Accessing Vector elements gives me an error Rust - rust

I trying to write a program that will find the median of any given list.
Eventually, In the FINAL FINAL stretch, an error was shot into my face.
I tried to access elements of a Vector through a variable.
Take a look at the calc_med() function.
use std::io;
use std::sync::Mutex;
#[macro_use]
extern crate lazy_static;
lazy_static! {
static ref num_list: Mutex<Vec<f64>> = Mutex::new(Vec::new());
}
fn main() {
loop {
println!("Enter: ");
let mut inp: String = String::new();
io::stdin().read_line(&mut inp).expect("Failure");
let upd_inp: f64 = match inp.trim().parse() {
Ok(num) => num,
Err(_) => {
if inp.trim() == String::from("q") {
break;
} else if inp.trim() == String::from("d") {
break {
println!("Done!");
calc_med();
};
} else {
continue;
}
}
};
num_list.lock().unwrap().push(upd_inp);
num_list
.lock()
.unwrap()
.sort_by(|a, b| a.partial_cmp(b).unwrap());
println!("{:?}", num_list.lock().unwrap());
}
}
fn calc_med() {
// FOR THE ATTENTION OF STACKOVERFLOW
let n: f64 = ((num_list.lock().unwrap().len()) as f64 + 1.0) / 2.0;
if n.fract() == 0.0 {
let n2: usize = n as usize;
} else {
let n3: u64 = n.round() as u64;
let n4: usize = n3 as usize;
let median: f64 = (num_list[n4] + num_list[n4 - 1]) / 2;
println!("{}", median);
}
}
The error is as following:
Compiling FindTheMedian v0.1.0 (/home/isaak/Documents/Code/Rusty/FindTheMedian)
error[E0608]: cannot index into a value of type `num_list`
--> src/main.rs:50:28
|
50 | let median: f64 = (num_list[n4] + num_list[n4 - 1]) / 2;
| ^^^^^^^^^^^^
error[E0608]: cannot index into a value of type `num_list`
--> src/main.rs:50:43
|
50 | let median: f64 = (num_list[n4] + num_list[n4 - 1]) / 2;
| ^^^^^^^^^^^^^^^^

The current code is trying to index a variable of type Mutex<Vec<f64>>, which is not valid. The way you access the underlying data in a mutex is by calling .lock() on it, which will in turn return a structure that resembles Result<Vec<f64>, Error>.
So, fixing only the line would look like this:
let num_list_vec = num_list.lock().unwrap();
let median: f64 = (num_list_vec[n4] + num_list_vec[n4 - 1]) / 2;
However, since you already locked at the start of the function this will not work, since the mutex is already locked. The best way then is to do the locking + unwraping at the start of the function and use the underlying value in all places:
fn calc_med() {
let num_list_vec = num_list.lock().unwrap();
let n: f64 = ((num_list_vec.len()) as f64 + 1.0) / 2.0;
if n.fract() == 0.0 {
let n2: usize = n as usize;
} else {
let n3: u64 = n.round() as u64;
let n4: usize = n3 as usize;
let median: f64 = (num_list_vec[n4] + num_list_vec[n4 - 1]) / 2;
println!("{}", median);
}
}
Edit: Checking your main, I see you are also lock().unwrap()ing in sequence a lot, which is not the way Mutex should be used. Mutex is mainly used whenever you have a need for multi-threaded programming, so that different threads cannot access the same variable twice. It also incurs a performance hit, so you shouldn't really use it in single-threaded scenarios most of the time.
Unless there's a bigger picture we're missing, you should just define your Vec in main and pass it to calc_med as an argument. If the reason you did what you did was to get it as a global, there are other ways to do that in Rust without performance hits, but due to safe design of Rust these ways are not encouraged and should only be used if you know 100% what you want.

Your error is the num_list is not an vector, it's a mutex with an vector inside of it. To access the value inside of a mutex, you must lock it, and then unwrap the result. You do this correctly in main.
To avoid continually unlocking and locking, it is generally best practice to lock the mutex once, at the start of the function. Rust will automatically drop the lock when the reference goes out of scope. See the updated example:
fn calc_med() { // FOR THE ATTENTION OF STACKOVERFLOW
let nums = num_list.lock().unwrap();
let n: f64 = (nums.len() as f64 + 1.0) / 2.0;
if n.fract() == 0.0 {
let n2: usize = n as usize;
} else {
let n3: u64 = n.round() as u64;
let n4: usize = n3 as usize;
let median: f64 = (nums[n4] + nums[n4 - 1]) / 2;
println!("{}", median);
}
}

Related

How to create threads that last entire duration of program and pass immutable chunks for threads to operate on?

