use std::sync::atomic::{AtomicBool, Ordering}; use crate::parallel::{num_threads, Reduce}; /// Runs `left` and `right` in parallel, returning their output when both are done.pub fn join<O1: Send, O2: Send>(left: impl FnOnce() -> O1 + Send, right: impl FnOnce() -> O2 + Send) -> (O1, O2) { crossbeam_utils::thread::scope(|s| { let left = s.spawn(|_| left()); let right = s.spawn(|_| right()); (left.join().unwrap(), right.join().unwrap()) }) .unwrap()} /// Runs `f` with a scope to be used for spawning threads that will not outlive the function call./// That way it's possible to handle threads without needing the 'static lifetime for data they interact with.////// Note that the threads should not rely on actual parallelism as threading might be turned off entirely, hence should not/// connect each other with channels as deadlock would occur in single-threaded mode.pub fn threads<'env, F, R>(f: F) -> std::thread::Result<R>where F: FnOnce(&crossbeam_utils::thread::Scope<'env>) -> R,{ crossbeam_utils::thread::scope(f)} /// Read items from `input` and `consume` them in multiple threads,/// whose output output is collected by a `reducer`. Its task is to/// aggregate these outputs into the final result returned by this function with the benefit of not having to be thread-safe.////// * if `thread_limit` is `Some`, the given amount of threads will be used. If `None`, all logical cores will be used./// * `new_thread_state(thread_number) -> State` produces thread-local state once per thread to be based to `consume`/// * `consume(Item, &mut State) -> Output` produces an output given an input obtained by `input` along with mutable state initially/// created by `new_thread_state(…)`./// * For `reducer`, see the [`Reduce`] traitpub fn in_parallel<I, S, O, R>( input: impl Iterator<Item = I> + Send, thread_limit: Option<usize>, new_thread_state: impl Fn(usize) -> S + Send + Clone, consume: impl Fn(I, &mut S) -> O + Send + Clone, mut reducer: R,) -> Result<<R as Reduce>::Output, <R as Reduce>::Error>where R: Reduce<Input = O>, I: Send, O: Send,{ let num_threads = num_threads(thread_limit); crossbeam_utils::thread::scope(move |s| { let receive_result = { let (send_input, receive_input) = crossbeam_channel::bounded::<I>(num_threads); let (send_result, receive_result) = crossbeam_channel::bounded::<O>(num_threads); for thread_id in 0..num_threads { s.spawn({ let send_result = send_result.clone(); let receive_input = receive_input.clone(); let new_thread_state = new_thread_state.clone(); let consume = consume.clone(); move |_| { let mut state = new_thread_state(thread_id); for item in receive_input { if send_result.send(consume(item, &mut state)).is_err() { break; } } } }); } s.spawn(move |_| { for item in input { if send_input.send(item).is_err() { break; } } }); receive_result }; for item in receive_result { drop(reducer.feed(item)?); } reducer.finalize() }) .expect("no panic")} /// An experiment to have fine-grained per-item parallelization with built-in aggregation via thread state./// This is only good for operations where near-random access isn't detrimental, so it's not usually great/// for file-io as it won't make use of sorted inputs well./// Note that `periodic` is not guaranteed to be called in case other threads come up first and finish too fast.// TODO: better docspub fn in_parallel_with_slice<I, S, E>( input: &[I], thread_limit: Option<usize>, new_thread_state: impl FnMut(usize) -> S + Send + Clone, consume: impl FnMut(&I, &mut S) -> Result<(), E> + Send + Clone, mut periodic: impl FnMut() -> Option<std::time::Duration> + Send,) -> Result<Vec<S>, E>where I: Send + Sync, E: Send + Sync, S: Send,{ let num_threads = num_threads(thread_limit); let num_items = input.len(); let mut results = Vec::with_capacity(num_threads); let stop_everything = &AtomicBool::default(); crossbeam_utils::thread::scope({ move |s| { s.spawn({ move |_| loop { if stop_everything.load(Ordering::Relaxed) { break; } match periodic() { Some(duration) => std::thread::sleep(duration), None => { stop_everything.store(true, Ordering::Relaxed); break; } } } }); let threads: Vec<_> = (0..num_threads) .map(|thread_id| { s.spawn({ let mut new_thread_state = new_thread_state.clone(); let mut consume = consume.clone(); move |_| { let mut state = new_thread_state(thread_id); for input_index in (thread_id..num_items).step_by(num_threads) { if stop_everything.load(Ordering::Relaxed) { break; } let item = &input[input_index]; if let Err(err) = consume(item, &mut state) { stop_everything.store(true, Ordering::Relaxed); return Err(err); } } Ok(state) } }) }) .collect(); for thread in threads { match thread.join() { Ok(res) => { results.push(res?); } Err(err) => { // a panic happened, stop the world gracefully (even though we panic later) stop_everything.store(true, Ordering::Relaxed); std::panic::resume_unwind(err); } } } stop_everything.store(true, Ordering::Relaxed); Ok(results) } }) .expect("no panic")}
use std::sync::atomic::{AtomicBool, Ordering};
use crate::parallel::{num_threads, Reduce};
/// Runs `left` and `right` in parallel, returning their output when both are done.
pub fn join<O1: Send, O2: Send>(left: impl FnOnce() -> O1 + Send, right: impl FnOnce() -> O2 + Send) -> (O1, O2) {
crossbeam_utils::thread::scope(|s| {
let left = s.spawn(|_| left());
let right = s.spawn(|_| right());
(left.join().unwrap(), right.join().unwrap())
})
.unwrap()
}
/// Runs `f` with a scope to be used for spawning threads that will not outlive the function call.
