Using WebAssembly threads from C, C++ and Rust

Learn how to bring multithreaded applications written in other languages to WebAssembly.

Ingvar Stepanyan
Ingvar Stepanyan

WebAssembly threads support is one of the most important performance additions to WebAssembly. It allows you to either run parts of your code in parallel on separate cores, or the same code over independent parts of the input data, scaling it to as many cores as the user has and significantly reducing the overall execution time.

In this article you will learn how to use WebAssembly threads to bring multithreaded applications written in languages like C, C++, and Rust to the web.

How WebAssembly threads work

WebAssembly threads is not a separate feature, but a combination of several components that allows WebAssembly apps to use traditional multithreading paradigms on the web.

Web Workers

First component is the regular Workers you know and love from JavaScript. WebAssembly threads use the new Worker constructor to create new underlying threads. Each thread loads a JavaScript glue, and then the main thread uses Worker#postMessage method to share the compiled WebAssembly.Module as well as a shared WebAssembly.Memory (see below) with those other threads. This establishes communication and allows all those threads to run the same WebAssembly code on the same shared memory without going through JavaScript again.

Web Workers have been around for over a decade now, are widely supported, and don't require any special flags.


WebAssembly memory is represented by a WebAssembly.Memory object in the JavaScript API. By default WebAssembly.Memory is a wrapper around an ArrayBuffer—a raw byte buffer that can be accessed only by a single thread.

> new WebAssembly.Memory({ initial:1, maximum:10 }).buffer
ArrayBuffer { … }

To support multithreading, WebAssembly.Memory gained a shared variant too. When created with a shared flag via the JavaScript API, or by the WebAssembly binary itself, it becomes a wrapper around a SharedArrayBuffer instead. It's a variation of ArrayBuffer that can be shared with other threads and read or modified simultaneously from either side.

> new WebAssembly.Memory({ initial:1, maximum:10, shared:true }).buffer
SharedArrayBuffer { … }

Unlike postMessage, normally used for communication between main thread and Web Workers, SharedArrayBuffer doesn't require copying data or even waiting for the event loop to send and receive messages. Instead, any changes are seen by all threads nearly instantly, which makes it a much better compilation target for traditional synchronisation primitives.

SharedArrayBuffer has a complicated history. It was initially shipped in several browsers mid-2017, but had to be disabled in the beginning of 2018 due to discovery of Spectre vulnerabilities. The particular reason was that data extraction in Spectre relies on timing attacks—measuring execution time of a particular piece of code. To make this kind of attack harder, browsers reduced precision of standard timing APIs like and However, shared memory, combined with a simple counter loop running in a separate thread is also a very reliable way to get high-precision timing, and it's much harder to mitigate without significantly throttling runtime performance.

Instead, Chrome 68 (mid-2018) re-enabled SharedArrayBuffer again by leveraging Site Isolation—a feature that puts different websites into different processes and makes it much more difficult to use side-channel attacks like Spectre. However, this mitigation was still limited only to Chrome desktop, as Site Isolation is a fairly expensive feature, and couldn't be enabled by default for all sites on low-memory mobile devices nor was it yet implemented by other vendors.

Fast-forward to 2020, Chrome and Firefox both have implementations of Site Isolation, and a standard way for websites to opt-in to the feature with COOP and COEP headers. An opt-in mechanism allows to use Site Isolation even on low-powered devices where enabling it for all the websites would be too expensive. To opt-in, add the following headers to the main document in your server configuration:

Cross-Origin-Embedder-Policy: require-corp
Cross-Origin-Opener-Policy: same-origin

Once you opt-in, you get access to SharedArrayBuffer (including WebAssembly.Memory backed by a SharedArrayBuffer), precise timers, memory measurement and other APIs that require an isolated origin for security reasons. Check out the Making your website "cross-origin isolated" using COOP and COEP for more details.

WebAssembly atomics

While SharedArrayBuffer allows each thread to read and write to the same memory, for correct communication you want to make sure they don't perform conflicting operations at the same time. For example, it's possible for one thread to start reading data from a shared address, while another thread is writing to it, so the first thread will now get a corrupted result. This category of bugs is known as race conditions. In order to prevent race conditions, you need to somehow synchronize those accesses. This is where atomic operations come in.

WebAssembly atomics is an extension to the WebAssembly instruction set that allow to read and write small cells of data (usually 32- and 64-bit integers) "atomically". That is, in a way that guarantees that no two threads are reading or writing to the same cell at the same time, preventing such conflicts at a low level. Additionally, WebAssembly atomics contain two more instruction kinds—"wait" and "notify"—that allow one thread to sleep ("wait") on a given address in a shared memory until another thread wakes it up via "notify".

All the higher-level synchronisation primitives, including channels, mutexes, and read-write locks build upon those instructions.

How to use WebAssembly threads

Feature detection

WebAssembly atomics and SharedArrayBuffer are relatively new features and aren't yet available in all browsers with WebAssembly support. You can find which browsers support new WebAssembly features on the roadmap.

