Auto merge of #38779 - Craig-Macomber:bench, r=alexcrichton

Do not run outer setup part of benchmarks multiple times to fix issue 20142

Fix #20142

This is my first real rust code, so I expect the quality is quite bad. Please let me know in which ways it is horrible and I'll fix it.

Previously the whole benchmark function was rerun many times, but with this change, only the callback passed to iter is rerun. This improves performances by saving benchmark startup time. The setup used to be called a minimum of 101 times, and now only runs once.

I wasn't sure exactly what should be done for the case where iter is never called, so I left a FIXME for that: currently it does not error, and I added tests to cover that.

I have left the algorithm and statistics unchanged: I don't like how the minimum number of runs is 301 (that's bad for very slow benchmarks) but I consider such changes out of scope for this fix.

Author: bors

src/libtest/lib.rs

@@ -185,13 +185,19 @@ impl fmt::Debug for TestFn {
 /// This is fed into functions marked with `#[bench]` to allow for
 /// set-up & tear-down before running a piece of code repeatedly via a
 /// call to `iter`.
-#[derive(Copy, Clone)]
+#[derive(Clone)]
 pub struct Bencher {
-    iterations: u64,
-    dur: Duration,
+    mode: BenchMode,
+    summary: Option<stats::Summary>,
     pub bytes: u64,
 }
 
+#[derive(Clone, PartialEq, Eq)]
+pub enum BenchMode {
+    Auto,
+    Single,
+}
+
 #[derive(Copy, Clone, Debug, PartialEq, Eq, Hash)]
 pub enum ShouldPanic {
     No,
@@ -1444,138 +1450,148 @@ impl Bencher {
     pub fn iter<T, F>(&mut self, mut inner: F)
         where F: FnMut() -> T
     {
-        let start = Instant::now();
-        let k = self.iterations;
-        for _ in 0..k {
-            black_box(inner());
+        if self.mode == BenchMode::Single {
+            ns_iter_inner(&mut inner, 1);
+            return;
         }
-        self.dur = start.elapsed();
-    }
 
-    pub fn ns_elapsed(&mut self) -> u64 {
-        self.dur.as_secs() * 1_000_000_000 + (self.dur.subsec_nanos() as u64)
+        self.summary = Some(iter(&mut inner));
     }
 
-    pub fn ns_per_iter(&mut self) -> u64 {
-        if self.iterations == 0 {
-            0
-        } else {
-            self.ns_elapsed() / cmp::max(self.iterations, 1)
-        }
-    }
-
-    pub fn bench_n<F>(&mut self, n: u64, f: F)
-        where F: FnOnce(&mut Bencher)
+    pub fn bench<F>(&mut self, mut f: F) -> Option<stats::Summary>
+        where F: FnMut(&mut Bencher)
     {
-        self.iterations = n;
         f(self);
+        return self.summary;
     }
+}
 