I have a bunch of math that has real time constraints. My main loop will just call this function repeatedly and it will always store results into an existing buffer. However, I want to be able to spawn the threads at init time and then allow the threads to run and do their work and then wait for more data. The synchronization I will use a Barrier and have that part working. What I can't get working and have tried various iterations of Arc or crossbeam is splitting the thread spawning up and the actual workload. This is what I have now.
pub const WORK_SIZE: usize = 524_288;
pub const NUM_THREADS: usize = 6;
pub const NUM_TASKS_PER_THREAD: usize = WORK_SIZE / NUM_THREADS;
fn main() {
let mut work: Vec<f64> = Vec::with_capacity(WORK_SIZE);
for i in 0..WORK_SIZE {
work.push(i as f64);
}
crossbeam::scope(|scope| {
let threads: Vec<_> = work
.chunks(NUM_TASKS_PER_THREAD)
.map(|chunk| scope.spawn(move |_| chunk.iter().cloned().sum::<f64>()))
.collect();
let threaded_time = std::time::Instant::now();
let thread_sum: f64 = threads.into_iter().map(|t| t.join().unwrap()).sum();
let threaded_micros = threaded_time.elapsed().as_micros() as f64;
println!("threaded took: {:#?}", threaded_micros);
let serial_time = std::time::Instant::now();
let no_thread_sum: f64 = work.iter().cloned().sum();
let serial_micros = serial_time.elapsed().as_micros() as f64;
println!("serial took: {:#?}", serial_micros);
assert_eq!(thread_sum, no_thread_sum);
println!(
"Threaded performace was {:?}",
serial_micros / threaded_micros
);
})
.unwrap();
}
But I can't find a way to spin these threads up in an init function and then in a do_work function pass work into them. I attempted to do something like this with Arc's and Mutex's but couldn't get everything straight there either. What I want to turn this into is something like the following
use std::sync::{Arc, Barrier, Mutex};
use std::{slice::Chunks, thread::JoinHandle};
pub const WORK_SIZE: usize = 524_288;
pub const NUM_THREADS: usize = 6;
pub const NUM_TASKS_PER_THREAD: usize = WORK_SIZE / NUM_THREADS;
//simplified version of what actual work that code base will do
fn do_work(data: &[f64], result: Arc<Mutex<f64>>, barrier: Arc<Barrier>) {
loop {
barrier.wait();
let sum = data.into_iter().cloned().sum::<f64>();
let mut result = *result.lock().unwrap();
result += sum;
}
}
fn init(
mut data: Chunks<'_, f64>,
result: &Arc<Mutex<f64>>,
barrier: &Arc<Barrier>,
) -> Vec<std::thread::JoinHandle<()>> {
let mut handles = Vec::with_capacity(NUM_THREADS);
//spawn threads, in actual code these would be stored in a lib crate struct
for i in 0..NUM_THREADS {
let result = result.clone();
let barrier = barrier.clone();
let chunk = data.nth(i).unwrap();
handles.push(std::thread::spawn(|| {
//Pass the particular thread the particular chunk it will operate on.
do_work(chunk, result, barrier);
}));
}
handles
}
fn main() {
let mut work: Vec<f64> = Vec::with_capacity(WORK_SIZE);
let mut result = Arc::new(Mutex::new(0.0));
for i in 0..WORK_SIZE {
work.push(i as f64);
}
let work_barrier = Arc::new(Barrier::new(NUM_THREADS + 1));
let threads = init(work.chunks(NUM_TASKS_PER_THREAD), &result, &work_barrier);
loop {
work_barrier.wait();
//actual code base would do something with summation stored in result.
println!("{:?}", result.lock().unwrap());
}
}
I hope this expresses the intent clearly enough of what I need to do. The issue with this specific implementation is that the chunks don't seem to live long enough and when I tried wrapping them in an Arc as it just moved the argument doesn't live long enough to the Arc::new(data.chunk(_)) line.
use std::sync::{Arc, Barrier, Mutex};
use std::thread;
pub const WORK_SIZE: usize = 524_288;
pub const NUM_THREADS: usize = 6;
pub const NUM_TASKS_PER_THREAD: usize = WORK_SIZE / NUM_THREADS;
//simplified version of what actual work that code base will do
fn do_work(data: &[f64], result: Arc<Mutex<f64>>, barrier: Arc<Barrier>) {
loop {
barrier.wait();
let sum = data.iter().sum::<f64>();
*result.lock().unwrap() += sum;
}
}
fn init(
work: Vec<f64>,
result: Arc<Mutex<f64>>,
barrier: Arc<Barrier>,
) -> Vec<thread::JoinHandle<()>> {
let mut handles = Vec::with_capacity(NUM_THREADS);
//spawn threads, in actual code these would be stored in a lib crate struct
for i in 0..NUM_THREADS {
let slice = work[i * NUM_TASKS_PER_THREAD..(i + 1) * NUM_TASKS_PER_THREAD].to_owned();
let result = Arc::clone(&result);
let w = Arc::clone(&barrier);
handles.push(thread::spawn(move || {
do_work(&slice, result, w);
}));
}
handles
}
fn main() {
let mut work: Vec<f64> = Vec::with_capacity(WORK_SIZE);
let result = Arc::new(Mutex::new(0.0));
for i in 0..WORK_SIZE {
work.push(i as f64);
}
let work_barrier = Arc::new(Barrier::new(NUM_THREADS + 1));
let _threads = init(work, Arc::clone(&result), Arc::clone(&work_barrier));
loop {
thread::sleep(std::time::Duration::from_secs(3));
work_barrier.wait();
//actual code base would do something with summation stored in result.
println!("{:?}", result.lock().unwrap());
}
}

