Thread safe asynchronous code

Writing correct asynchronous programs with multiple threads requires care in C++. Here we describe a particular pattern that helps avoid errors, and which will integrate well with the C++ FIDL bindings and component runtime.


Asynchronous runtimes

The async library defines the interface for initiating asynchronous operations on Fuchsia. It defines an opaque async_dispatcher_t type, and associated functions.

There are several implementations of this dispatcher interface. A popular one is async_loop_t and its C++ wrapper async::Loop. Libraries that performs asynchronous work generally should not know what is the concrete implementation. Instead they would call functions over the async_dispatcher_t* interface.

Thread safety

The reader should familiarize themselves with the terminology around thread safety if needed.

A program that upholds thread safety avoids data races: broadly, reading and writing the same data without a defined ordering between those operations (see precise definition of a data race in the C++ standard). These races are a source of errors because they lead to undefined behavior at run-time.

An individual C++ type also has categorizations around thread-safety. Referring common practice interpretations from abseil:

  • A C++ object is thread-safe if concurrent usages does not cause data races.
  • A C++ object is thread-unsafe if any concurrent usage may cause data races.

One may wrap a thread-unsafe type with synchronization primitives e.g. mutexes to make it thread-safe. This is called adding external synchronization. Doing so adds overhead, and not all users will use that type concurrently. Hence it's common for a library to be thread-unsafe by default, and require the user to add synchronization if desired. Such types may have comments like the following:

// This class is thread-unsafe. Methods require external synchronization.
class SomeUnsafeType { /* ... */ };

Achieving thread safety in asynchronous code

Achieving thread safety gets more subtle in asynchronous code due to the presence of callbacks. Consider the following snippet:

// |CsvParser| asynchronously reads from a file, and parses the contents as
// comma separated values.
class CsvParser{
  void Load() {
    reader_.AsyncRead([this] (std::string data) {
      values_ = Parse(data);

  std::vector<std::string> Parse(const std::string& data);

  FileReader reader_;
  std::vector<std::string> values_;

AsyncRead will complete the work in the background, then call the lambda specified as the callback function when the work completes. Because the lambda captures this, it is commonly referred to as an "upcall": the reader_ that is owned by an instance of CsvParser makes a call to the owner.

Let's consider how to avoid races between this callback and the destruction of CsvParser. Adding a mutex in CsvParser won't help, because the mutex would be destroyed if CsvParser is destroyed. One may require that CsvParser must always be reference counted, but that results in an opinionated API and tends to recursively cause everything referenced by CsvParser to also be reference counted.

If we ensure that there is always a defined ordering between the destruction of CsvParser and the invocation of the callback, then the race condition is avoided. On Fuchsia, the callback is typically scheduled on an async_dispatcher_t object. A common pattern is to use a single threaded dispatcher:

  • Use an async::Loop as the dispatcher implementation.
  • Only run one thread to service the loop.
  • Only destroy upcall targets on that thread. For example, destroy the CsvParser within a task posted to that dispatcher.

Since the same thread invokes asynchronous callbacks and destroys the instance, there must be a defined ordering between those operations.

This scenario is common across Fuchsia C++ because FIDL server components are strongly encouraged to be concurrent and asynchronous. See C++ FIDL threading guide for a concrete discussion of this scenario when using FIDL bindings.


More generally, if a dispatcher promises that tasks posted on that dispatcher always run with a defined ordering, it is safe to destroy upcall targets on a dispatcher task, and synchronization with upcalls is guaranteed. Such dispatchers are said to support sequences: sequential execution domains which runs a series of tasks with strict mutual exclusion, but where the underlying execution may hop from one thread to another.

Synchronized driver dispatchers (fdf::Dispatcher created with the FDF_DISPATCHER_OPTION_SYNCHRONIZED option) are an example of sequence supporting dispatchers.

When using dispatchers supporting sequences, a common pattern for ensuring thread safety is to use the object from a single sequence.

Enforce with runtime checks

We provide libraries for enforcing the above common patterns at runtime. In particular, thread-unsafe types may check that an instance is always used from an asynchronous dispatcher that ensures ordering between operations. Here "used from" covers construction, destruction, and calling instance methods. We call this mutual exclusion guarantee. Specifically:

  • If the async_dispatcher_t supports sequences, then code running on tasks posted to that dispatcher are ordered with one another.
  • If the async_dispatcher_t does not support sequences, then code running on tasks posted to that dispatcher are ordered if that dispatcher is only serviced by a single thread, for example, a single-threaded async::Loop.

In short, either the dispatcher supports sequences in which case the object must be used on that sequence, or the code runs on a single dispatcher thread and the object must be used on that thread.

The async library offers a BasicLockable type, async::synchronization_checker. You may call .lock() or lock the checker using a std::lock_guard whenever a function requires mutual exclusion. Doing so checks that the function is called from a dispatcher with such a guarantee, without actually taking any locks. Here is a full example:

// |ChannelReader| lets one asynchronously read from a Zircon channel.
// ## Thread safety
// Instances must be used from an async dispatcher with mutual exclusion
// guarantee. See
class ChannelReader {
  ChannelReader(async_dispatcher_t* dispatcher, zx::channel channel)
      : dispatcher_(dispatcher),
        wait_(channel_.get(), ZX_CHANNEL_READABLE) {}

  ~ChannelReader() {
    // |lock| explicitly checks that the dispatcher is not calling callbacks
    // that use this |ChannelReader| instance in the meantime.

