rayon README

The project's README from github.com/rayon-rs/rayon. As one markdown file: README.md.

Rayon

Rayon crate Rayon documentation minimum rustc 1.85 build status

Rayon is a data-parallelism library for Rust. It is extremely lightweight and makes it easy to convert a sequential computation into a parallel one. It also guarantees data-race freedom. (You may also enjoy this blog post about Rayon, which gives more background and details about how it works, or this video, from the Rust Belt Rust conference.) Rayon is available on crates.io, and API documentation is available on docs.rs.

Parallel iterators and more

Rayon makes it drop-dead simple to convert sequential iterators into parallel ones: usually, you just change your foo.iter() call into foo.par_iter(), and Rayon does the rest:

use rayon::prelude::*;
fn sum_of_squares(input: &[i32]) -> i32 {
    input.par_iter() // <-- just change that!
         .map(|&i| i * i)
         .sum()
}

Parallel iterators take care of deciding how to divide your data into tasks; it will dynamically adapt for maximum performance. If you need more flexibility than that, Rayon also offers the join and scope functions, which let you create parallel tasks on your own. For even more control, you can create custom thread pools rather than using Rayon's default, global thread pool.

No data races

You may have heard that parallel execution can produce all kinds of crazy bugs. Well, rest easy. Rayon's APIs all guarantee data-race freedom, which generally rules out most parallel bugs (though not all). In other words, if your code compiles, it typically does the same thing it did before.

For the most part, parallel iterators in particular are guaranteed to produce the same results as their sequential counterparts. One caveat: If your iterator has side effects (for example, sending methods to other threads through a Rust channel or writing to disk), those side effects may occur in a different order. Note also that, in some cases, parallel iterators offer alternative versions of the sequential iterator methods that can have higher performance.

Using Rayon

Rayon is available on crates.io. The recommended way to use it is to add a line into your Cargo.toml such as:

[dependencies]
rayon = "1.12"

To use the parallel iterator APIs, a number of traits have to be in scope. The easiest way to bring those things into scope is to use the Rayon prelude. In each module where you would like to use the parallel iterator APIs, just add:

use rayon::prelude::*;

Rayon currently requires rustc 1.85.0 or greater.

Usage with WebAssembly

By default, when building to WebAssembly, Rayon will treat it as any other platform without multithreading support and will fall back to sequential iteration. This allows existing code to compile and run successfully with no changes necessary, but it will run slower as it will only use a single CPU core.

You can build Rayon-based projects with proper multithreading support for the Web, but you'll need an adapter and some project configuration to account for differences between WebAssembly threads and threads on the other platforms.

Check out the wasm-bindgen-rayon docs for more details.

Contribution

Rayon is an open source project! If you'd like to contribute to Rayon, check out the list of "help wanted" issues. These are all (or should be) issues that are suitable for getting started, and they generally include a detailed set of instructions for what to do. Please ask questions if anything is unclear! Also, check out the Guide to Development page on the wiki. Note that all code submitted in PRs to Rayon is assumed to be licensed under Rayon's dual MIT/Apache 2.0 licensing.

Quick demo

To see Rayon in action, check out the rayon-demo directory, which includes a number of demos of code using Rayon. For example, run this command to get a visualization of an N-body simulation. To see the effect of using Rayon, press s to run sequentially and p to run in parallel.

> cd rayon-demo
> cargo run --release -- nbody visualize

For more information on demos, try:

> cd rayon-demo
> cargo run --release -- --help

Other questions?

See the Rayon FAQ.

License

Rayon is distributed under the terms of both the MIT license and the Apache License (Version 2.0). See LICENSE-APACHE and LICENSE-MIT for details. Opening a pull request is assumed to signal agreement with these licensing terms.

rayon (rayon-rs/rayon)

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13.4K ·GitHub
Rayon
What is this?Rayon is a data-parallelism library for Rust. It is extremely lightweight and makes it easy to turn a sequential computation into a parallel one, with data-race freedom guaranteed.
Is it an app I run, or a library I code against?A library: you add it as a dependency to your Rust project and call its APIs from your code. There is nothing standalone to install or run — the crate lives on crates.io and the API docs on docs.rs.
How do I start using it in a project?Add a rayon line to your Cargo.toml, then use the Rayon prelude in each module where you want the parallel iterator APIs so the required traits are in scope.
Do I need anything special installed to use it?Just a recent Rust toolchain: Rayon currently requires rustc 1.85.0 or greater, which any up-to-date stable install covers.
Will the parallel version behave exactly like my sequential code?Mostly yes: data-race freedom is guaranteed and parallel iterators produce the same results as sequential ones. The one caveat: side effects like channel sends or disk writes may happen in a different order.
Can I use it in my own projects for free?Yes — Rayon is distributed under the terms of both the MIT license and the Apache License (Version 2.0).
Is there a quick way to see Rayon in action?Yes — the rayon-demo directory includes several demos, such as a visualization of an N-body simulation. Press s to run it sequentially and p to run it in parallel to compare the difference.
Why pick Rayon over hand-rolling my own threads?That is its whole pitch: parallelizing sequential iterators is described as drop-dead simple, and the APIs guarantee data-race freedom, so code that compiles typically behaves the same as before — without you managing task splitting yourself.
How mature is the project?Rayon has been on GitHub since October 2014 and has around 13,400 stars. The README also links a background blog post, a conference talk, and an FAQ covering other questions.
What are similar projects?conc, taskflow, tokio, perry, bend, compio, muduo, concurrentqueue
Which topics is it in?parallel-computing, parallel, multithreading, concurrency, systems-programming, high-performance, wasm, performance, rust, apache-2.0, library, developer-tools
Creator
rayon-rs
Size
3.6 MB
Stars
13.4K
Updated
CommitAug 28
Age
12y
Commits · 90 Days