| |
| |
| |
| |
| |
| use fast_split::classify::{Atoms, classify}; |
| use fast_split::fsm::{Span, whitespace_split_scalar, whitespace_split_simd}; |
| use std::hint::black_box; |
| use std::time::Instant; |
|
|
| const CORPORA: &[(&str, &str)] = &[ |
| ("English", "../data/big.txt"), |
| ("French", "benches/data/fr.txt"), |
| ("Russian", "benches/data/ru.txt"), |
| ("Greek", "benches/data/el.txt"), |
| ("Arabic", "benches/data/ar.txt"), |
| ("Hindi", "benches/data/hi.txt"), |
| ("Thai", "benches/data/th.txt"), |
| ("Chinese", "benches/data/zh.txt"), |
| ("Japanese", "../data/unigram_wagahaiwa_nekodearu.txt"), |
| ("Korean", "benches/data/ko.txt"), |
| ]; |
|
|
| |
| fn ws_ref(s: &str) -> Vec<Span> { |
| let mut out = Vec::new(); |
| let mut start: Option<usize> = None; |
| for (i, c) in s.char_indices() { |
| if c.is_whitespace() { |
| if let Some(st) = start.take() { |
| out.push((st as u32, i as u32)); |
| } |
| } else if start.is_none() { |
| start = Some(i); |
| } |
| } |
| if let Some(st) = start { |
| out.push((st as u32, s.len() as u32)); |
| } |
| out |
| } |
|
|
| fn ns_per_byte<F: FnMut() -> usize>(len: usize, iters: u32, mut f: F) -> f64 { |
| for _ in 0..3 { |
| black_box(f()); |
| } |
| let mut best = f64::INFINITY; |
| for _ in 0..7 { |
| let t = Instant::now(); |
| let mut acc = 0usize; |
| for _ in 0..iters { |
| acc = acc.wrapping_add(f()); |
| } |
| black_box(acc); |
| best = best.min(t.elapsed().as_nanos() as f64 / (iters as usize * len) as f64); |
| } |
| best |
| } |
|
|
| fn main() { |
| let manifest = env!("CARGO_MANIFEST_DIR"); |
| println!( |
| "{:<10} {:>7} {:>5} {:>8} {:>8} | {:>7} {:>6}", |
| "lang", "bytes", "b/tok", "simd", "scalar", "speedup", "parity" |
| ); |
|
|
| for (label, rel) in CORPORA { |
| let raw = match std::fs::read_to_string(format!("{manifest}/{rel}")) { |
| Ok(s) if !s.trim().is_empty() => s, |
| _ => { |
| println!("{label:<10} (skipped — {rel} missing)"); |
| continue; |
| } |
| }; |
| let mut c = raw.len().min(180_000); |
| while c > 0 && !raw.is_char_boundary(c) { |
| c -= 1; |
| } |
| let corpus = &raw[..c]; |
| let text = corpus.as_bytes(); |
| let n = text.len(); |
| let iters = (4_000_000 / n).clamp(3, 150) as u32; |
|
|
| let mut tags = vec![0u8; n]; |
| classify::<Atoms>(text, &mut tags); |
|
|
| |
| let reference = ws_ref(corpus); |
| let (mut a, mut b) = (Vec::new(), Vec::new()); |
| whitespace_split_scalar(text, &tags, &mut a); |
| whitespace_split_simd(text, &tags, &mut b); |
| let parity = if a == reference && b == reference { |
| "✓" |
| } else { |
| if a != reference { |
| eprintln!(" {label}: scalar != ref ({} vs {} tokens)", a.len(), reference.len()); |
| } |
| if b != reference { |
| let k = a.iter().zip(&b).position(|(x, y)| x != y).unwrap_or(a.len().min(b.len())); |
| eprintln!(" {label}: simd != ref @tok {k}: simd={:?} scal={:?}", b.get(k), a.get(k)); |
| } |
| "✗" |
| }; |
| let btok = n as f64 / a.len().max(1) as f64; |
|
|
| let simd = ns_per_byte(n, iters, || { |
| b.clear(); |
| whitespace_split_simd(text, &tags, &mut b); |
| b.len() |
| }); |
| let scal = ns_per_byte(n, iters, || { |
| a.clear(); |
| whitespace_split_scalar(text, &tags, &mut a); |
| a.len() |
| }); |
|
|
| println!( |
| "{label:<10} {n:>7} {btok:>5.1} {simd:>8.3} {scal:>8.3} | {:>6.2}x {parity:>6}", |
| scal / simd |
| ); |
| } |
| println!("\n(ns/byte, lower better. simd = whitespace_split_simd, scalar = generic fsm_split core.)"); |
| } |
|
|