cross-runtime benchmarking lib
bun add mitata
npm install mitata
import { run, bench, group, baseline } from 'mitata';
// deno
// import { ... } from 'https://esm.sh/mitata';
bench('noop', () => {});
bench('noop2', () => {});
group('group', () => {
baseline('baseline', () => {});
bench('Date.now()', () => Date.now());
bench('performance.now()', () => performance.now());
});
group({ name: 'group2', summary: false }, () => {
bench('new Array(0)', () => new Array(0));
bench('new Array(1024)', () => new Array(1024));
});
await run({
avg: true, // enable/disable avg column (default: true)
json: false, // enable/disable json output (default: false)
colors: true, // enable/disable colors (default: true)
min_max: true, // enable/disable min/max column (default: true)
collect: false, // enable/disable collecting returned values into an array during the benchmark (default: false)
percentiles: false, // enable/disable percentiles column (default: true)
});output:
terminal screenshot
cpu: unknown
runtime: bun 0.0.79 (arm64-darwin)
benchmark time (avg) (min … max)
---------------------------------------------------------
noop 321.41 ps/iter (304.1 ps … 8.55 ns)
noop2 389.13 ps/iter (304.1 ps … 11.13 ns)
baseline 788.15 ps/iter (304.1 ps … 6.29 ns)
Date.now() 31.12 ns/iter (30.94 ns … 34.7 ns)
performance.now() 98.82 ns/iter (98.03 ns … 106.8 ns)
summary
baseline
39.49x faster than Date.now()
125.38x faster than performance.now()
new Array(0) 7.67 ns/iter (6.53 ns … 181.62 ns)
new Array(1024) 295.78 ns/iter (240.04 ns … 528.28 ns)If you run benchmarks like this, you might notice that they get slower (only few nanoseconds) after the first few runs.
bench('noop', () => {});
bench('noop', () => {});
bench('noop', () => {});
bench('noop', () => {});
bench('noop', () => {});
bench('noop', () => {});
bench('noop', () => {});
bench('noop', () => {});
bench('noop', () => {});
bench('noop', () => {});
bench('noop', () => {});
bench('noop', () => {});
bench('noop', () => {});I call this behavior "JIT bias". In simple words, v8 and JSC JIT expect us to pass the same function, so they optimize for it, but we break that promise and get deoptimized.
MIT © Evan