To ensure that all users can load your application, you'll need to implement progressive enhancement by building two different versions of Wasm—one with multithreading support and one without it. Then load the supported version depending on feature detection results. To detect WebAssembly threads support at runtime, use wasm-feature-detect library and load the module like this:

import { threads } from 'wasm-feature-detect';

const hasThreads = await threads();

const module = await (
    ? import('./module-with-threads.js')
    : import('./module-without-threads.js')

// …now use `module` as you normally would

Now let's take a look at how to build a multithreaded version of the WebAssembly module.


In C, particularly on Unix-like systems, the common way to use threads is via POSIX Threads provided by the pthread library. Emscripten provides an API-compatible implementation of the pthread library built atop Web Workers, shared memory and atomics, so that the same code can work on the web without changes.

Let's take a look at an example:


#include <stdio.h>
#include <unistd.h>
#include <pthread.h>

void *thread_callback(void *arg)
    printf("Inside the thread: %d\n", *(int *)arg);
    return NULL;

int main()
    puts("Before the thread");

    pthread_t thread_id;
    int arg = 42;
    pthread_create(&thread_id, NULL, thread_callback, &arg);

    pthread_join(thread_id, NULL);

    puts("After the thread");

    return 0;

Here the headers for the pthread library are included via pthread.h. You can also see a couple of crucial functions for dealing with threads.

pthread_create will create a background thread. It takes a destination to store a thread handle in, some thread creation attributes (here not passing any, so it's just NULL), the callback to be executed in the new thread (here thread_callback), and an optional argument pointer to pass to that callback in case you want to share some data from the main thread—in this example we're sharing a pointer to a variable arg.

pthread_join can be called later at any time to wait for the thread to finish the execution, and get the result returned from the callback. It accepts the earlier assigned thread handle as well as a pointer to store the result. In this case, there aren't any results so the function takes a NULL as an argument.

To compile code using threads with Emscripten, you need to invoke emcc and pass a -pthread parameter, as when compiling the same code with Clang or GCC on other platforms:

emcc -pthread example.c -o example.js

However, when you try to run it in a browser or Node.js, you'll see a warning and then the program will hang:

Before the thread
Tried to spawn a new thread, but the thread pool is exhausted.
This might result in a deadlock unless some threads eventually exit or the code
explicitly breaks out to the event loop.
If you want to increase the pool size, use setting `-s PTHREAD_POOL_SIZE=...`.
If you want to throw an explicit error instead of the risk of deadlocking in those
cases, use setting `-s PTHREAD_POOL_SIZE_STRICT=2`.
[…hangs here…]

What happened? The problem is, most of the time-consuming APIs on the web are asynchronous and rely on the event loop to execute. This limitation is an important distinction compared to traditional environments, where applications normally run I/O in synchronous, blocking manner. Check out the blog post about Using asynchronous web APIs from WebAssembly if you'd like to learn more.

In this case, the code synchronously invokes pthread_create to create a background thread, and follows up by another synchronous call to pthread_join that waits for the background thread to finish execution. However, Web Workers, that are used behind the scenes when this code is compiled with Emscripten, are asynchronous. So what happens is, pthread_create only schedules a new Worker thread to be created on the next event loop run, but then pthread_join immediately blocks the event loop to wait for that Worker, and by doing so prevents it from ever being created. It's a classic example of a deadlock.

One way to solve this problem is to create a pool of Workers ahead of time, before the program has even started. When pthread_create is invoked, it can take a ready-to-use Worker from the pool, run the provided callback on its background thread, and return the Worker back to the pool. All of this can be done synchronously, so there won't be any deadlocks as long as the pool is sufficiently large.

This is exactly what Emscripten allows with the -s PTHREAD_POOL_SIZE=... option. It allows to specify a number of threads—either a fixed number, or a JavaScript expression like navigator.hardwareConcurrency to create as many threads as there are cores on the CPU. The latter option is helpful when your code can scale to an arbitrary number of threads.

In the example above, there is only one thread being created, so instead of reserving all cores it's sufficient to use -s PTHREAD_POOL_SIZE=1:

emcc -pthread -s PTHREAD_POOL_SIZE=1 example.c -o example.js

This time, when you execute it, things work successfully:

Before the thread
Inside the thread: 42
After the thread
Pthread 0x701510 exited.

There is another problem though: see that sleep(1) in the code example? It executes in the thread callback, meaning off the main thread, so it should be fine, right? Well, it isn't.

When pthread_join is called, it has to wait for the thread execution to finish, meaning that if the created thread is performing long-running tasks—in this case, sleeping 1 second—then the main thread will also have to block for the same amount of time till the results are back. When this JS is executed in the browser, it will block the UI thread for 1 second until the thread callback returns. This leads to poor user experience.

There are few solutions to this:

  • pthread_detach
  • Custom Worker and Comlink


First, if you only need to run some tasks off the main thread, but don't need to wait for the results, you can use pthread_detach instead of pthread_join. This will leave the thread callback running in the background. If you're using this option, you can switch off the warning with -s PTHREAD_POOL_SIZE_STRICT=0.