Sharing arrays between threads in Rust

I'm new to Rust and I'm struggling with some ownership semantics.
The goal is to do some nonsense measurements on multiplying 2 f64 arrays and writing the result in a third array.
In the single-threaded version, a single thread takes care of the whole range. In the multi-threaded version, each thread takes care of a segment of the range.
The single-threaded version is easy, but my problem is with the multithreaded version where I'm struggling with the ownership rules.
I was thinking to use raw pointers, to bypass the borrow checker. But I'm still not able to make it pass.
#![feature(box_syntax)]
use std::time::SystemTime;
use rand::Rng;
use std::thread;
fn main() {
let nCells = 1_000_000;
let concurrency = 1;
let mut one = box [0f64; 1_000_000];
let mut two = box [0f64; 1_000_000];
let mut res = box [0f64; 1_000_000];
println!("Creating data");
let mut rng = rand::thread_rng();
for i in 0..nCells {
one[i] = rng.gen::<f64>();
two[i] = rng.gen::<f64>();
res[i] = 0 as f64;
}
println!("Finished creating data");
let rounds = 100000;
let start = SystemTime::now();
let one_raw = Box::into_raw(one);
let two_raw = Box::into_raw(two);
let res_raw = Box::into_raw(res);
let mut handlers = Vec::new();
for _ in 0..rounds {
let sizePerJob = nCells / concurrency;
for j in 0..concurrency {
let from = j * sizePerJob;
let to = (j + 1) * sizePerJob;
handlers.push(thread::spawn(|| {
unsafe {
unsafe {
processData(one_raw, two_raw, res_raw, from, to);
}
}
}));
}
for j in 0..concurrency {
handlers.get_mut(j).unwrap().join();
}
handlers.clear();
}
let durationUs = SystemTime::now().duration_since(start).unwrap().as_micros();
let durationPerRound = durationUs / rounds;
println!("duration per round {} us", durationPerRound);
}
// Make sure we can find the function in the generated Assembly
#[inline(never)]
pub fn processData(one: *const [f64;1000000],
two: *const [f64;1000000],
res: *mut [f64;1000000],
from: usize,
to: usize) {
unsafe {
for i in from..to {
(*res)[i] = (*one)[i] * (*two)[i];
}
}
}
This is the error I'm getting
error[E0277]: `*mut [f64; 1000000]` cannot be shared between threads safely
--> src/main.rs:38:27
|
38 | handlers.push(thread::spawn(|| {
| ^^^^^^^^^^^^^ `*mut [f64; 1000000]` cannot be shared between threads safely
|
= help: the trait `Sync` is not implemented for `*mut [f64; 1000000]`
= note: required because of the requirements on the impl of `Send` for `&*mut [f64; 1000000]`
note: required because it's used within this closure
--> src/main.rs:38:41
|
38 | handlers.push(thread::spawn(|| {
| ^^
note: required by a bound in `spawn`
--> /home/pveentjer/.rustup/toolchains/nightly-x86_64-unknown-linux-gnu/lib/rustlib/src/rust/library/std/src/thread/mod.rs:653:8
|
653 | F: Send + 'static,
| ^^^^ required by this bound in `spawn`
[edit] I know that spawning threads is very expensive. I'll convert this to a pool of worker threads that can be recycled once this code is up and running.
You can use chunks_mut or split_at_mut to get non-overlapping slices of one two and res. You can then access different slices from different threads safely. See: documentation for chunks_mut and documentation for split_at_mut
I was able to compile it using scoped threads and chunks_mut. I have removed all the unsafe stuff because there is no need. See the code:
#![feature(box_syntax)]
#![feature(scoped_threads)]
use rand::Rng;
use std::thread;
use std::time::SystemTime;
fn main() {
let nCells = 1_000_000;
let concurrency = 2;
let mut one = box [0f64; 1_000_000];
let mut two = box [0f64; 1_000_000];
let mut res = box [0f64; 1_000_000];
println!("Creating data");
let mut rng = rand::thread_rng();
for i in 0..nCells {
one[i] = rng.gen::<f64>();
two[i] = rng.gen::<f64>();
res[i] = 0 as f64;
}
println!("Finished creating data");
let rounds = 1000;
let start = SystemTime::now();
for _ in 0..rounds {
let size_per_job = nCells / concurrency;
thread::scope(|s| {
for it in one
.chunks_mut(size_per_job)
.zip(two.chunks_mut(size_per_job))
.zip(res.chunks_mut(size_per_job))
{
let ((one, two), res) = it;
s.spawn(|| {
processData(one, two, res);
});
}
});
}
let durationUs = SystemTime::now().duration_since(start).unwrap().as_micros();
let durationPerRound = durationUs / rounds;
println!("duration per round {} us", durationPerRound);
}
// Make sure we can find the function in the generated Assembly
#[inline(never)]
pub fn processData(one: &[f64], two: &[f64], res: &mut [f64]) {
for i in 0..one.len() {
res[i] = one[i] * two[i];
}
}

