Crate rayon

Rayon is a data-parallelism library that makes it easy to convert sequential computations into parallel.

It is lightweight and convenient for introducing parallelism into existing code. It guarantees data-race free executions and takes advantage of parallelism when sensible, based on work-load at runtime.

How to use Rayon

There are two ways to use Rayon:

Basic usage and the Rayon prelude

First, you will need to add rayon to your Cargo.toml.

Next, to use parallel iterators or the other high-level methods, you need to import several traits. Those traits are bundled into the module rayon::prelude. It is recommended that you import all of these traits at once by adding use rayon::prelude::* at the top of each module that uses Rayon methods.

These traits give you access to the par_iter method which provides parallel implementations of many iterative functions such as map, for_each, filter, fold, and more.

Crate Layout

Rayon extends many of the types found in the standard library with parallel iterator implementations. The modules in the rayon crate mirror std itself: so, e.g., the option module in Rayon contains parallel iterators for the Option type, which is found in the option module of std. Similarly, the collections module in Rayon offers parallel iterator types for the collections from std. You will rarely need to access these submodules unless you need to name iterator types explicitly.

Targets without threading

Rayon has limited support for targets without std threading implementations. See the rayon_core documentation for more information about its global fallback.

Other questions?

See the Rayon FAQ.

Modules