Second, if you're compiling a C application rather than a library, you can use -s PROXY_TO_PTHREAD option, which will offload the main application code to a separate thread in addition to any nested threads created by the application itself. This way, main code can block safely at any time without freezing the UI. Incidentally, when using this option, you don't have to precreate the thread pool either—instead, Emscripten can leverage the main thread for creating new underlying Workers, and then block the helper thread in pthread_join without deadlocking.

Third, if you're working on a library and still need to block, you can create your own Worker, import the Emscripten-generated code and expose it with Comlink to the main thread. Main thread will be able to invoke any exported methods as asynchronous functions, and that way will also avoid blocking the UI.

In a simple application such as the previous example -s PROXY_TO_PTHREAD is the best option:

emcc -pthread -s PROXY_TO_PTHREAD example.c -o example.js


All the same caveats and logic apply in the same way to C++. The only new thing you gain is access to higher-level APIs like std::thread and std::async, which use the previously discussed pthread library under the hood.

So the example above can be rewritten in more idiomatic C++ like this:


#include <iostream>
#include <thread>
#include <chrono>

int main()
    puts("Before the thread");

    int arg = 42;
    std::thread thread([&]() {
        std::cout << "Inside the thread: " << arg << std::endl;


    std::cout << "After the thread" << std::endl;

    return 0;

When compiled and executed with similar parameters, it will behave in the same way as the C example:

emcc -std=c++11 -pthread -s PROXY_TO_PTHREAD example.cpp -o example.js


Before the thread
Inside the thread: 42
Pthread 0xc06190 exited.
After the thread
Proxied main thread 0xa05c18 finished with return code 0. EXIT_RUNTIME=0 set, so
keeping main thread alive for asynchronous event operations.
Pthread 0xa05c18 exited.


Unlike Emscripten, Rust doesn't have a specialized end-to-end web target, but instead provides a generic wasm32-unknown-unknown target for generic WebAssembly output.

If Wasm is intended to be used in a web environment, any interaction with JavaScript APIs is left to external libraries and tooling like wasm-bindgen and wasm-pack. Unfortunately, this means that the standard library is not aware of Web Workers and standard APIs such as std::thread won't work when compiled to WebAssembly.

Luckily, the majority of the ecosystem depends on higher-level libraries to take care of multithreading. At that level it's much easier to abstract away all the platform differences.

In particular, Rayon is the most popular choice for data-parallelism in Rust. It allows you to take method chains on regular iterators and, usually with a single line change, convert them in a way where they'd run in parallel on all available threads instead of sequentially. For example:

pub fn sum_of_squares(numbers: &[i32]) -> i32 {
  .map(|x| x * x)

With this small change, the code will split up the input data, calculate x * x and partial sums in parallel threads, and in the end add up those partial results together.

To accommodate for platforms without working std::thread, Rayon provides hooks that allow to define custom logic for spawning and exiting threads.

wasm-bindgen-rayon taps into those hooks to spawn WebAssembly threads as Web Workers. To use it, you need to add it as a dependency and follow the configuration steps described in the docs. The example above will end up looking like this:

pub use wasm_bindgen_rayon::init_thread_pool;

pub fn sum_of_squares(numbers: &[i32]) -> i32 {
  .map(|x| x * x)

Once done, the generated JavaScript will export an extra initThreadPool function. This function will create a pool of Workers and reuse them throughout the lifetime of the program for any multithreaded operations done by Rayon.

This pool mechanism is similar to the -s PTHREAD_POOL_SIZE=... option in Emscripten explained earlier, and also needs to be initialized before the main code to avoid deadlocks:

import init, { initThreadPool, sum_of_squares } from './pkg/index.js';

// Regular wasm-bindgen initialization.
await init();

// Thread pool initialization with the given number of threads
// (pass `navigator.hardwareConcurrency` if you want to use all cores).
await initThreadPool(navigator.hardwareConcurrency);

// you can invoke any exported functions as you normally would
console.log(sum_of_squares(new Int32Array([1, 2, 3]))); // 14

Note that the same caveats about blocking the main thread apply here too. Even the sum_of_squares example still needs to block the main thread to wait for the partial results from other threads.

It might be a very short wait or a long one, depending on the complexity of iterators and number of available threads, but, to be on the safe side, browser engines actively prevent blocking the main thread altogether and such code will throw an error. Instead, you should create a Worker, import the wasm-bindgen-generated code there, and expose its API with a library like Comlink to the main thread.

Check out the wasm-bindgen-rayon example for an end-to-end demo showing:

Real-world use cases

We actively use WebAssembly threads in for client-side image compression—in particular, for formats like AVIF (C++), JPEG-XL (C++), OxiPNG (Rust) and WebP v2 (C++). Thanks to the multithreading alone, we've seen consistent 1.5x-3x speed-ups (exact ratio differs per codec), and were able to push those numbers even further by combining WebAssembly threads with WebAssembly SIMD!

Google Earth is another notable service that's using WebAssembly threads for its web version.

FFMPEG.WASM is a WebAssembly version of a popular FFmpeg multimedia toolchain that uses WebAssembly threads to efficiently encode videos directly in the browser.

There are many more exciting examples using WebAssembly threads out there. Be sure to check out the demos and bring your own multithreaded applications and libraries to the web!