  // Asynchronously wait for the channel to become readable, then read the
  // data into a member variable.
  void AsyncRead() {
    // This guard checks that the |AsyncRead| method is called from a task
    // running on a dispatcher with mutual exclusion guarantee.
    std::lock_guard guard(checker_);


    zx_status_t status = wait_.Begin(
        // The dispatcher that will perform the waiting.

        // The async dispatcher will call this callback when the channel is
        // ready to be read from. Because this callback captures `this`, we
        // must ensure the callback does not race with destroying the
        // |ChannelReader| instance. This is accomplished by calling
        // `checker_.lock()` in the |ChannelReader| destructor.
        [this](async_dispatcher_t* dispatcher, async::WaitBase* wait, zx_status_t status,
               const zx_packet_signal_t* signal) {
          if (status != ZX_OK) {
          std::lock_guard guard(checker_);

          uint32_t actual;
          status =,, nullptr,
                                 static_cast<uint32_t>(data_.capacity()), 0, &actual, nullptr);
          if (status != ZX_OK) {
    ZX_ASSERT(status == ZX_OK);

  std::vector<uint8_t> data() const {
    // Here we also verify synchronization, because we want to avoid race
    // conditions such as the user calling |AsyncRead| which clears the
    // data and calling |data| to get the data at the same time.
    std::lock_guard guard(checker_);

    return data_;

  async_dispatcher_t* dispatcher_;
  async::synchronization_checker checker_;
  zx::channel channel_;
  std::vector<uint8_t> data_ __TA_GUARDED(checker_);
  async::WaitOnce wait_;

zx::channel c1, c2;
ASSERT_EQ(ZX_OK, zx::channel::create(0, &c1, &c2));

async::Loop loop(&kAsyncLoopConfigNeverAttachToThread);
ChannelReader reader{loop.dispatcher(), std::move(c1)};

ASSERT_EQ(, std::vector<uint8_t>{});

const std::vector<uint8_t> kData{1, 2, 3};
ASSERT_EQ(ZX_OK, c2.write(0,, static_cast<uint32_t>(kData.size()), nullptr, 0));

// Using |reader| must be synchronized with dispatching asynchronous operations.
// Here, they are synchronized because we perform these one after the other
// from a single thread.

ASSERT_EQ(, kData);

// The following is disallowed, and would lead to a panic.
// If the dispatcher is running from a different thread, then we cannot
// ensure that |reader| is not used in the meantime.
// std::thread([&] { loop.RunUntilIdle(); }).join();

fidl::Client is another example of types that check for mutual exclusion guarantee at runtime: destroying a fidl::Client on a non-dispatcher thread will lead to a panic.

Discard callbacks during destruction

You may have noticed that for the ChannelReader example above to work, the callback passed to wait_.Begin(...) must be silently discarded, instead of called with some error, if ChannelReader is destroyed. Indeed the documentation on async::WaitOnce mentions that it "automatically cancels the wait when it goes out of scope".

During destruction, some C++ objects would discard the registered callbacks if those have yet to be called. These kind of APIs are said to guarantee at most once delivery. async::Wait and async::Task are examples of such objects. This style works well when the callback references a single receiver that owns the wait/task, i.e. the callback is an upcall. These APIs are typically also thread-unsafe and requires the aforementioned mutual exclusion guarantee.

Other objects will always call the the registered callback exactly once, even during destruction. Those calls would typically provide an error or status indicating cancellation. They are said to guarantee exactly once delivery.

One should consult the corresponding documentation when using an asynchronous API to understand the cancellation semantics.

It is possible to convert an exactly once API into an at most once API by discarding the upcall if the object making the upcalls is already destroyed. closure-queue is a library that implements this idea; destroying a ClosureQueue will discard unexecuted callbacks scheduled on that queue.

Use an object with different mutual exclusion requirements

To maintain the mutual exclusion guarantees, one may manage and use a group of objects on the same sequence (if supported) or single threaded dispatcher. Those objects can synchronously call into one another without breaking the mutual exclusion runtime checks. A special case of this is an application that runs everything on a single async::Loop with a single thread, typically called the main thread.

More complex applications may have multiple sequences or multiple single threaded dispatchers. When individual objects must be used from their corresponding sequence or single threaded dispatcher, a question arises: how does one object call another object if they are associated with different dispatchers?

A time-tested approach is to have the objects send messages between one another, as opposed to synchronously calling their instance methods. Concretely, this could mean that if object A needs to do something to object B, A would post an asynchronous task to B's dispatcher using async::PostTask. The task (usually a lambda function) may then synchronously use B because it is already running under B's mutual exclusion guarantee.

When tasks are posted to a different dispatcher, it's harder to safely discard them when the receiver object goes out of scope. Here are some approaches:

  • One may shutdown the dispatcher before destroying the object, if that dispatcher serves exactly that object. For example, B may own an async::Loop as the last member field. When B destructs, the async::Loop would be destroyed, which silently discards any unexecuted tasks posted to B.
  • One may reference count the objects, and pass a weak pointer to the posted task. The posted task should do nothing if the pointer is expired.

Golang is a popular example that baked this principle into their language design.

Prior arts

Lightweight mechanisms of ensuring a set of tasks execute one after the other, without necessarily starting operating system threads, is a recurring theme: