The Synchronization library includes abstractions and primitives for managing tasks across different threads. This library encompasses the following header files:

  • mutex.h
    Provides primitives for managing locks on resources. A mutex is the most important primitive in this library and the building block for most all concurrency utilities.
  • notification.h
    Provides a simple mechanism for notifying threads of events.
  • barrier.h and blocking_counter.h
    Provides synchronization abstractions for cumulative events.

The Abseil base library also includes a number of concurrency-related header files:

  • base/thread_annotations.h
    Provides macros for documenting the locking policy of multi-threaded code, and providing warnings and errors for misuse of such locks.
  • base/call_once.h
    Provides an Abseil version of std::call_once() for invoking a callable object exactly once across all threads.

This document will cover all of the above.

Synchronization Overview

In sequential (i.e. single-threaded) systems, we usually think of events as happening in a specific total order: for any operations A and B, either A happens before B, or B happens before A. In concurrent systems, this is no longer the case: for some pairs of operations it may not be possible to say which one happens earlier (i.e. events are only partially ordered), in which case we say that they happen concurrently. Notice that this definition has nothing to do with whether they “actually” happen simultaneously, but only with whether we can guarantee that they won’t.

Concurrent operations may conflict if they are not used (or designed) properly within a multi-threaded environment, resulting in the following problems:

  • Operations may require write access to shared resources. We call these issues memory access issues.
  • Operations may need to occur in a specific order. We sometimes call these issues synchronization issues (although memory access issues are also synchronization issues).

In either case, lack of control on the shared resources or lack of control on the operation order can lead to race conditions. The purpose of the concurrency abstractions within this library is to address these issues and avoid such race conditions.

Memory Access Issues

Memory access issues are often addressed through a variety of means, including:

  • Making the shared resource private or read-only (for data where this is appropriate)
  • Converting the data access into a “message passing” scheme, to provide copies of the shared information for temporary use rather than direct access to the memory.
  • Locking access to the shared resource, typically for write operations, to prevent more than one user from reading or writing concurrently.
  • Using atomic operations to access to the shared resource, such as those provided by std::atomic. Note that the rules for properly applying atomic operations are quite complicated, which is one of many reasons you should avoid atomics.

Locking access to shared resources is usually addressed through mutually-exclusive locks known as mutexes. Abseil provides its own Mutex class for this purpose; similarly, the C++ standard library provides a std::mutex class for the same purpose. (Reasons why we implement our own Mutex class are discussed in Mutex Design Notes.)

Types that behave correctly regardless of the order, scheduling, or interleaving of their operations are known as thread-safe. In most cases, such types use mutexes and atomic operations underneath the hood to guard access to the object’s internal state.

See Mutexes below for more information.

Synchronization Operations

Synchronization issues other than simple memory access issues are often more complex and require abstractions specifically built to address the underlying problem, (again, often through mutexes and atomic operations, which are quite tricky to implement properly). Synchronization operations are designed to control the order of events in different threads.

Keep in mind that operations on “thread-safe” types aren’t necessarily synchronization operations. When you read a value that another thread wrote, you can’t assume that the write happens before the read; they may happen concurrently.

For example:

foo::counter first, second;

void thread1() {
  first.Add(1);    // (a)
  second.Add(1);   // (b)

void thread2() {
  while (second.value() == 0) {
  CHECK(first.value() == 1);   // ERROR

Even if foo::counter were thread-safe (and you wouldn’t need to worry about data races), you might think that the CHECK() will succeed, because line (a) happens before line (b), and the CHECK() can’t be reached until line (b) has executed. However, unless Add() and value() are also synchronization operations, none of the operations in thread1 need necessarily happen before any of the operations in thread2, and that CHECK() may fail.

Abseil provides several synchronization abstractions. See Synchronization Operations for more information.


