tornavis/source/blender/blenlib/BLI_cache_mutex.hh

107 lines
3.2 KiB
C++

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