2020-08-29 04:33:20 +00:00
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use crate::span;
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2020-11-12 02:47:22 +00:00
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use ordered_float::NotNan;
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2019-01-12 15:57:19 +00:00
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use std::{
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2020-11-10 12:30:01 +00:00
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collections::VecDeque,
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2019-06-09 18:14:02 +00:00
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time::{Duration, Instant},
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2019-01-12 15:57:19 +00:00
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};
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2020-11-10 12:30:01 +00:00
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/// This Clock tries to make this tick a constant time by sleeping the rest of
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/// the tick
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/// - if we actually took less time than we planned: sleep and return planned
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/// time
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/// - if we ran behind: don't sleep and return actual time
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/// We DON'T do any fancy averaging of the deltas for tick for 2 reasons:
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/// - all Systems have to work based on `dt` and we cannot assume that this is
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/// const through all ticks
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/// - when we have a slow tick, a lag, it doesn't help that we have 10 fast
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/// ticks directly afterwards
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/// We return a smoothed version for display only!
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pub struct Clock {
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/// This is the dt that the Clock tries to archive with each call of tick.
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target_dt: Duration,
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/// last time `tick` was called
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last_sys_time: Instant,
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/// will be calculated in `tick` returns the dt used by the next iteration
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/// of the main loop
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last_dt: Duration,
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/// summed up `last_dt`
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total_tick_time: Duration,
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// Stats only
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2020-11-12 02:47:22 +00:00
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// uses f32 so we have enough precision to display fps values while saving space
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last_dts_millis: VecDeque<NotNan<f32>>,
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last_dts_millis_sorted: Vec<NotNan<f32>>,
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stats: ClockStats,
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}
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pub struct ClockStats {
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/// busy_dt is the part of the last tick that we didn't sleep.
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/// e.g. the total tick is 33ms, including 25ms sleeping. then this returns
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/// 8ms
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pub last_busy_dt: Duration,
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/// avg over the last NUMBER_OF_OLD_DELTAS_KEPT ticks
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pub average_tps: f64,
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/// = 50% percentile
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pub median_tps: f64,
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/// lowest 10% of the frames
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pub percentile_90_tps: f64,
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/// lowest 5% of the frames
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pub percentile_95_tps: f64,
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/// lowest 1% of the frames
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pub percentile_99_tps: f64,
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}
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const NUMBER_OF_OLD_DELTAS_KEPT: usize = 100;
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impl Clock {
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pub fn new(target_dt: Duration) -> Self {
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Self {
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target_dt,
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last_sys_time: Instant::now(),
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last_dt: target_dt,
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total_tick_time: Duration::default(),
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last_dts_millis: VecDeque::with_capacity(NUMBER_OF_OLD_DELTAS_KEPT),
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last_dts_millis_sorted: Vec::with_capacity(NUMBER_OF_OLD_DELTAS_KEPT),
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stats: ClockStats::new(&Vec::new(), target_dt),
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}
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}
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pub fn set_target_dt(&mut self, target_dt: Duration) { self.target_dt = target_dt; }
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pub fn stats(&self) -> &ClockStats { &self.stats }
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pub fn dt(&self) -> Duration { self.last_dt }
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/// Do not modify without asking @xMAC94x first!
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pub fn tick(&mut self) {
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2020-09-07 04:59:16 +00:00
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span!(_guard, "tick", "Clock::tick");
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span!(guard, "clock work");
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let current_sys_time = Instant::now();
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let busy_delta = current_sys_time.duration_since(self.last_sys_time);
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// Maintain TPS
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self.last_dts_millis_sorted = self.last_dts_millis.iter().copied().collect();
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self.last_dts_millis_sorted.sort_unstable();
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self.stats = ClockStats::new(&self.last_dts_millis_sorted, busy_delta);
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drop(guard);
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2019-05-17 09:22:32 +00:00
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// Attempt to sleep to fill the gap.
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if let Some(sleep_dur) = self.target_dt.checked_sub(busy_delta) {
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spin_sleep::sleep(sleep_dur);
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}
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let after_sleep_sys_time = Instant::now();
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self.last_dt = after_sleep_sys_time.duration_since(self.last_sys_time);
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if self.last_dts_millis.len() >= NUMBER_OF_OLD_DELTAS_KEPT {
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self.last_dts_millis.pop_front();
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}
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self.last_dts_millis.push_back(
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NotNan::new(self.last_dt.as_secs_f32() * 1000.0)
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.expect("Duration::as_secs_f32 never returns NaN"),
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);
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self.total_tick_time += self.last_dt;
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self.last_sys_time = after_sleep_sys_time;
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}
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}
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impl ClockStats {
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fn new(sorted: &[NotNan<f32>], last_busy_dt: Duration) -> Self {
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const NANOS_PER_SEC: f64 = Duration::from_secs(1).as_nanos() as f64;
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const NANOS_PER_MILLI: f64 = Duration::from_millis(1).as_nanos() as f64;
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let len = sorted.len();
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let average_millis = sorted.iter().sum::<NotNan<f32>>().into_inner() / len.max(1) as f32;
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let average_tps = NANOS_PER_SEC / (average_millis as f64 * NANOS_PER_MILLI);
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let (median_tps, percentile_90_tps, percentile_95_tps, percentile_99_tps) = if len
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>= NUMBER_OF_OLD_DELTAS_KEPT
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{
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let median_millis = *sorted[len / 2];
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let percentile_90_millis = *sorted[(NUMBER_OF_OLD_DELTAS_KEPT as f32 * 0.1) as usize];
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let percentile_95_millis = *sorted[(NUMBER_OF_OLD_DELTAS_KEPT as f32 * 0.05) as usize];
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let percentile_99_millis = *sorted[(NUMBER_OF_OLD_DELTAS_KEPT as f32 * 0.01) as usize];
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let median_tps = NANOS_PER_SEC / (median_millis as f64 * NANOS_PER_MILLI);
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let percentile_90_tps = NANOS_PER_SEC / (percentile_90_millis as f64 * NANOS_PER_MILLI);
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let percentile_95_tps = NANOS_PER_SEC / (percentile_95_millis as f64 * NANOS_PER_MILLI);
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let percentile_99_tps = NANOS_PER_SEC / (percentile_99_millis as f64 * NANOS_PER_MILLI);
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(
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median_tps,
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percentile_90_tps,
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percentile_95_tps,
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percentile_99_tps,
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)
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2019-04-22 16:50:15 +00:00
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} else {
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let avg_tps = NANOS_PER_SEC / last_busy_dt.as_nanos() as f64;
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(avg_tps, avg_tps, avg_tps, avg_tps)
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};
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Self {
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last_busy_dt,
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average_tps,
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median_tps,
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percentile_90_tps,
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percentile_95_tps,
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percentile_99_tps,
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}
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2019-01-12 15:57:19 +00:00
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}
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}
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