/// That way it's possible to handle threads without needing the 'static lifetime for data they interact with.
///
/// Note that the threads should not rely on actual parallelism as threading might be turned off entirely, hence should not
/// connect each other with channels as deadlock would occur in single-threaded mode.
pub fn threads<'env, F, R>(f: F) -> std::thread::Result<R>
where
F: FnOnce(&crossbeam_utils::thread::Scope<'env>) -> R,
{
crossbeam_utils::thread::scope(f)
}
/// Read items from `input` and `consume` them in multiple threads,
/// whose output output is collected by a `reducer`. Its task is to
/// aggregate these outputs into the final result returned by this function with the benefit of not having to be thread-safe.
///
/// * if `thread_limit` is `Some`, the given amount of threads will be used. If `None`, all logical cores will be used.
/// * `new_thread_state(thread_number) -> State` produces thread-local state once per thread to be based to `consume`
/// * `consume(Item, &mut State) -> Output` produces an output given an input obtained by `input` along with mutable state initially
/// created by `new_thread_state(…)`.
/// * For `reducer`, see the [`Reduce`] trait
pub fn in_parallel<I, S, O, R>(
input: impl Iterator<Item = I> + Send,
thread_limit: Option<usize>,
new_thread_state: impl Fn(usize) -> S + Send + Clone,
consume: impl Fn(I, &mut S) -> O + Send + Clone,
mut reducer: R,
) -> Result<<R as Reduce>::Output, <R as Reduce>::Error>
where
R: Reduce<Input = O>,
I: Send,
O: Send,
{
let num_threads = num_threads(thread_limit);
crossbeam_utils::thread::scope(move |s| {
let receive_result = {
let (send_input, receive_input) = crossbeam_channel::bounded::<I>(num_threads);
let (send_result, receive_result) = crossbeam_channel::bounded::<O>(num_threads);
for thread_id in 0..num_threads {
s.spawn({
let send_result = send_result.clone();
let receive_input = receive_input.clone();
let new_thread_state = new_thread_state.clone();
let consume = consume.clone();
move |_| {
let mut state = new_thread_state(thread_id);
for item in receive_input {
if send_result.send(consume(item, &mut state)).is_err() {
break;
}
}
}
});
}
s.spawn(move |_| {
for item in input {
if send_input.send(item).is_err() {
break;
}
}
});
receive_result
};
for item in receive_result {
drop(reducer.feed(item)?);
}
reducer.finalize()
})
.expect("no panic")
}
/// An experiment to have fine-grained per-item parallelization with built-in aggregation via thread state.
/// This is only good for operations where near-random access isn't detrimental, so it's not usually great
/// for file-io as it won't make use of sorted inputs well.
/// Note that `periodic` is not guaranteed to be called in case other threads come up first and finish too fast.
// TODO: better docs
pub fn in_parallel_with_slice<I, S, E>(
input: &[I],
thread_limit: Option<usize>,
new_thread_state: impl FnMut(usize) -> S + Send + Clone,
consume: impl FnMut(&I, &mut S) -> Result<(), E> + Send + Clone,
mut periodic: impl FnMut() -> Option<std::time::Duration> + Send,
) -> Result<Vec<S>, E>
where
I: Send + Sync,
E: Send + Sync,
S: Send,
{
let num_threads = num_threads(thread_limit);
let num_items = input.len();
let mut results = Vec::with_capacity(num_threads);
let stop_everything = &AtomicBool::default();
crossbeam_utils::thread::scope({
move |s| {
s.spawn({
move |_| loop {
if stop_everything.load(Ordering::Relaxed) {
break;
}
match periodic() {
Some(duration) => std::thread::sleep(duration),
None => {
stop_everything.store(true, Ordering::Relaxed);
break;
}
}
}
});
let threads: Vec<_> = (0..num_threads)
.map(|thread_id| {
s.spawn({
let mut new_thread_state = new_thread_state.clone();
let mut consume = consume.clone();
move |_| {
let mut state = new_thread_state(thread_id);
for input_index in (thread_id..num_items).step_by(num_threads) {
if stop_everything.load(Ordering::Relaxed) {
break;
}
let item = &input[input_index];
if let Err(err) = consume(item, &mut state) {
stop_everything.store(true, Ordering::Relaxed);
return Err(err);
}
}
Ok(state)
}
})
})
.collect();
for thread in threads {
match thread.join() {
Ok(res) => {
results.push(res?);
}
Err(err) => {
// a panic happened, stop the world gracefully (even though we panic later)
stop_everything.store(true, Ordering::Relaxed);
std::panic::resume_unwind(err);
}
}
}
stop_everything.store(true, Ordering::Relaxed);
Ok(results)
}
})
.expect("no panic")
}