mirror of
https://github.com/danbulant/oxc
synced 2026-05-24 20:32:10 +00:00
508091314f
Add NodeJS parser to benchmarks. Previous attempt #2724 did not work due CodSpeed producing very inaccurate results (https://github.com/CodSpeedHQ/action/issues/96). This version runs the actual benchmarks without CodSpeed's instrumentation. Then another faux-benchmark runs within Codspeed's instrumented action and just performs meaningless calculations in a loop for as long as is required to take same amount of time as the original uninstrumented benchmarks took. It's unfortunate that we therefore don't get flame graphs on CodSpeed, but this seems to be the best we can do for now.
53 lines
2.1 KiB
Rust
53 lines
2.1 KiB
Rust
use std::{env, fs, path::PathBuf, time::Duration};
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use oxc_benchmark::{
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black_box, criterion_group, criterion_main, BenchmarkId, Criterion, SamplingMode,
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};
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use serde::Deserialize;
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#[derive(Deserialize)]
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struct BenchResult {
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filename: String,
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duration: f64,
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}
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/// This is a fake benchmark which is only here to get benchmarks for NAPI parser into CodSpeed.
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/// It's a workaround for CodSpeed's measurement of JS + NAPI being wildly inaccurate:
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/// https://github.com/CodSpeedHQ/action/issues/96
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/// So instead in CI we run the actual benchmark without CodSpeed's instrumentation
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/// (see `.github/workflows/benchmark.yml` and `napi/parser/parse.bench.mjs`).
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/// `parse.bench.mjs` writes the results of the benchmarks to a file `results.json`.
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/// This pseudo-benchmark reads that file and just performs meaningless calculations in a loop
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/// the number of times required to take same amount of time as the original benchmark.
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fn bench_parser_napi(criterion: &mut Criterion) {
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let data_dir = env::var("DATA_DIR").unwrap();
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let results_path: PathBuf = [&data_dir, "results.json"].iter().collect();
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let results_file = fs::File::open(&results_path).unwrap();
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let files: Vec<BenchResult> = serde_json::from_reader(results_file).unwrap();
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fs::remove_file(&results_path).unwrap();
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let mut group = criterion.benchmark_group("parser_napi");
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// Reduce time to run benchmark as much as possible (10 is min for sample size)
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group.sample_size(10);
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group.warm_up_time(Duration::from_micros(1));
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group.sampling_mode(SamplingMode::Flat);
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for file in files {
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let cycles = (file.duration * 266672645.0) as u64;
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group.bench_function(BenchmarkId::from_parameter(&file.filename), |b| {
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b.iter(|| {
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let cycles = black_box(cycles);
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let mut n: u64 = 0x1c2e9b89d37e0c1b;
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for _ in 0..cycles {
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n = n.rotate_right(3);
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n = n ^ 0x18bb6752b938b511;
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}
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black_box(n);
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});
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});
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}
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group.finish();
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}
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criterion_group!(parser, bench_parser_napi);
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criterion_main!(parser);
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