257 lines
9.3 KiB
C++
257 lines
9.3 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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#pragma once
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/** \file
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* \ingroup bli
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*/
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#ifdef WITH_TBB
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/* Quiet top level deprecation message, unrelated to API usage here. */
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# if defined(WIN32) && !defined(NOMINMAX)
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/* TBB includes Windows.h which will define min/max macros causing issues
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* when we try to use std::min and std::max later on. */
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# define NOMINMAX
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# define TBB_MIN_MAX_CLEANUP
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# endif
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# include <tbb/blocked_range.h>
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# include <tbb/parallel_for.h>
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# include <tbb/parallel_for_each.h>
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# include <tbb/parallel_invoke.h>
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# include <tbb/parallel_reduce.h>
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# include <tbb/task_arena.h>
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# ifdef WIN32
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/* We cannot keep this defined, since other parts of the code deal with this on their own, leading
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* to multiple define warnings unless we un-define this, however we can only undefine this if we
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* were the ones that made the definition earlier. */
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# ifdef TBB_MIN_MAX_CLEANUP
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# undef NOMINMAX
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# endif
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# endif
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#endif
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#include "BLI_function_ref.hh"
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#include "BLI_index_range.hh"
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#include "BLI_lazy_threading.hh"
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#include "BLI_task_size_hints.hh"
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namespace blender {
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/**
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* Wrapper type around an integer to differentiate it from other parameters in a function call.
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*/
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struct GrainSize {
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int64_t value;
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explicit constexpr GrainSize(const int64_t grain_size) : value(grain_size) {}
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};
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} // namespace blender
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namespace blender::threading {
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template<typename Range, typename Function>
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inline void parallel_for_each(Range &&range, const Function &function)
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{
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#ifdef WITH_TBB
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tbb::parallel_for_each(range, function);
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#else
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for (auto &&value : range) {
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function(value);
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}
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#endif
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}
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namespace detail {
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void parallel_for_impl(IndexRange range,
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int64_t grain_size,
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FunctionRef<void(IndexRange)> function,
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const TaskSizeHints &size_hints);
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void memory_bandwidth_bound_task_impl(FunctionRef<void()> function);
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} // namespace detail
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/**
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* Executes the given function for sub-ranges of the given range, potentially in parallel.
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* This is the main primitive for parallelizing code.
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*
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* \param range: The indices that should be iterated over in parallel.
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* \param grain_size: The approximate amount of work that should be scheduled at once.
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* For example of the range is [0 - 1000] and the grain size is 200, then the function will be
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* called 5 times with [0 - 200], [201 - 400], ... (approximately). The `size_hints` parameter
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* can be used to adjust how the work is split up if the tasks have different sizes.
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* \param function: A callback that actually does the work in parallel. It should have one
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* #IndexRange parameter.
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* \param size_hints: Can be used to specify the size of the tasks *relative to* each other and the
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* grain size. If all tasks have approximately the same size, this can be ignored. Otherwise, one
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* can use `threading::individual_task_sizes(...)` or `threading::accumulated_task_sizes(...)`.
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* If the grain size is e.g. 200 and each task has the size 100, then only two tasks will be
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* scheduled at once.
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*/
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template<typename Function>
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inline void parallel_for(const IndexRange range,
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const int64_t grain_size,
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const Function &function,
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const TaskSizeHints &size_hints = detail::TaskSizeHints_Static(1))
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{
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if (range.is_empty()) {
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return;
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}
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/* Invoking tbb for small workloads has a large overhead. */
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if (use_single_thread(size_hints, range, grain_size)) {
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function(range);
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return;
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}
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detail::parallel_for_impl(range, grain_size, function, size_hints);
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}
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/**
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* Move the sub-range boundaries down to the next aligned index. The "global" begin and end
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* remain fixed though.
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*/
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inline IndexRange align_sub_range(const IndexRange unaligned_range,
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const int64_t alignment,
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const IndexRange global_range)
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{
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const int64_t global_begin = global_range.start();
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const int64_t global_end = global_range.one_after_last();
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const int64_t alignment_mask = ~(alignment - 1);
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const int64_t unaligned_begin = unaligned_range.start();
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const int64_t unaligned_end = unaligned_range.one_after_last();
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const int64_t aligned_begin = std::max(global_begin, unaligned_begin & alignment_mask);
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const int64_t aligned_end = unaligned_end == global_end ?