How to give each CPU core mutable access to a portion of a Vec? [duplicate]

This question already has an answer here:
How do I pass disjoint slices from a vector to different threads?
(1 answer)
Closed 4 years ago.
I've got an embarrassingly parallel bit of graphics rendering code that I would like to run across my CPU cores. I've coded up a test case (the function computed is nonsense) to explore how I might parallelize it. I'd like to code this using std Rust in order to learn about using std::thread. But, I don't understand how to give each thread a portion of the framebuffer. I'll put the full testcase code below, but I'll try to break it down first.
The sequential form is super simple:
let mut buffer0 = vec![vec![0i32; WIDTH]; HEIGHT];
for j in 0..HEIGHT {
for i in 0..WIDTH {
buffer0[j][i] = compute(i as i32,j as i32);
}
}
I thought that it would help to make a buffer that was the same size, but re-arranged to be 3D & indexed by core first. This is the same computation, just a reordering of the data to show the workings.
let mut buffer1 = vec![vec![vec![0i32; WIDTH]; y_per_core]; num_logical_cores];
for c in 0..num_logical_cores {
for y in 0..y_per_core {
let j = y*num_logical_cores + c;
if j >= HEIGHT {
break;
}
for i in 0..WIDTH {
buffer1[c][y][i] = compute(i as i32,j as i32)
}
}
}
But, when I try to put the inner part of the code in a closure & create a thread, I get errors about the buffer & lifetimes. I basically don't understand what to do & could use some guidance. I want per_core_buffer to just temporarily refer to the data in buffer2 that belongs to that core & allow it to be written, synchronize all the threads & then read buffer2 afterwards. Is this possible?
let mut buffer2 = vec![vec![vec![0i32; WIDTH]; y_per_core]; num_logical_cores];
let mut handles = Vec::new();
for c in 0..num_logical_cores {
let per_core_buffer = &mut buffer2[c]; // <<< lifetime error
let handle = thread::spawn(move || {
for y in 0..y_per_core {
let j = y*num_logical_cores + c;
if j >= HEIGHT {
break;
}
for i in 0..WIDTH {
per_core_buffer[y][i] = compute(i as i32,j as i32)
}
}
});
handles.push(handle)
}
for handle in handles {
handle.join().unwrap();
}
The error is this & I don't understand:
error[E0597]: `buffer2` does not live long enough
--> src/main.rs:50:36
|
50 | let per_core_buffer = &mut buffer2[c]; // <<< lifetime error
| ^^^^^^^ borrowed value does not live long enough
...
88 | }
| - borrowed value only lives until here
|
= note: borrowed value must be valid for the static lifetime...
The full testcase is:
extern crate num_cpus;
use std::time::Instant;
use std::thread;
fn compute(x: i32, y: i32) -> i32 {
(x*y) % (x+y+10000)
}
fn main() {
let num_logical_cores = num_cpus::get();
const WIDTH: usize = 40000;
const HEIGHT: usize = 10000;
let y_per_core = HEIGHT/num_logical_cores + 1;
// ------------------------------------------------------------
// Serial Calculation...
let mut buffer0 = vec![vec![0i32; WIDTH]; HEIGHT];
let start0 = Instant::now();
for j in 0..HEIGHT {
for i in 0..WIDTH {
buffer0[j][i] = compute(i as i32,j as i32);
}
}
let dur0 = start0.elapsed();
// ------------------------------------------------------------
// On the way to Parallel Calculation...
