Thread synchronization is a fundamental challenge in real-time audio processing.

Efficient Real-Time Synchronization in Audio Processing with std::memory_order_release and std::memory_order_acquire

Thread synchronization is a fundamental challenge in real-time audio processing. While traditional locking mechanisms such as mutexes provide a straightforward approach to managing shared state, they introduce unacceptable overhead in real-time audio threads. Blocking operations, such as memory allocations introduced by the use of a mutex on a high-priority processing thread can lead to priority inversion, latency spikes, and audio dropouts.

One method of addressing C++ thread synchronization in real-time processing involves using std::atomic data structures. Atomics are a lightweight mechanism for data synchronization, however correct usage of memory ordering remains a common point of confusion among software engineers. While the default memory ordering behavior of std::atomic is std::memory_order_seq_cst (sequental consistency), which easiest to understand, it also imposes unnecessary performance costs which can be avoided. More efficient synchronization can be achieved with std::memory_order_release and std::memory_order_acquire, yet many developers are unfamiliar with how these memory orderings work in practice.

This blog post explores:

• Why mutexes are unsuitable for real-time audio.
• How std::memory_order_release and std::memory_order_acquire ensure safe, lock-free synchronization.
• Practical example of applying these concepts to real-time parameter updates in an audio engine.

The Mutex

std::mutex is an excellent stdlib object for guaranteeing thread synchronization between shared data. Used in conjunction with RAII-based containers like std::lock_guard, stdlib offers built-in mechanisms for guaranteeing mutual exclusion. While a mutex is held, no other thread can acquire the mutex until the original holder of the mutex has released its acquisition of the object, guaranteeing that only one thread modifies a resource at a time.

We keep mutexes out of the real-time audio processing thread for a few reasons:

1. Mutexes can block the audio thread when attempting to lock a mutex that is already held by another thread.
2. Unpredictable performance issues can occur as a result of priority inversion if a lower priority thread holds a lock that the real-time processing thread needs
3. Mutexes introduce non-deterministic latency as a result of thread contention and scheduling, which is unacceptable for the strict timing guaranteeings of real-time audio processing.

Atomic Memory Ordering

std::memory_order_acquire/release is a mechanism that allows us to tell the compiler to synchronize reads and writes happening on an atomic object utilizing these flags, while foregoing the overhead of global memory ordering (which is provided to us with the default memory ordering flag std::memory_order_seq_cst).

std::memory_order_seq_cst assumes a sequentially consistent memory ordering. For folks that may not know, threading was introduced to the C++ library via C++11. Before C++11, all C++ applications were assumed to be read from top-to-bottom, assuming a sequentially consistent ordering.

Nowadays, the default behavior of std::memory_order_seq_cst does provide a guaranteed memory order, which will guarantee the same value is read and written by concurrent atomic load and atomic store operations. For the sake of real-time audio processing, which needs to be non-blocking and blazingly fast, we can utilize the std:memory_order_acquire/release mechanism to guarantee concurrent reads and writes produce and consume the same value, which is incredibly important for processing real-time parameter updates which are expected to happen accurately and consistently. Let’s take a look at an example:

A Concise Example

#include <atomic>

// Shared atomic parameter
std::atomic<float> gain {1.f};

// Control thread: Updating the gain value
void updateGain(float newGain) 
{
    gain.store(newGain, std::memory_order_release);
}

// Audio thread: Reading the gain safely
float processAudio() 
{
    return gain.load(std::memory_order_acquire); // Always sees the latest update
}

In the example above, we have a function updateGain(float) which is expected to be called from our user interface. The user interface exists on a different thread than our high-priority real-time processing thread. Our real-time processing thread calls processAudio() which reads the value of our std::atomic<float> gain variable. Because the real-time thread is happening very quickly, it’s likely that gain.load() and gain.store() will be called concurrently. By utilizing std::memory_order_release while calling gain.store(), and std::memory_order_acquire while calling updateGain() from the user interface, our application will guarantee that the value seen by the load() operation is the same value provided to the store() operation. Modern compilers may offer ordering guarantees by way of the default memory ordering flag, but at the added cost of the overhead of the global memory order (all all atomics being synchronized).

It is also worth mentioning that alternate memory ordering options exist such as std::memory_order_relaxed which offers no guarantees of concurrency between atomics reads and writes (only atomicity is guaranteed), std::memory_order_acq_rel which combines acquire and release semantics into a single operation for atomic read-modify-write operations such as variants of std::atomic::fetch() and std::atomic::exchange().

In Closing

By utilizing std::memory_order_release and std::memory_order_acquire, developers can ensure safe, low-latency data synchronization between threads without the unnecessary synchronization overhead of the default memory ordering flag std:memory_order_seq_cst. The std::memory_order_release and std::memory_order_acquire memory orderings allow for efficient one-way data transfer, ensuring that atomic values being read and written concurrently read the same value being stored.

Understanding and applying the right memory ordering strategy can make a significant impact on the performance of our real-time processes. By incorporating the strategy described in this article, developers can improve performance without sacrificing correctness, guaranteeing non-blocking high performance multi-threaded audio processing code.

Additional Links

https://en.cppreference.com/w/cpp/atomic/memory_order https://www.sobyte.net/post/2022-06/cpp-memory-order/ https://leanpub.com/concurrencywithmodernc