Data Parallelism - Rust Cookbook (original) (raw)
Rust Cookbook
Parallel Tasks
Mutate the elements of an array in parallel
The example uses the rayon
crate, which is a data parallelism library for Rust.rayon
provides the par_iter_mut method for any parallel iterable data type. This is an iterator-like chain that potentially executes in parallel.
use rayon::prelude::*;
fn main() {
let mut arr = [0, 7, 9, 11];
arr.par_iter_mut().for_each(|p| *p -= 1);
println!("{:?}", arr);
}
Test in parallel if any or all elements of a collection match a given predicate
This example demonstrates using the rayon::any and rayon::all methods, which are parallelized counterparts to std::any and std::all. rayon::any checks in parallel whether any element of the iterator matches the predicate, and returns as soon as one is found. rayon::all checks in parallel whether all elements of the iterator match the predicate, and returns as soon as a non-matching element is found.
use rayon::prelude::*;
fn main() {
let mut vec = vec![2, 4, 6, 8];
assert!(!vec.par_iter().any(|n| (*n % 2) != 0));
assert!(vec.par_iter().all(|n| (*n % 2) == 0));
assert!(!vec.par_iter().any(|n| *n > 8 ));
assert!(vec.par_iter().all(|n| *n <= 8 ));
vec.push(9);
assert!(vec.par_iter().any(|n| (*n % 2) != 0));
assert!(!vec.par_iter().all(|n| (*n % 2) == 0));
assert!(vec.par_iter().any(|n| *n > 8 ));
assert!(!vec.par_iter().all(|n| *n <= 8 ));
}
Search items using given predicate in parallel
This example uses rayon::find_any and par_iter to search a vector in parallel for an element satisfying the predicate in the given closure.
If there are multiple elements satisfying the predicate defined in the closure argument of rayon::find_any, rayon
returns the first one found, not necessarily the first one.
Also note that the argument to the closure is a reference to a reference (&&x
). See the discussion on std::find for additional details.
use rayon::prelude::*;
fn main() {
let v = vec![6, 2, 1, 9, 3, 8, 11];
let f1 = v.par_iter().find_any(|&&x| x == 9);
let f2 = v.par_iter().find_any(|&&x| x % 2 == 0 && x > 6);
let f3 = v.par_iter().find_any(|&&x| x > 8);
assert_eq!(f1, Some(&9));
assert_eq!(f2, Some(&8));
assert!(f3 > Some(&8));
}
Sort a vector in parallel
This example will sort in parallel a vector of Strings.
Allocate a vector of empty Strings. par_iter_mut().for_each
populates random values in parallel. Although multiple optionsexist to sort an enumerable data type, par_sort_unstableis usually faster than stable sorting algorithms.
use rand::{Rng, thread_rng};
use rand::distributions::Alphanumeric;
use rayon::prelude::*;
fn main() {
let mut vec = vec![String::new(); 100_000];
vec.par_iter_mut().for_each(|p| {
let mut rng = thread_rng();
*p = (0..5).map(|_| rng.sample(&Alphanumeric) as char).collect()
});
vec.par_sort_unstable();
}
Map-reduce in parallel
This example uses rayon::filter, rayon::map, and rayon::reduceto calculate the average age of Person
objects whose age is over 30.
rayon::filter returns elements from a collection that satisfy the given predicate. rayon::map performs an operation on every element, creating a new iteration, and rayon::reduce performs an operation given the previous reduction and the current element. Also shows use of rayon::sum, which has the same result as the reduce operation in this example.
use rayon::prelude::*;
struct Person {
age: u32,
}
fn main() {
let v: Vec<Person> = vec![
Person { age: 23 },
Person { age: 19 },
Person { age: 42 },
Person { age: 17 },
Person { age: 17 },
Person { age: 31 },
Person { age: 30 },
];
let num_over_30 = v.par_iter().filter(|&x| x.age > 30).count() as f32;
let sum_over_30 = v.par_iter()
.map(|x| x.age)
.filter(|&x| x > 30)
.reduce(|| 0, |x, y| x + y);
let alt_sum_30: u32 = v.par_iter()
.map(|x| x.age)
.filter(|&x| x > 30)
.sum();
let avg_over_30 = sum_over_30 as f32 / num_over_30;
let alt_avg_over_30 = alt_sum_30 as f32/ num_over_30;
assert!((avg_over_30 - alt_avg_over_30).abs() < std::f32::EPSILON);
println!("The average age of people older than 30 is {}", avg_over_30);
}
Generate jpg thumbnails in parallel
This example generates thumbnails for all .jpg files in the current directory then saves them in a new folder called thumbnails
.
glob::glob_with finds jpeg files in current directory. rayon
resizes images in parallel using par_iter calling DynamicImage::resize.
use error_chain::error_chain;
use std::path::Path;
use std::fs::create_dir_all;
use error_chain::ChainedError;
use glob::{glob_with, MatchOptions};
use image::{FilterType, ImageError};
use rayon::prelude::*;
error_chain! {
foreign_links {
Image(ImageError);
Io(std::io::Error);
Glob(glob::PatternError);
}
}
fn main() -> Result<()> {
let options: MatchOptions = Default::default();
let files: Vec<_> = glob_with("*.jpg", options)?
.filter_map(|x| x.ok())
.collect();
if files.len() == 0 {
error_chain::bail!("No .jpg files found in current directory");
}
let thumb_dir = "thumbnails";
create_dir_all(thumb_dir)?;
println!("Saving {} thumbnails into '{}'...", files.len(), thumb_dir);
let image_failures: Vec<_> = files
.par_iter()
.map(|path| {
make_thumbnail(path, thumb_dir, 300)
.map_err(|e| e.chain_err(|| path.display().to_string()))
})
.filter_map(|x| x.err())
.collect();
image_failures.iter().for_each(|x| println!("{}", x.display_chain()));
println!("{} thumbnails saved successfully", files.len() - image_failures.len());
Ok(())
}
fn make_thumbnail<PA, PB>(original: PA, thumb_dir: PB, longest_edge: u32) -> Result<()>
where
PA: AsRef<Path>,
PB: AsRef<Path>,
{
let img = image::open(original.as_ref())?;
let file_path = thumb_dir.as_ref().join(original);
Ok(img.resize(longest_edge, longest_edge, FilterType::Nearest)
.save(file_path)?)
}