_for_weighted` which allows passing in an additional callback that returns the size of each task. Pull Request: https://projects.blender.org/blender/blender/pulls/118348
227 lines
6.5 KiB
C++
227 lines
6.5 KiB
C++
/* SPDX-FileCopyrightText: 2023 Blender Authors
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*
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* SPDX-License-Identifier: GPL-2.0-or-later */
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/** \file
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* \ingroup bli
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*
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* Task parallel range functions.
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*/
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#include <cstdlib>
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#include "MEM_guardedalloc.h"
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#include "BLI_array.hh"
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#include "BLI_lazy_threading.hh"
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#include "BLI_offset_indices.hh"
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#include "BLI_task.h"
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#include "BLI_task.hh"
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#include "BLI_threads.h"
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#include "BLI_vector.hh"
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#include "atomic_ops.h"
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#ifdef WITH_TBB
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# include <tbb/blocked_range.h>
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# include <tbb/enumerable_thread_specific.h>
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# include <tbb/parallel_for.h>
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# include <tbb/parallel_reduce.h>
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#endif
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#ifdef WITH_TBB
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/* Functor for running TBB parallel_for and parallel_reduce. */
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struct RangeTask {
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TaskParallelRangeFunc func;
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void *userdata;
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const TaskParallelSettings *settings;
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void *userdata_chunk;
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/* Root constructor. */
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RangeTask(TaskParallelRangeFunc func, void *userdata, const TaskParallelSettings *settings)
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: func(func), userdata(userdata), settings(settings)
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{
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init_chunk(settings->userdata_chunk);
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}
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/* Copy constructor. */
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RangeTask(const RangeTask &other)
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: func(other.func), userdata(other.userdata), settings(other.settings)
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{
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init_chunk(settings->userdata_chunk);
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}
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/* Splitting constructor for parallel reduce. */
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RangeTask(RangeTask &other, tbb::split /*unused*/)
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: func(other.func), userdata(other.userdata), settings(other.settings)
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{
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init_chunk(settings->userdata_chunk);
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}
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~RangeTask()
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{
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if (settings->func_free != nullptr) {
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settings->func_free(userdata, userdata_chunk);
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}
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MEM_SAFE_FREE(userdata_chunk);
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}
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void init_chunk(void *from_chunk)
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{
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if (from_chunk) {
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userdata_chunk = MEM_mallocN(settings->userdata_chunk_size, "RangeTask");
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memcpy(userdata_chunk, from_chunk, settings->userdata_chunk_size);
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}
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else {
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userdata_chunk = nullptr;
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}
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}
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void operator()(const tbb::blocked_range<int> &r) const
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{
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TaskParallelTLS tls;
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tls.userdata_chunk = userdata_chunk;
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for (int i = r.begin(); i != r.end(); ++i) {
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func(userdata, i, &tls);
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}
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}
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void join(const RangeTask &other)
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{
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settings->func_reduce(userdata, userdata_chunk, other.userdata_chunk);
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}
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};
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#endif
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void BLI_task_parallel_range(const int start,
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const int stop,
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void *userdata,
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TaskParallelRangeFunc func,
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const TaskParallelSettings *settings)
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{
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#ifdef WITH_TBB
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/* Multithreading. */
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if (settings->use_threading && BLI_task_scheduler_num_threads() > 1) {
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RangeTask task(func, userdata, settings);
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const size_t grainsize = std::max(settings->min_iter_per_thread, 1);
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const tbb::blocked_range<int> range(start, stop, grainsize);
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blender::lazy_threading::send_hint();
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if (settings->func_reduce) {
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parallel_reduce(range, task);
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if (settings->userdata_chunk) {
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memcpy(settings->userdata_chunk, task.userdata_chunk, settings->userdata_chunk_size);
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}
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}
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else {
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parallel_for(range, task);
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}
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return;
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}
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#endif
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/* Single threaded. Nothing to reduce as everything is accumulated into the
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* main userdata chunk directly. */
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TaskParallelTLS tls;
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tls.userdata_chunk = settings->userdata_chunk;
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for (int i = start; i < stop; i++) {
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func(userdata, i, &tls);
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}
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if (settings->func_free != nullptr) {
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settings->func_free(userdata, settings->userdata_chunk);
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}
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}
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int BLI_task_parallel_thread_id(const TaskParallelTLS * /*tls*/)
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{
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#ifdef WITH_TBB
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/* Get a unique thread ID for texture nodes. In the future we should get rid
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* of the thread ID and change texture evaluation to not require per-thread
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* storage that can't be efficiently allocated on the stack. */
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static tbb::enumerable_thread_specific<int> tbb_thread_id(-1);
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static int tbb_thread_id_counter = 0;
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int &thread_id = tbb_thread_id.local();
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if (thread_id == -1) {
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thread_id = atomic_fetch_and_add_int32(&tbb_thread_id_counter, 1);
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if (thread_id >= BLENDER_MAX_THREADS) {
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BLI_assert_msg(0, "Maximum number of threads exceeded for sculpting");
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thread_id = thread_id % BLENDER_MAX_THREADS;
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}
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}
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return thread_id;
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#else
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return 0;
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#endif
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}
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namespace blender::threading::detail {
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void parallel_for_impl(const IndexRange range,
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const int64_t grain_size,
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const FunctionRef<void(IndexRange)> function)
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{
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#ifdef WITH_TBB
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/* Invoking tbb for small workloads has a large overhead. */
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if (range.size() >= grain_size) {
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lazy_threading::send_hint();
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tbb::parallel_for(
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tbb::blocked_range<int64_t>(range.first(), range.one_after_last(), grain_size),
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[function](const tbb::blocked_range<int64_t> &subrange) {
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function(IndexRange(subrange.begin(), subrange.size()));
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});
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return;
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}
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#else
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UNUSED_VARS(grain_size);
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#endif
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function(range);
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}
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void parallel_for_weighted_impl(
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const IndexRange range,
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const int64_t grain_size,
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const FunctionRef<void(IndexRange)> function,
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const FunctionRef<void(IndexRange, MutableSpan<int64_t>)> task_sizes_fn)
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{
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/* Shouldn't be too small, because then there is more overhead when the individual tasks are
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* small. Also shouldn't be too large because then the serial code to split up tasks causes extra
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* overhead. */
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const int64_t outer_grain_size = std::min<int64_t>(grain_size, 512);
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threading::parallel_for(range, outer_grain_size, [&](const IndexRange sub_range) {
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/* Compute the size of every task in the current range. */
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Array<int64_t, 1024> task_sizes(sub_range.size());
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task_sizes_fn(sub_range, task_sizes);
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/* Split range into multiple segments that have a size that approximates the grain size. */
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Vector<int64_t, 256> offsets_vec;
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offsets_vec.append(0);
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int64_t counter = 0;
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for (const int64_t i : sub_range.index_range()) {
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counter += task_sizes[i];
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if (counter >= grain_size) {
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offsets_vec.append(i + 1);
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counter = 0;
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}
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}
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if (offsets_vec.last() < sub_range.size()) {
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offsets_vec.append(sub_range.size());
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}
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const OffsetIndices<int64_t> offsets = offsets_vec.as_span();
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/* Run the dynamically split tasks in parallel. */
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threading::parallel_for(offsets.index_range(), 1, [&](const IndexRange offsets_range) {
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for (const int64_t i : offsets_range) {
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const IndexRange actual_range = offsets[i].shift(sub_range.start());
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function(actual_range);
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}
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});
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});
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}
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} // namespace blender::threading::detail
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