// Reorder the data buffer to be 3D with one 2D region per core.
let mut buffer1 = vec![vec![vec![0i32; WIDTH]; y_per_core]; num_logical_cores];
let start1 = Instant::now();
for c in 0..num_logical_cores {
for y in 0..y_per_core {
let j = y*num_logical_cores + c;
if j >= HEIGHT {
break;
}
for i in 0..WIDTH {
buffer1[c][y][i] = compute(i as i32,j as i32)
}
}
}
let dur1 = start1.elapsed();
// ------------------------------------------------------------
// Actual Parallel Calculation...
let mut buffer2 = vec![vec![vec![0i32; WIDTH]; y_per_core]; num_logical_cores];
let mut handles = Vec::new();
let start2 = Instant::now();
for c in 0..num_logical_cores {
let per_core_buffer = &mut buffer2[c]; // <<< lifetime error
let handle = thread::spawn(move || {
for y in 0..y_per_core {
let j = y*num_logical_cores + c;
if j >= HEIGHT {
break;
}
for i in 0..WIDTH {
per_core_buffer[y][i] = compute(i as i32,j as i32)
}
}
});
handles.push(handle)
}
for handle in handles {
handle.join().unwrap();
}
let dur2 = start2.elapsed();
println!("Runtime: Serial={0:.3}ms, AlmostParallel={1:.3}ms, Parallel={2:.3}ms",
1000.*dur0.as_secs() as f64 + 1e-6*(dur0.subsec_nanos() as f64),
1000.*dur1.as_secs() as f64 + 1e-6*(dur1.subsec_nanos() as f64),
1000.*dur2.as_secs() as f64 + 1e-6*(dur2.subsec_nanos() as f64));
// Sanity check
for j in 0..HEIGHT {
let c = j % num_logical_cores;
let y = j / num_logical_cores;
for i in 0..WIDTH {
if buffer0[j][i] != buffer1[c][y][i] {
println!("wtf1? {0} {1} {2} {3}",i,j,buffer0[j][i],buffer1[c][y][i])
}
if buffer0[j][i] != buffer2[c][y][i] {
println!("wtf2? {0} {1} {2} {3}",i,j,buffer0[j][i],buffer2[c][y][i])
}
}
}
}
Thanks to #Shepmaster for the pointers and clarification that this is not an easy problem for Rust, and that I needed to consider crates to find a reasonable solution. I'm only just starting out in Rust, so this really wasn't clear to me.
I liked the ability to control the number of threads that scoped_threadpool gives, so I went with that. Translating my code from above directly, I tried to use the 4D buffer with core as the most-significant-index and that ran into troubles because that 3D vector does not implement the Copy trait. The fact that it implements Copy makes me concerned about performance, but I went back to the original problem and implemented it more directly & found a reasonable speedup by making each row a thread. Copying each row will not be a large memory overhead.
The code that works for me is:
let mut buffer2 = vec![vec![0i32; WIDTH]; HEIGHT];
let mut pool = Pool::new(num_logical_cores as u32);
pool.scoped(|scope| {
let mut y = 0;
for e in &mut buffer2 {
scope.execute(move || {
for x in 0..WIDTH {
(*e)[x] = compute(x as i32,y as i32);
}
});
y += 1;
}
});
On a 6 core, 12 thread i7-8700K for 400000x4000 testcase this runs in 3.2 seconds serially & 481ms in parallel--a reasonable speedup.
EDIT: I continued to think about this issue and got a suggestion from Rustlang on twitter that I should consider rayon. I converted my code to rayon and got similar speedup with the following code.
let mut buffer2 = vec![vec![0i32; WIDTH]; HEIGHT];
buffer2
.par_iter_mut()
.enumerate()
.map(|(y,e): (usize, &mut Vec<i32>)| {
for x in 0..WIDTH {
(*e)[x] = compute(x as i32,y as i32);
}
})
.collect::<Vec<_>>();