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unaligned_end :
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std::max(global_begin, unaligned_end & alignment_mask);
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const IndexRange aligned_range = IndexRange::from_begin_end(aligned_begin, aligned_end);
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return aligned_range;
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}
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/**
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* Same as #parallel_for but tries to make the sub-range sizes multiples of the given alignment.
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* This can improve performance when the range is processed using vectorized and/or unrolled loops,
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* because the fallback loop that processes remaining values is used less often. A disadvantage of
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* using this instead of #parallel_for is that the size differences between sub-ranges can be
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* larger, which means that work is distributed less evenly.
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*/
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template<typename Function>
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inline void parallel_for_aligned(const IndexRange range,
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const int64_t grain_size,
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const int64_t alignment,
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const Function &function)
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{
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parallel_for(range, grain_size, [&](const IndexRange unaligned_range) {
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const IndexRange aligned_range = align_sub_range(unaligned_range, alignment, range);
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function(aligned_range);
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});
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}
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template<typename Value, typename Function, typename Reduction>
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inline Value parallel_reduce(IndexRange range,
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int64_t grain_size,
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const Value &identity,
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const Function &function,
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const Reduction &reduction)
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{
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#ifdef WITH_TBB
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if (range.size() >= grain_size) {
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lazy_threading::send_hint();
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return tbb::parallel_reduce(
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tbb::blocked_range<int64_t>(range.first(), range.one_after_last(), grain_size),
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identity,
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[&](const tbb::blocked_range<int64_t> &subrange, const Value &ident) {
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return function(IndexRange(subrange.begin(), subrange.size()), ident);
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},
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reduction);
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}
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#else
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UNUSED_VARS(grain_size, reduction);
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#endif
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return function(range, identity);
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}
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template<typename Value, typename Function, typename Reduction>
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inline Value parallel_reduce_aligned(const IndexRange range,
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const int64_t grain_size,
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const int64_t alignment,
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const Value &identity,
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const Function &function,
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const Reduction &reduction)
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{
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parallel_reduce(
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range,
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grain_size,
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identity,
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[&](const IndexRange unaligned_range, const Value &ident) {
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const IndexRange aligned_range = align_sub_range(unaligned_range, alignment, range);
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function(aligned_range, ident);
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},
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reduction);
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}
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/**
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* Execute all of the provided functions. The functions might be executed in parallel or in serial
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* or some combination of both.
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*/
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template<typename... Functions> inline void parallel_invoke(Functions &&...functions)
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{
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#ifdef WITH_TBB
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tbb::parallel_invoke(std::forward<Functions>(functions)...);
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#else
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(functions(), ...);
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#endif
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}
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/**
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* Same #parallel_invoke, but allows disabling threading dynamically. This is useful because when
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* the individual functions do very little work, there is a lot of overhead from starting parallel
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* tasks.
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*/
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template<typename... Functions>
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inline void parallel_invoke(const bool use_threading, Functions &&...functions)
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{
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if (use_threading) {
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lazy_threading::send_hint();
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parallel_invoke(std::forward<Functions>(functions)...);
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}
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else {
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(functions(), ...);
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}
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}
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/** See #BLI_task_isolate for a description of what isolating a task means. */
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template<typename Function> inline void isolate_task(const Function &function)
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{
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#ifdef WITH_TBB
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lazy_threading::ReceiverIsolation isolation;
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tbb::this_task_arena::isolate(function);
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#else
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function();
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#endif
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}
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/**
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* Should surround parallel code that is highly bandwidth intensive, e.g. it just fills a buffer
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* with no or just few additional operations. If the buffers are large, it's beneficial to limit
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* the number of threads doing the work because that just creates more overhead on the hardware
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* level and doesn't provide a notable performance benefit beyond a certain point.
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*/
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template<typename Function>
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inline void memory_bandwidth_bound_task(const int64_t approximate_bytes_touched,
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const Function &function)
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{
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/* Don't limit threading when all touched memory can stay in the CPU cache, because there a much
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* higher memory bandwidth is available compared to accessing RAM. This value is supposed to be
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* on the order of the L3 cache size. Accessing that value is not quite straight forward and even
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* if it was, it's not clear if using the exact cache size would be beneficial because there is
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* often more stuff going on the CPU at the same time. */
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if (approximate_bytes_touched <= 8 * 1024 * 1024) {
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function();
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return;
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}
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detail::memory_bandwidth_bound_task_impl(function);
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}
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} // namespace blender::threading
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