-    // This is a more statistics-driven benchmark algorithm
-    pub fn auto_bench<F>(&mut self, mut f: F) -> stats::Summary
-        where F: FnMut(&mut Bencher)
-    {
-        // Initial bench run to get ballpark figure.
-        let mut n = 1;
-        self.bench_n(n, |x| f(x));
-
-        // Try to estimate iter count for 1ms falling back to 1m
-        // iterations if first run took < 1ns.
-        if self.ns_per_iter() == 0 {
-            n = 1_000_000;
-        } else {
-            n = 1_000_000 / cmp::max(self.ns_per_iter(), 1);
-        }
-        // if the first run took more than 1ms we don't want to just
-        // be left doing 0 iterations on every loop. The unfortunate
-        // side effect of not being able to do as many runs is
-        // automatically handled by the statistical analysis below
-        // (i.e. larger error bars).
-        if n == 0 {
-            n = 1;
+fn ns_from_dur(dur: Duration) -> u64 {
+    dur.as_secs() * 1_000_000_000 + (dur.subsec_nanos() as u64)
+}
+
+fn ns_iter_inner<T, F>(inner: &mut F, k: u64) -> u64
+    where F: FnMut() -> T
+{
+    let start = Instant::now();
+    for _ in 0..k {
+        black_box(inner());
+    }
+    return ns_from_dur(start.elapsed());
+}
+
+
+pub fn iter<T, F>(inner: &mut F) -> stats::Summary
+    where F: FnMut() -> T
+{
+    // Initial bench run to get ballpark figure.
+    let ns_single = ns_iter_inner(inner, 1);
+
+    // Try to estimate iter count for 1ms falling back to 1m
+    // iterations if first run took < 1ns.
+    let ns_target_total = 1_000_000; // 1ms
+    let mut n = ns_target_total / cmp::max(1, ns_single);
+
+    // if the first run took more than 1ms we don't want to just
+    // be left doing 0 iterations on every loop. The unfortunate
+    // side effect of not being able to do as many runs is
+    // automatically handled by the statistical analysis below
+    // (i.e. larger error bars).
+    n = cmp::max(1, n);
+
+    let mut total_run = Duration::new(0, 0);
+    let samples: &mut [f64] = &mut [0.0_f64; 50];
+    loop {
+        let loop_start = Instant::now();
+
+        for p in &mut *samples {
+            *p = ns_iter_inner(inner, n) as f64 / n as f64;
         }
 
-        let mut total_run = Duration::new(0, 0);
-        let samples: &mut [f64] = &mut [0.0_f64; 50];
-        loop {
-            let loop_start = Instant::now();
+        stats::winsorize(samples, 5.0);
+        let summ = stats::Summary::new(samples);
 
-            for p in &mut *samples {
-                self.bench_n(n, |x| f(x));
-                *p = self.ns_per_iter() as f64;
-            }
+        for p in &mut *samples {
+            let ns = ns_iter_inner(inner, 5 * n);
+            *p = ns as f64 / (5 * n) as f64;
+        }
 
-            stats::winsorize(samples, 5.0);
-            let summ = stats::Summary::new(samples);
+        stats::winsorize(samples, 5.0);
+        let summ5 = stats::Summary::new(samples);
 
-            for p in &mut *samples {
-                self.bench_n(5 * n, |x| f(x));
-                *p = self.ns_per_iter() as f64;
-            }
+        let loop_run = loop_start.elapsed();
 
-            stats::winsorize(samples, 5.0);
-            let summ5 = stats::Summary::new(samples);
-            let loop_run = loop_start.elapsed();
+        // If we've run for 100ms and seem to have converged to a
+        // stable median.
+        if loop_run > Duration::from_millis(100) && summ.median_abs_dev_pct < 1.0 &&
+           summ.median - summ5.median < summ5.median_abs_dev {
+            return summ5;
+        }
 
-            // If we've run for 100ms and seem to have converged to a
-            // stable median.
-            if loop_run > Duration::from_millis(100) && summ.median_abs_dev_pct < 1.0 &&
-               summ.median - summ5.median < summ5.median_abs_dev {
-                return summ5;
-            }
+        total_run = total_run + loop_run;
+        // Longest we ever run for is 3s.
+        if total_run > Duration::from_secs(3) {
+            return summ5;
+        }
 
-            total_run = total_run + loop_run;
-            // Longest we ever run for is 3s.
-            if total_run > Duration::from_secs(3) {
+        // If we overflow here just return the results so far. We check a
+        // multiplier of 10 because we're about to multiply by 2 and the
+        // next iteration of the loop will also multiply by 5 (to calculate
+        // the summ5 result)
+        n = match n.checked_mul(10) {
+            Some(_) => n * 2,
+            None => {
                 return summ5;
             }
-
-            // If we overflow here just return the results so far. We check a
-            // multiplier of 10 because we're about to multiply by 2 and the
-            // next iteration of the loop will also multiply by 5 (to calculate
-            // the summ5 result)
-            n = match n.checked_mul(10) {
-                Some(_) => n * 2,
-                None => return summ5,
-            };
-        }
+        };
     }
 }
 
