Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Rayon (Rust Belt Rust)
Search
nikomatsakis
October 28, 2016
Programming
7
1k
Rayon (Rust Belt Rust)
A talk about Rayon from the Rust Belt Rust conference
nikomatsakis
October 28, 2016
Tweet
Share
More Decks by nikomatsakis
See All by nikomatsakis
Hereditary Harrop Formulas (Papers We Love Boston)
nikomatsakis
2
460
Rust: Systems Programming for All!
nikomatsakis
0
170
CppNow 2017
nikomatsakis
0
190
Rust at Mozilla (part of Mozilla Onboarding)
nikomatsakis
0
160
Guaranteeing Memory Safety and Data-Race Freedom in Rust
nikomatsakis
0
220
Other Decks in Programming
See All in Programming
Compose Hot Reload is here, stop re-launching your apps! (Android Makers 2025)
zsmb
1
460
Preact、HooksとSignalsの両立 / Preact: Harmonizing Hooks and Signals
ssssota
1
1.3k
ベクトル検索システムの気持ち
monochromegane
31
9.8k
サービスクラスのありがたみを発見したときの思い出 #phpcon_odawara
77web
4
610
Agentic Applications with Symfony
el_stoffel
2
260
Defying Front-End Inertia: Inertia.js on Rails
skryukov
0
440
List とは何か? / PHPerKaigi 2025
meihei3
0
620
OpenTelemetryを活用したObservability入門 / Introduction to Observability with OpenTelemetry
seike460
PRO
1
420
趣味全開のAITuber開発
kokushin
0
180
プロダクト横断分析に役立つ、事前集計しないサマリーテーブル設計
hanon52_
1
260
MCP調べてみました! / Exploring MCP
uhzz
2
2.2k
Empowering Developers with HTML-Aware ERB Tooling @ RubyKaigi 2025, Matsuyama, Ehime
marcoroth
1
160
Featured
See All Featured
Site-Speed That Sticks
csswizardry
4
470
A Tale of Four Properties
chriscoyier
158
23k
Speed Design
sergeychernyshev
28
880
Making Projects Easy
brettharned
116
6.1k
実際に使うSQLの書き方 徹底解説 / pgcon21j-tutorial
soudai
177
52k
Creating an realtime collaboration tool: Agile Flush - .NET Oxford
marcduiker
29
2k
Why Our Code Smells
bkeepers
PRO
336
57k
Fireside Chat
paigeccino
37
3.4k
Automating Front-end Workflow
addyosmani
1369
200k
Understanding Cognitive Biases in Performance Measurement
bluesmoon
28
1.6k
YesSQL, Process and Tooling at Scale
rocio
172
14k
Designing for humans not robots
tammielis
252
25k
Transcript
Rayon Data Parallelism for Fun and Profit Nicholas Matsakis (nmatsakis
on IRC)
Want to make parallelization easy 2 fn load_images(paths: &[PathBuf]) ->
Vec<Image> { paths.iter() .map(|path| Image::load(path)) .collect() } fn load_images(paths: &[PathBuf]) -> Vec<Image> { paths.par_iter() .map(|path| Image::load(path)) .collect() } For each path… …load an image… …create and return a vector.
Want to make parallelization safe 3 fn load_images(paths: &[PathBuf]) ->
Vec<Image> { let mut pngs = 0; paths.par_iter() .map(|path| { if path.ends_with(“png”) { pngs += 1; } Image::load(path) }) .collect() } Data-race Will not compile
4 http://blog.faraday.io/saved-by-the-compiler-parallelizing-a-loop-with-rust-and-rayon/
5 Parallel Iterators join() threadpool Basically all safe Safe interface
Unsafe impl Unsafe
6 fn load_images(paths: &[PathBuf]) -> Vec<Image> { paths.iter() .map(|path| Image::load(path))
.collect() }
7 fn load_images(paths: &[PathBuf]) -> Vec<Image> { paths.par_iter() .map(|path| Image::load(path))
.collect() }
Not quite that simple… 8 (but almost!) 1. No mutating
shared state (except for atomics, locks). 2. Some combinators are inherently sequential. 3. Some things aren’t implemented yet.