Can I reset a borrow of a local in a loop?

I have a processing loop that needs a pointer to a large lookup table.
The pointer is unfortunately triply indirected from the source data, so keeping that pointer around for the inner loop is essential for performance.
Is there any way I can tell the borrow checker that I'm "unborrowing" the state variable in the unlikely event I need to modify the state... so I can only re-lookup the slice in the event that the modify_state function triggers?
One solution I thought of was to change data to be a slice reference and do a mem::replace on the struct at the beginning of the function and pull the slice into local scope, then replace it back at the end of the function — but that is very brittle and error prone (as I need to remember to replace the item on every return). Is there another way to accomplish this?
struct DoubleIndirect {
data: [u8; 512 * 512],
lut: [usize; 16384],
lut_index: usize,
}
#[cold]
fn modify_state(s: &mut DoubleIndirect) {
s.lut_index += 63;
s.lut_index %= 16384;
}
fn process(state: &mut DoubleIndirect) -> [u8; 65536] {
let mut ret: [u8; 65536] = [0; 65536];
let mut count = 0;
let mut data_slice = &state.data[state.lut[state.lut_index]..];
for ret_item in ret.iter_mut() {
*ret_item = data_slice[count];
if count % 197 == 196 {
data_slice = &[];
modify_state(state);
data_slice = &state.data[state.lut[state.lut_index]..];
}
count += 1
}
return ret;
}
The simplest way to do this is to ensure the borrows of state are all disjoint:
#[cold]
fn modify_state(lut_index: &mut usize) {
*lut_index += 63;
*lut_index %= 16384;
}
fn process(state: &mut DoubleIndirect) -> [u8; 65536] {
let mut ret: [u8; 65536] = [0; 65536];
let mut count = 0;
let mut lut_index = &mut state.lut_index;
let mut data_slice = &state.data[state.lut[*lut_index]..];
for ret_item in ret.iter_mut() {
*ret_item = data_slice[count];
if count % 197 == 196 {
modify_state(lut_index);
data_slice = &state.data[state.lut[*lut_index]..];
}
count += 1
}
return ret;
}
The problem is basically two things: first, Rust will not look beyond a function's signature to find out what it does. As far as the compiler knows, your call to modify_state could be changing state.data as well, and it can't allow that.
The second problem is that borrows are lexical; the compiler looks at the block of code where the borrow might be used as goes with that. It doesn't (currently) bother to try and reduce the length of borrows to match where they're actually active.
You can also play games with, for example, using std::mem::replace to pull state.data out into a local variable, do your work, then replace it back just before you return.

How do I use a Condvar to limit multithreading?