 pub mod bench {
     use std::cmp;
-    use std::time::Duration;
-    use super::{Bencher, BenchSamples};
+    use stats;
+    use super::{Bencher, BenchSamples, BenchMode};
 
     pub fn benchmark<F>(f: F) -> BenchSamples
         where F: FnMut(&mut Bencher)
     {
         let mut bs = Bencher {
-            iterations: 0,
-            dur: Duration::new(0, 0),
+            mode: BenchMode::Auto,
+            summary: None,
             bytes: 0,
         };
 
-        let ns_iter_summ = bs.auto_bench(f);
+        return match bs.bench(f) {
+            Some(ns_iter_summ) => {
+                let ns_iter = cmp::max(ns_iter_summ.median as u64, 1);
+                let mb_s = bs.bytes * 1000 / ns_iter;
 
-        let ns_iter = cmp::max(ns_iter_summ.median as u64, 1);
-        let mb_s = bs.bytes * 1000 / ns_iter;
-
-        BenchSamples {
-            ns_iter_summ: ns_iter_summ,
-            mb_s: mb_s as usize,
-        }
+                BenchSamples {
+                    ns_iter_summ: ns_iter_summ,
+                    mb_s: mb_s as usize,
+                }
+            }
+            None => {
+                // iter not called, so no data.
+                // FIXME: error in this case?
+                let samples: &mut [f64] = &mut [0.0_f64; 1];
+                BenchSamples {
+                    ns_iter_summ: stats::Summary::new(samples),
+                    mb_s: 0,
+                }
+            }
+        };
     }
 
     pub fn run_once<F>(f: F)
-        where F: FnOnce(&mut Bencher)
+        where F: FnMut(&mut Bencher)
     {
         let mut bs = Bencher {
-            iterations: 0,
-            dur: Duration::new(0, 0),
+            mode: BenchMode::Single,
+            summary: None,
             bytes: 0,
         };
-        bs.bench_n(1, f);
+        bs.bench(f);
     }
 }
 
@@ -1585,6 +1601,8 @@ mod tests {
                TestDescAndFn, TestOpts, run_test, MetricMap, StaticTestName, DynTestName,
                DynTestFn, ShouldPanic};
     use std::sync::mpsc::channel;
+    use bench;
+    use Bencher;
 
     #[test]
     pub fn do_not_run_ignored_tests() {
@@ -1880,4 +1898,34 @@ mod tests {
         m1.insert_metric("in-both-want-upwards-and-improved", 1000.0, -10.0);
         m2.insert_metric("in-both-want-upwards-and-improved", 2000.0, -10.0);
     }
+
+    #[test]
+    pub fn test_bench_once_no_iter() {
+        fn f(_: &mut Bencher) {}
+        bench::run_once(f);
+    }
+
+    #[test]
+    pub fn test_bench_once_iter() {
+        fn f(b: &mut Bencher) {
+            b.iter(|| {
+            })
+        }
+        bench::run_once(f);
+    }
+
+    #[test]
+    pub fn test_bench_no_iter() {
+        fn f(_: &mut Bencher) {}
+        bench::benchmark(f);
+    }
+
+    #[test]
+    pub fn test_bench_iter() {
+        fn f(b: &mut Bencher) {
+            b.iter(|| {
+            })
+        }
+        bench::benchmark(f);
+    }
 }

src/libtest/stats.rs

@@ -120,7 +120,7 @@ pub trait Stats {
 }
 
 /// Extracted collection of all the summary statistics of a sample set.
-#[derive(Clone, PartialEq)]
+#[derive(Clone, PartialEq, Copy)]
 #[allow(missing_docs)]
 pub struct Summary {
     pub sum: f64,
@@ -896,4 +896,7 @@ mod bench {
             v.sum();
         })
     }
+
+    #[bench]
+    pub fn no_iter(_: &mut Bencher) {}
 }