blob: 1518047460477b6cd2d73256adc4d1bd906903ca [file] [log] [blame]
//! Benchmark the overhead that the synchronization of `OnceCell::get` causes.
//! We do some other operations that write to memory to get an imprecise but somewhat realistic
//! measurement.
use once_cell::sync::OnceCell;
use std::sync::atomic::{AtomicUsize, Ordering};
const N_THREADS: usize = 16;
const N_ROUNDS: usize = 1_000_000;
static CELL: OnceCell<usize> = OnceCell::new();
static OTHER: AtomicUsize = AtomicUsize::new(0);
fn main() {
let start = std::time::Instant::now();
let threads =
(0..N_THREADS).map(|i| std::thread::spawn(move || thread_main(i))).collect::<Vec<_>>();
for thread in threads {
thread.join().unwrap();
}
println!("{:?}", start.elapsed());
println!("{:?}", OTHER.load(Ordering::Relaxed));
}
#[inline(never)]
fn thread_main(i: usize) {
// The operations we do here don't really matter, as long as we do multiple writes, and
// everything is messy enough to prevent the compiler from optimizing the loop away.
let mut data = [i; 128];
let mut accum = 0usize;
for _ in 0..N_ROUNDS {
let _value = CELL.get_or_init(|| i + 1);
let k = OTHER.fetch_add(data[accum & 0x7F] as usize, Ordering::Relaxed);
for j in data.iter_mut() {
*j = (*j).wrapping_add(accum);
accum = accum.wrapping_add(k);
}
}
}