The major primitive for use within concurrency tasks is a mutex, which is a mutually exclusive lock that can be used to prevent multiple threads from accessing and/or writing to a shared resource.

absl::Mutex and std::mutex

Abseil provides its own Mutex class, and within Google, we use this class instead of the similar std::mutex. Mutex provides most of the functionality of std::mutex but adds the following additional features:

  • absl::Mutex adds conditional critical sections, an alternative to condition variables. Mutex::Await() and Mutex::LockWhen() allow the client to wait for a condition without needing a condition variable; the client need not write the while-loop, nor need they use Signal(). (See Condition below.)
  • Mutex intrinsically supports deadlock detection (when locks are not acquired in a consistent order). The deadlock detector is enabled by default in most non-opt build modes, and it can detect deadlock risks that even Clang’s Thread Sanitizer misses. (See Deadlock Detection below.)

Additionally, absl::Mutex can act as a reader-writer lock (like std::shared_mutex) with special ReaderLock() and ReaderUnlock() functions. (See Reader-Writer Locks below.)

We’ve found these features to be critically important for maintaining a large and complex code base. We are not necessarily intending to compete with std::mutex itself; if you find the features usable within your code base, consider absl::Mutex and its utilities.

Like std::mutex, Abseil’s Mutex is not re-entrant (also known as non-recursive). As well, it does not provide strict FIFO behaviour or fairness in the short term; to do so would require significant overhead. However, it tends to be approximately fair in the long term.

Mutex Basics

The absl::Mutex class implements a mutually exclusive lock on on some resource, allowing threads which also use the mutex to avoid concurrent access to that resource, which is typically some variable or data structure with associated invariants. For example, a financial transaction system may wish only one writer to access certain data elements at one time. Mutexes are so common that many words have been coined to describe their operation.

Each Mutex has two basic operations: Mutex::Lock() and Mutex::Unlock(). Conceptually, it has just a single bit of abstract state: a boolean indicating it is true (locked) or false (unlocked). When a Mutex is created, this lock is initially false and the mutex is said to be free or unlocked. Lock() blocks the caller until some moment when the mutex is free, and then atomically changes this mutex state from false to true; the mutex is then said to be held or locked by the caller. Unlock() sets this mutex state to false once more.

Calling Lock() is often referred to as locking or acquiring a mutex, while calling Unlock() is referred to as unlocking or releasing a mutex. An action performed by a thread while holding a mutex is said to be performed under the mutex. Data structures manipulated under the mutex, and their invariants, are said to be protected by the mutex.

Clients of Mutex must obey these rules:

  1. Each time a thread acquires a Mutex it must later release it.
  2. A thread may not attempt to release a Mutex unless it holds it.
  3. A thread may not attempt to acquire an exclusive lock on a Mutex it already holds.

Because Lock() acts atomically to change the state of the state of the mutex, we are guaranteed that, if these rules are followed, only one thread may hold a mutex at any given time.

These rules must be followed both to prevent concurrent access to the protected resource and avoid deadlock, in which a thread blocks waiting for a lock to be released. The last rule prevents self-deadlock, when a holder of a mutex attempts to acquire a mutex it already holds. Such mutexes are known as non-recursive (or non-reentrant) mutexes.

These rules are best followed by bracketing regions of code with matching calls to Lock() and Unlock() a mutex in the same procedure. Such sections of code are called critical regions. Much Google C++ code uses the helper class MutexLock, which through RAII automatically acquires a mutex on construction and releases it when the lock goes out of scope.

Mutexes and Invariants

Most mutexes are used to ensure some invariant state can only be changed atomically while the mutex is held. The programmer is required to re-establish the invariant before releasing the mutex; code can then assume the invariant holds whenever acquiring the mutex, even in the face of updates that temporarily invalidate the invariant during the critical section. However, one cannot guarantee the invariant is true in a thread that does not hold the mutex, because the mutex holder may be changing the monitored state at that moment.

