Adding upstream version 86.0.1.upstream/86.0.1upstream

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

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+# Rayon
+
+[![Rayon crate](https://img.shields.io/crates/v/rayon.svg)](https://crates.io/crates/rayon)
+[![Rayon documentation](https://docs.rs/rayon/badge.svg)](https://docs.rs/rayon)
+![minimum rustc 1.36](https://img.shields.io/badge/rustc-1.36+-red.svg)
+![build status](https://github.com/rayon-rs/rayon/workflows/master/badge.svg)
+[![Join the chat at https://gitter.im/rayon-rs/Lobby](https://badges.gitter.im/rayon-rs/Lobby.svg)](https://gitter.im/rayon-rs/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
+
+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][blog] about Rayon, which gives more background
+and details about how it works, or [this video][video], from the Rust
+Belt Rust conference.) Rayon is
+[available on crates.io](https://crates.io/crates/rayon), and
+[API Documentation is available on docs.rs](https://docs.rs/rayon/).
+
+[blog]: http://smallcultfollowing.com/babysteps/blog/2015/12/18/rayon-data-parallelism-in-rust/
+[video]: https://www.youtube.com/watch?v=gof_OEv71Aw
+
+## 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:
+
+```rust
+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 threadpools] rather than
+using Rayon's default, global threadpool.
+
+[Parallel iterators]: https://docs.rs/rayon/*/rayon/iter/index.html
+[join]: https://docs.rs/rayon/*/rayon/fn.join.html
+[scope]: https://docs.rs/rayon/*/rayon/fn.scope.html
+[custom threadpools]: https://docs.rs/rayon/*/rayon/struct.ThreadPool.html
+
+## 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, 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.
+
+[Rust channel]: https://doc.rust-lang.org/std/sync/mpsc/fn.channel.html
+
+## Using Rayon
+
+[Rayon is available on crates.io](https://crates.io/crates/rayon). The
+recommended way to use it is to add a line into your Cargo.toml such
+as:
+
+```toml
+[dependencies]
+rayon = "1.5"
+```
+
+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](https://docs.rs/rayon/*/rayon/prelude/index.html).  In
+each module where you would like to use the parallel iterator APIs,
+just add:
+
+```rust
+use rayon::prelude::*;
+```
+
+Rayon currently requires `rustc 1.36.0` or greater.
+
+## Contribution
+
+Rayon is an open source project! If you'd like to contribute to Rayon, check out [the list of "help wanted" issues](https://github.com/rayon-rs/rayon/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22). 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](https://github.com/rayon-rs/rayon/wiki/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/Apache2 licensing](https://github.com/rayon-rs/rayon/blob/master/README.md#license).
+
+## 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 nbody simulation. To see the
+effect of using Rayon, press `s` to run sequentially and `p` to run in
+parallel.
+
+```text
+> cd rayon-demo
+> cargo run --release -- nbody visualize
+```
+
+For more information on demos, try:
+
+```text
+> cd rayon-demo
+> cargo run --release -- --help
+```
+
+## Other questions?
+
+See [the Rayon FAQ][faq].
+
+[faq]: https://github.com/rayon-rs/rayon/blob/master/FAQ.md
+
+## License
+
+Rayon is distributed under the terms of both the MIT license and the
+Apache License (Version 2.0). See [LICENSE-APACHE](LICENSE-APACHE) and
+[LICENSE-MIT](LICENSE-MIT) for details. Opening a pull requests is
+assumed to signal agreement with these licensing terms.