9 fn load_images(paths: &[PathBuf]) -> Vec<Image> { let mut pngs
= 0; paths.par_iter() .map(|path| { if path.ends_with(“png”) { pngs += 1; } Image::load(path) }) .collect() } Data-race Will not compile
10 `c` not shared between iterations! fn increment_all(counts: &mut [u32])
{ for c in counts.iter_mut() { *c += 1; } } fn increment_all(counts: &mut [u32]) { paths.par_iter_mut() .for_each(|c| *c += 1); }
fn load_images(paths: &[PathBuf]) -> Vec<Image> { let pngs = paths.par_iter()
.filter(|p| p.ends_with(“png”)) .map(|_| 1) .sum(); paths.par_iter() .map(|p| Image::load(p)) .collect() } 11
12 But beware: atomics introduce nondeterminism! use std::sync::atomic::{AtomicUsize, Ordering}; fn
load_images(paths: &[PathBuf]) -> Vec<Image> { let pngs = AtomicUsize::new(0); paths.par_iter() .map(|path| { if path.ends_with(“png”) { pngs.fetch_add(1, Ordering::SeqCst); } Image::load(path) }) .collect() }
13 3 2 1 12 0 4 5 1 2
1 3 2 1 0 1 3 4 0 3 6 7 8 vec1 vec2 6 2 6 * sum 8 82 fn dot_product(vec1: &[i32], vec2: &[i32]) -> i32 { vec1.iter() .zip(vec2) .map(|(e1, e2)| e1 * e2) .fold(0, |a, b| a + b) // aka .sum() }
14 fn dot_product(vec1: &[i32], vec2: &[i32]) -> i32 { vec1.par_iter()
.zip(vec2) .map(|(e1, e2)| e1 * e2) .reduce(|| 0, |a, b| a + b) // aka .sum() } 3 2 1 12 0 4 5 1 2 1 3 2 1 0 1 3 4 0 3 6 7 8 vec1 vec2 sum 20 19 43 39 82
15 Parallel iterators: Mostly like normal iterators, but: • closures
cannot mutate shared state • some operations are different For the most part, Rust protects you from surprises.
16 Parallel Iterators join() threadpool
The primitive: join() 17 rayon::join(|| do_something(…), || do_something_else(…)); Meaning: maybe
execute two closures in parallel. Idea: - add `join` wherever parallelism is possible - let the library decide when it is profitable
18 fn load_images(paths: &[PathBuf]) -> Vec<Image> { paths.par_iter() .map(|path| Image::load(path))
.collect() } Image::load(paths[0]) Image::load(paths[1])
Work stealing 19 Cilk: http://supertech.lcs.mit.edu/cilk/ (0..22) Thread A Thread B
(0..15) (15..22) (1..15) (queue) (queue) (0..1) (15..22) (15..18) (18..22) (15..16) (16..18) “stolen” (18..22) “stolen”
20
21 Parallel Iterators join() threadpool Rayon: • Parallelize for fun
and profit • Variety of APIs available • Future directions: • more iterators • integrate SIMD, array ops • integrate persistent trees • factor out threadpool
22 Parallel Iterators join() scope() threadpool
23 the scope `s` task `t1` task `t2` rayon::scope(|s| {
… s.spawn(move |s| { // task t1 }); s.spawn(move |s| { // task t2 }); … });
rayon::scope(|s| { … s.spawn(move |s| { // task t1 s.spawn(move
|s| { // task t2 … }); … }); … }); 24 the scope task t1 task t2
`not_ok` is freed here 25 the scope task t1 let
ok: &[u32]s = &[…]; rayon::scope(|scope| { … let not_ok: &[u32] = &[…]; … scope.spawn(move |scope| { // which variables can t1 use? }); });
26 fn join<A,B>(a: A, b: B) where A: FnOnce() +
Send, B: FnOnce() + Send, { rayon::scope(|scope| { scope.spawn(move |_| a()); scope.spawn(move |_| b()); }); } (Real join avoids heap allocation)
27 struct Tree<T> { value: T, children: Vec<Tree<T>>, } impl<T>
Tree<T> { fn process_all(&mut self) { process_value(&mut self.value); for child in &mut self.children { child.process_all(); } } }
28 impl<T> Tree<T> { fn process_all(&mut self) where T: Send
{ rayon::scope(|scope| { for child in &mut self.children { scope.spawn(move |_| child.process_all()); } process_value(&mut self.value); }); } }
29 impl<T> Tree<T> { fn process_all(&mut self) where T: Send
{ rayon::scope(|scope| { let children = &mut self.children; scope.spawn(move |scope| { for child in &mut children { scope.spawn(move |_| child.process_all()); } }); process_value(&mut self.value); }); } }
30 impl<T: Send> Tree<T> { fn process_all(&mut self) { rayon::scope(|s|
self.process_in(s)); } fn process_in<‘s>(&’s mut self, scope: &Scope<‘s>) { let children = &mut self.children; scope.spawn(move |scope| { for child in &mut children { scope.spawn(move |scope| child.process_in(scope)); } }); process_value(&mut self.value); } }