For example, suppose Mutex mu protects the invariant that a + b == 0. This code is then legal:

assert(a + b == 0); // invariant assumed to hold
a++;                // invariant temporarily invalidated
b--;                // invariant restored before mu is released

while this code is erroneous:

assert(a + b == 0); // invariant assumed to hold
a++;                // invariant invalidated
mu.Unlock();        // BUG: mutex released while invariant invalid
b--;                // attempt to restore the invariant,
                    // but the damage is already done

The following does not invalidate the invariant, but incorrectly assumes it is true when the lock is not held:

assert(a + b == 0); // correct: invariant assumed to hold
assert(a + b == 0); // BUG: can't assume invariant without lock

The invariant holds only when evaluated on state observed within a single critical section:

assert(a + b == 0);    // correct: invariant assumed to hold
temp = a;              // takes a temporary copy of "a"
assert(temp + b == 0); // BUG: can't assume invariant on state
                       // from two distinct critical sections

The MutexLock Wrapper

Forgetting to acquire and release locks on a Mutex often leads to errors in your code. The Abseil concurrency library includes a MutexLock wrapper class to make acquiring and releasing a Mutex easier. The class uses RAII to acquire the mutex and automatically releases it when the class goes out of scope.


Class Foo {

  Foo::Bar* Baz() {
    MutexLock l(&lock_);
    return bar;

    Mutex lock_;

Conditional Mutex Behavior

An Abseil Mutex can be configured to block threads until a certain condition occurs. Such conditional behavior is accomplished in two ways: a traditional conditional variable CondVar (similar to the std::condition_variable available to std::mutex) or through a mechanism unique to Abseil’s mutex: conditional critical sections, using a Mutex::Condition.

Conditional Critical Sections (using the Condition construction) are generally preferred as use of separate condition variables has proven to be error prone. The Mutex contains a number of member functions (e.g. Mutex::Await()) that are hard to get wrong. Generally, prefer use of Condition; in rare cases, when there are multiple threads waiting on distinctly different conditions, however, a battery of CondVars may be more efficient.

Conditional Critical Sections

Abseil’s Mutex has been extended through the addition of conditional critical sections, an alternative to condition variables. Member functions such as Mutex::Await() and Mutex::LockWhen() use intrinsic Condition predicates to allow a client to wait for a condition without needing a condition variable; the client need not write the while-loop, nor need they use Signal().

Clients can imagine that a mutex contains an imaginary condition variable; with that assumption, these corresponding code fragments on the left and right are equivalent:

Conditional critical sections Condition variables
... // arbitrary code A
mu.Await(Condition(f, arg));

... // arbitrary code B

mu.LockWhen(Condition(f, arg));

... // arbitrary code C
... // arbitrary code A
while (!f(arg)) {;
... // arbitrary code B

while (!f(arg)) {;
... // arbitrary code C

When LockWhen() and Await() are used, the condition must be encapsulated in a function (f in the examples) with a void * argument (or by a lambda). As with condition variables, the condition must be a function of state protected by the mutex. The minor inconvenience of requiring a function is rewarded by eliminating the need for the condition variable and the while-loop, which are now hidden inside the Mutex implementation.

Even better, Mutex::Unlock() will take care of calling Signal or SignalAll() to wake waiters whose conditions are now true; its performance is usually as good as or better than that achieved with a condition variable. Thus, the example of the previous subsection could be written as:

bool f(bool *arg) { return *arg; }

// Waiter
mu.LockWhen(Condition(f, &cond_expr));
// cond_expr now holds

// Waker
// cond_expr now holds

In rare cases, when many threads may be waiting with many different and usually-false conditions, it may be better to use multiple condition variables. In general, we recommend conditional critical sections for simplicity.

The call mu.LockWhen(Condition(f, arg)) is equivalent to mu.Lock(); mu.Await(Condition(f, arg)). Similarly, the call mu.Await(Condition(f, arg)) is equivalent to mu.Unlock(); mu.LockWhen(Condition(f, arg)).

The variants LockWhenWithTimeout() and AwaitWithTimeout() allow a thread to wait either for a condition to become true or for some time to elapse. They each return true iff the condition is true:

if (mu.LockWhenWithTimeout(Condition(f, &cond_expr), 1000 /*ms*/)) {
  // mu held; cond_expr true
} else {
  // mu held; cond_expr false; 1000ms timeout expired

These calls are analogous to cv.WaitWithTimeout().

