Lib.rs

Similar to rayon, rayoff equips iterators with additional functionality for introducing parallelism. However, instead of using a work-stealing stategy to ensure threads don't starve for work, rayoff uses a simpler map-reduce stategy:

1. Divvy up the iterator into chunks of roughly equal size (see here for implementation details).
2. Map each chunk to its own thread.
3. Reduce over the results of each thread's computation.

In almost all cases, rayon is the superior choice. However, if your computations won't benefit from work-stealing, then rayoff may give you better performance. Disclaimer: rayoff requires a nightly compiler (rustc 1.60.0 as of this writing) and internally uses unsafe code. Use at your own risk!

Example

use rayoff::*;

fn check(candidate: &[u8]) -> bool {
    candidate == b"orange8"
}

let wordlist = ["apple", "orange", "pear", "banana"];
let cracked_password = wordlist.divvy_cpus().find_map_any(|&word| {
    let mut buf = [0u8; 8];
    let len = word.len();
    buf[..len].copy_from_slice(word.as_bytes());
    for i in b'0'..=b'9' {
        buf[len] = i;
        let password = &buf[..len + 1];
        if check(password) {
            return Some(password.to_vec());
        }
    }
    None
});

assert_eq!(cracked_password.unwrap(), b"orange8");

License

rayoff is dual-licensed under the MIT and Apache 2.0 licenses (see LICENSE-MIT and LICENSE-APACHE for details).