107 lines
3.2 KiB
C++
107 lines
3.2 KiB
C++
/* SPDX-License-Identifier: GPL-2.0-or-later */
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#pragma once
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/**
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* A #CacheMutex is used to protect a lazily computed cache from being computed more than once.
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* Using #CacheMutex instead of a "raw mutex" to protect a cache has some benefits:
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* - Avoid common pitfalls like forgetting to use task isolation or a double checked lock.
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* - Cleaner and less redundant code because the same locking patterns don't have to be repeated
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* everywhere.
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* - One can benefit from potential future improvements to #CacheMutex of which there are a few
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* mentioned below.
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*
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* The data protected by #CacheMutex is not part of #CacheMutex. Instead, the #CacheMutex and its
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* protected data should generally be placed next to each other.
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*
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* Each #CacheMutex protects exactly one cache, so multiple cache mutexes have to be used when a
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* class has multiple caches. That is contrary to a "custom" solution using `std::mutex` where one
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* mutex could protect multiple caches at the cost of higher lock contention.
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*
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* To make sure the cache is up to date, call `CacheMutex::ensure` and pass in the function that
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* computes the cache.
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*
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* To tell the #CacheMutex that the cache is invalidated and to be re-evaluated upon next access
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* use `CacheMutex::tag_dirty`.
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*
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* This example shows how one could implement a lazily computed average vertex position in an
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* imaginary `Mesh` data structure:
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*
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* \code{.cpp}
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* class Mesh {
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* private:
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* mutable CacheMutex average_position_cache_mutex_;
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* mutable float3 average_position_cache_;
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*
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* public:
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* const float3 &average_position() const
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* {
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* average_position_cache_mutex_.ensure([&]() {
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* average_position_cache_ = actually_compute_average_position();
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* });
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* return average_position_cache_;
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* }
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*
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* void tag_positions_changed()
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* {
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* average_position_cache_mutex_.tag_dirty();
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* }
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* };
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* \endcode
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*
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* Possible future improvements:
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* - Avoid task isolation when we know that the cache computation does not use threading.
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* - Try to use a smaller mutex. The mutex does not have to be fair for this use case.
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* - Try to join the cache computation instead of blocking if another thread is computing the cache
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* already.
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*/
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#include <atomic>
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#include <mutex>
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#include "BLI_function_ref.hh"
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namespace blender {
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class CacheMutex {
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private:
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std::mutex mutex_;
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std::atomic<bool> cache_valid_ = false;
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public:
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/**
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* Make sure the cache exists and is up to date. This calls `compute_cache` once to update the
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* cache (which is stored outside of this class) if it is dirty, otherwise it does nothing.
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*
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* This function is thread-safe under the assumption that the same parameters are passed from
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* every thread.
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*/
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void ensure(FunctionRef<void()> compute_cache);
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/**
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* Reset the cache. The next time #ensure is called, it will recompute that code.
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*/
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void tag_dirty()
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{
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cache_valid_.store(false);
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}
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/**
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* Return true if the cache currently does not exist or has been invalidated.
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*/
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bool is_dirty() const
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{
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return !this->is_cached();
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}
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/**
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* Return true if the cache exists and is valid.
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*/
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bool is_cached() const
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{
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return cache_valid_.load(std::memory_order_relaxed);
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}
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};
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} // namespace blender
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