CondVar Condition Variables

Condition variables serve the same purpose as conditional critical sections; they are a means for blocking a thread until some condition has been satisfied. Usually, conditional critical sections are easier to use, but condition variables may be more familiar to programmers because they are included in the POSIX standard and Java language.

Viewed in isolation, a condition variable allows threads to block and to be woken by other threads. However, condition variables are designed to be used in a specific way; a condition variable interacts with a mutex to make it easy to wait for an arbitrary condition on state protected by the mutex.

Suppose that a thread is to wait for some boolean expression cond_expr to become true, where the state associated with cond_expr is protected by a mutex mu. The programmer would write:

// Waiter
while (!cond_expr) {
// cond_expr now holds

The Wait() call atomically unlocks mu (which the thread must hold), and blocks on the condition variable cv. When another thread signals the condition variable, the thread will reacquire the mu, and go around the mandatory while-loop to recheck cond_expr.

Another thread that makes cond_expr true might execute:

// Waker
// cond_expr now holds

The call to Signal() wakes at least one of the threads waiting on cv. Many threads may be blocked on a condition variable at any given time; if it makes sense to wake more than one such thread SignalAll() can be used. (The SignalAll() functionality is often referred to as broadcast in other implementations.)

A single condition variable can be used by threads waiting for different conditions. However, in this case, SignalAll() must be used when any of the conditions becomes true, because the CondVar implementation cannot otherwise guarantee to wake the correct thread. It can be more efficient to use one condition variable for each different condition; any number of condition variables can be used with a single mutex.

Both Signal() and SignalAll() are efficient if there are no threads to wake. Clients should call Signal() or SignalAll() inside the critical section that makes the condition true.

The call WaitWithTimeout() allows a thread to wait until either a condition is true, or until some time has elapsed. Like Wait(), WaitWithTimeout() always reacquires the mutex before returning.


static const int64 kMSToWait = 1000;  // we'll wait at most 1000ms
int64 ms_left_to_wait = kMSToWait;    // ms to wait at any given time
int64 deadline_ms = GetCurrentTimeMillis() + ms_left_to_wait;
while (!cond_expr && ms_left_to_wait > 0) {
  cv.WaitWithTimeout(&mu, ms_left_to_wait);
  ms_left_to_wait = deadline_ms - GetCurrentTimeMillis();
if (cond_expr) {
  // cond_expr true
} else {
  // cond_expr false; 1000ms timeout expired

Reader-Writer Locks

A reader-writer (shared-exclusive) lock has two locking modes. If the lock is not free, it may be held either in write (a.k.a. exclusive) mode by a single thread, or in read (a.k.a. shared) mode by one or more threads.

It is natural to use a reader-writer lock to protect a resource or data structure that is read often, but modified infrequently. Critical sections that modify the protected state must acquire the lock in write mode, while those that merely read the state may acquire the lock in read mode.

Note: reader-writer locks can reduce lock contention in some situations, but most locks are not contended enough for this to make a difference. When you use shared locks, the onus is on you to ensure that the code in reader critical sections really doesn’t mutate the data (logically or physically), and any mistakes here can lead to subtle race conditions.

Any Mutex can be used as a reader-writer lock. The Lock() call acquires the lock in write mode and must be paired with a call to Unlock(). The ReaderLock() call acquires the lock in read mode and must be paired with a call to ReaderUnlock(). absl::Mutex does not provide operations to convert from a read lock to a write lock or vice versa without first releasing the lock.

Both condition variables and mu.Await() may be used with Mutex read-mode critical sections as well as with write-mode critical sections.

Mutex does not allow readers to starve writers or vice versa. This leads to the slightly surprising effect that a request for a read lock may block even if the lock is already held by a reader. If this could not happen, a waiting writer could be prevented ever from making progress by two or more readers that kept the lock permanently in read mode, without any one holding the lock indefinitely.