I'm trying to use a Condvar to limit the number of threads that are active at any given time. I'm having a hard time finding good examples on how to use Condvar. So far I have:
use std::sync::{Arc, Condvar, Mutex};
use std::thread;
fn main() {
let thread_count_arc = Arc::new((Mutex::new(0), Condvar::new()));
let mut i = 0;
while i < 100 {
let thread_count = thread_count_arc.clone();
thread::spawn(move || {
let &(ref num, ref cvar) = &*thread_count;
{
let mut start = num.lock().unwrap();
if *start >= 20 {
cvar.wait(start);
}
*start += 1;
}
println!("hello");
cvar.notify_one();
});
i += 1;
}
}
The compiler error given is:
error[E0382]: use of moved value: `start`
--> src/main.rs:16:18
|
14 | cvar.wait(start);
| ----- value moved here
15 | }
16 | *start += 1;
| ^^^^^ value used here after move
|
= note: move occurs because `start` has type `std::sync::MutexGuard<'_, i32>`, which does not implement the `Copy` trait
I'm entirely unsure if my use of Condvar is correct. I tried staying as close as I could to the example on the Rust API. Wwat is the proper way to implement this?
Here's a version that compiles:
use std::{
sync::{Arc, Condvar, Mutex},
thread,
};
fn main() {
let thread_count_arc = Arc::new((Mutex::new(0u8), Condvar::new()));
let mut i = 0;
while i < 100 {
let thread_count = thread_count_arc.clone();
thread::spawn(move || {
let (num, cvar) = &*thread_count;
let mut start = cvar
.wait_while(num.lock().unwrap(), |start| *start >= 20)
.unwrap();
// Before Rust 1.42, use this:
//
// let mut start = num.lock().unwrap();
// while *start >= 20 {
// start = cvar.wait(start).unwrap()
// }
*start += 1;
println!("hello");
cvar.notify_one();
});
i += 1;
}
}
The important part can be seen from the signature of Condvar::wait_while or Condvar::wait:
pub fn wait_while<'a, T, F>(
&self,
guard: MutexGuard<'a, T>,
condition: F
) -> LockResult<MutexGuard<'a, T>>
where
F: FnMut(&mut T) -> bool,
pub fn wait<'a, T>(
&self,
guard: MutexGuard<'a, T>
) -> LockResult<MutexGuard<'a, T>>
This says that wait_while / wait consumes the guard, which is why you get the error you did - you no longer own start, so you can't call any methods on it!
These functions are doing a great job of reflecting how Condvars work - you give up the lock on the Mutex (represented by start) for a while, and when the function returns you get the lock again.
The fix is to give up the lock and then grab the lock guard return value from wait_while / wait. I've also switched from an if to a while, as encouraged by huon.
For reference, the usual way to have a limited number of threads in a given scope is with a Semaphore.
Unfortunately, Semaphore was never stabilized, was deprecated in Rust 1.8 and was removed in Rust 1.9. There are crates available that add semaphores on top of other concurrency primitives.
let sema = Arc::new(Semaphore::new(20));
for i in 0..100 {
let sema = sema.clone();
thread::spawn(move || {
let _guard = sema.acquire();
println!("{}", i);
})
}
This isn't quite doing the same thing: since each thread is not printing the total number of the threads inside the scope when that thread entered it.
I realized the code I provided didn't do exactly what I wanted it to, so I'm putting this edit of Shepmaster's code here for future reference.
use std::sync::{Arc, Condvar, Mutex};
use std::thread;
fn main() {
let thread_count_arc = Arc::new((Mutex::new(0u8), Condvar::new()));
let mut i = 0;
while i < 150 {
let thread_count = thread_count_arc.clone();
thread::spawn(move || {
let x;
let &(ref num, ref cvar) = &*thread_count;
{
let start = num.lock().unwrap();
let mut start = if *start >= 20 {
cvar.wait(start).unwrap()
} else {
start
};
*start += 1;
x = *start;
}
println!("{}", x);
{
let mut counter = num.lock().unwrap();
*counter -= 1;
}
cvar.notify_one();
});
i += 1;
}
println!("done");
}
Running this in the playground should show more or less expected behavior.
You want to use a while loop, and re-assign start at each iteration, like:
fn main() {
let thread_count_arc = Arc::new((Mutex::new(0), Condvar::new()));
let mut i = 0;
while i < 100 {
let thread_count = thread_count_arc.clone();
thread::spawn(move || {
let &(ref num, ref cvar) = &*thread_count;
let mut start = num.lock().unwrap();
while *start >= 20 {
let current = cvar.wait(start).unwrap();
start = current;
}
*start += 1;
println!("hello");
cvar.notify_one();
});
i += 1;
}
}
See also some article on the topic:
https://medium.com/#polyglot_factotum/rust-concurrency-five-easy-pieces-871f1c62906a
https://medium.com/#polyglot_factotum/rust-concurrency-patterns-condvars-and-locks-e278f18db74f

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