Beware that future maintainers may add mutations to “reader” critical sections accidentally, thus introducing errors. For example, self-optimizing data structures such as splay trees or LRU caches may modify the data structure on every read. Even simple data structures may keep track of usage statistics. Therefore, reader locks should be used with care, and their use should be easy for developers to recognize. It can help to forbid modifications using a pointer to a const data structure, though care must be still be exercised because of C++’s mutable keyword.

We recommend using Mutex as a simple mutex initially; introduce reader locks only when you know you have lock contention and you know that writes are infrequent.

Thread Annotations

The major drawbacks of absl::Mutex are drawbacks of any mutex type: you have to remember to lock it before entering a critical section, you have to remember to unlock it when you leave, and you have to avoid deadlock.

To help solve these problems, Abseil provides thread-safety annotations (in base/thread_annotations.h) to specify which variables are guarded by which mutexes, which mutexes should be held when calling which functions, what order mutexes should be acquired in, and so forth. These constraints are then checked at compile time, and although this mechanism is not foolproof, it does catch many common Mutex usage errors. Besides being part of the code documentation, annotations can also be used by the compiler or analysis tools to identify and warn about potential thread safety issues.

Annotation Guidelines

Every data object (whether a global variable in namespace scope or a data member in class scope) which requires protection from a mutex should have an annotation GUARDED_BY indicating which mutex protects it:

int accesses_ GUARDED_BY(mu_); // count of accesses

Every mutex should have a complementary comment indicating which variables and also any non-obvious invariants it protects:

Mutex mu_;       // protects accesses_, list_, count_
                 // invariant: count_ == number of elements in linked-list list_

Whenever a thread can hold two mutexes concurrently, either one (or both) of the mutexes should be annotated with ACQUIRED_BEFORE or ACQUIRED_AFTER to indicate which mutex must be acquired first:

Mutex mu0_ ACQUIRED_BEFORE(mu1_); // protects foo_

If the mutex acquisition order is not consistent, deadlock may result. See Deadlock Detection for utilities within the Concurrency library to detect deadlock.

Each routine should be annotated or have a comment indicating which mutexes must and must not be held on entry. These annotations allow implementors to edit routines without examining their call sites, and allows clients to use routines without reading their bodies.

The annotations EXCLUSIVE_LOCKS_REQUIRED, SHARED_LOCKS_REQUIRED, and LOCKS_EXCLUDED are used to document such information. Since we currently use GCC’s “attributes” to implement annotations, they can only be applied to the function declarations, not the definitions (unless they are inside a class definition).

If a routine acquires mu, we must annotate its declaration with LOCKS_EXCLUDED(mu):

// Function declaration with an annotation
void CountAccesses() LOCKS_EXCLUDED(mu_);

// Function definition
void CountAccesses() {

If a routine expects to be called with mu held, we must annotate it with EXCLUSIVE_LOCKS_REQUIRED(mu) or SHARED_LOCKS_REQUIRED(mu) depending on whether the routine needs a writer or reader lock:

// Function declaration with an annotation
void CountAccessesUnlocked() EXCLUSIVE_LOCKS_REQUIRED(mu_);

// Function definition
void CountAccessesUnlocked() {

Without such annotations/comments, working with mutexes is significantly harder. We strongly recommend their use.


A deadlock (sometimes called a deadly embrace) occurs when an activity attempts to acquire a limited resource that has been exhausted and cannot be replenished unless that activity makes progress.

When considering deadlocks involving only mutexes, each activity is typically represented by a thread, and the resources are mutexes that are exhausted when held, and replenished when released.

The simplest mutex-related deadlock is the self-deadlock:

mu.Lock();      // BUG: deadlock: thread already holds mu

Deadlocks involving two resources, such as a mutex and a bounded-sized thread pool, are easily generated too, but deadlocks involving three or more resources are less common. A two-mutex deadlock results when thread T0 attempts to acquire M1 while holding M0 at the same time that thread T1 attempts to acquire M0 while holding M1; each thread will wait indefinitely for the other.

Deadlock Detection

Fortunately, deadlocks are among the easiest bugs to debug and avoid. Debugging is typically easy because the address space stops exactly where the bug occurs. A stack trace of the threads is usually all that is required to see what the threads are waiting for and what resources they hold.

Additionally, the absl::Mutex API provides additional deadlock detection. Such detection is enabled only when the application is compiled in debug mode and the flag -synch_deadlock_detection is non-zero. When enabled, the API detects two additional types of deadlock cases:

  • Mutexes acquired in an inconsistent order. The deadlock detector maintains an acquired-before graph for mutexes in a process. An error is generated if potential deadlock (a cycle) is detected in that graph.
  • Mutexes which are released by threads which do no hold them.

If -synch_deadlock_detection=1, a message is printed for each lock-order error. If -synch_deadlock_detection=2, the first lock-order error causes the process to abort.

The following calls are not recommended for production code, but are useful when deadlock detection is enabled:

  • Mutex::AssertHeld(): abort with high probability if mu is not held exclusively by the calling thread.
  • Mutex::AssertReaderHeld(): abort with high probability if mu is not held in some mode by the calling thread.
  • Mutex::ForgetDeadlockInfo(): forget ordering information gathered for this mutex. This routine should be used if the ordering of mutexes changes during execution (this is rare).

Note that deadlock detection introduces significant overhead; it should not be enabled in production binaries.

Other Synchronization Operations

Most concurrency issues that are not restricted to memory access issues fall under the broad category of “synchronization” operations. Within a concurrent system, a synchronization operation generally encompasses operations for which a strict ordering must be ensured.

Abseil contains a number of synchronization abstractions:

  • call_once(), which allows a function to be executed exactly once across all threads.
  • A Notification, which allows threads to receive notification of a single occurrence of a single event.
  • A Barrier, which blocks threads until a prespecified threshold of threads utilizes the barrier, at which point the barrier is unblocked.
  • A BlockingCounter, which allows a thread to block for a pre-specified number of actions.


absl::call_once() is a fast implementation of the C++ standard library std::call_once(), for invoking a given function at most once, across all threads. You pass three arguments to call_once(): a once_flag to coordinate and identify unique callers, a function to invoke, and the arguments to invoke with the function.

The first call to call_once() with a particular once_flag argument (that does not throw an exception) will run the passed function with the provided arguments; other calls with the same once_flag argument will not run the function, but will wait for the provided function to finish running (if it is still running).

This mechanism provides a safe, simple, and fast mechanism for one-time initialization in a multi-threaded process:

class MyInitClass {
  absl::once_flag once_;

  MyInitClass* Init() {
    absl::call_once(once_, &MyInitClass::Init, this);
    return ptr_;


A Notification allows threads to receive notification of a single occurrence of a single event. Threads sign up for notification using one of the notification’s WaitForNotification*() member functions. Notification::Notify() is used to notify those waiting threads that the event has occurred, and may be only called once for any given notification.


// Create the notification
Notification notification_;

// Client waits for notification
void Foo() {
  // Do something based on that notification

void Bar() {
  // Do a bunch of stuff that needs to be done before notification


An absl::Barrier blocks threads until a prespecified threshold of threads utilizes the barrier. A thread utilizes the Barrier by calling Block() on the barrier, which will block that thread; no call to Block() will return until the specified number of threads have called it.


Barrier *barrier_ = new Barrier(num_active_threads);

void Foo() {
  if (barrier_->Block()) {
    delete barrier_;  // This thread is responsible for destroying barrier_;
  // Do something now that the Barrier has been reached.


An absl::BlockingCounter blocks all threads for a pre-specified number of actions. Threads call Wait() on a blocking counter to block until the specified number of events occur; worker threads then call DecrementCount() on the counter upon completion of their work. Once the counter’s internal “count” reaches zero, the blocked thread unblocks.


void Foo() {
  BlockingCounter things_to_process(things.size());

void Process(BlockingCounter* things) {
  // Do stuff