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fix(SW): Sequential and sequential_straight algs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,74 +1,51 @@ | ||
| use std::iter::repeat; | ||
| use rand::Rng; | ||
| use sw::{ | ||
| algorithm::{find_alignment_simd_lowmem, AlignmentScores}, | ||
| find_alignment_simd, | ||
| }; | ||
|
|
||
| #[allow(unused_imports)] | ||
| use sw::algorithm::{ | ||
| string_scores_parallel, string_scores_simd, string_scores_straight, traceback, | ||
| }; | ||
|
|
||
| use argminmax::ArgMinMax; | ||
|
|
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| const LANES: usize = 64; | ||
|
|
||
| use sw::{ | ||
| algorithm::AlignmentScores, | ||
| utils::{coord, roundup}, | ||
| }; | ||
|
|
||
| fn main() { | ||
| let scores = AlignmentScores { | ||
| gap: -2, | ||
| r#match: 3, | ||
| miss: -3, | ||
| }; | ||
|
|
||
| let mut query = repeat('A').take(128).collect::<Vec<_>>(); | ||
| let mut target = repeat('T').take(20000000).collect::<Vec<_>>(); | ||
|
|
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| target[67] = 'Z'; | ||
| target[68] = 'Z'; | ||
| query[13] = 'Z'; | ||
| query[14] = 'Z'; | ||
|
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| let start = std::time::Instant::now(); | ||
|
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| let data = string_scores_simd::<LANES>(&query, &target, scores); | ||
| let mut rng = rand::thread_rng(); | ||
|
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||
| // PERF: We might be able to eek out a bit more perf here by ignoring the min in a custom | ||
| // implementation | ||
| let (_min_index, max_index) = data.argminmax(); | ||
| let max = data[max_index]; | ||
| // let (max_index, max) = data.iter().enumerate().max_by_key(|(_, x)| *x).unwrap(); | ||
| let charset = ['A', 'T', 'C', 'G']; | ||
|
|
||
| let end = std::time::Instant::now(); | ||
| for _i in 0..10000 { | ||
| let query: Vec<_> = (0..) | ||
| .map(|_| { | ||
| let i: u8 = rng.gen(); | ||
| let char = charset[i as usize % charset.len()]; | ||
|
|
||
| let duration = end - start; | ||
| println!("Query * Target: {}", query.len() * target.len()); | ||
| println!("Duration: {:?}", duration.as_micros()); | ||
| char | ||
| }) | ||
| .take(1000) | ||
| .collect(); | ||
|
|
||
| println!( | ||
| "MCUPS: {}", | ||
| (query.len() * target.len()) / (duration.as_micros() as usize) | ||
| ); | ||
| let target: Vec<_> = (0..) | ||
| .map(|_| { | ||
| let i: u8 = rng.gen(); | ||
| let char = charset[i as usize % charset.len()]; | ||
|
|
||
| println!("Max: {}", max); | ||
| println!("Max index: {}", max_index); | ||
| let data_width = roundup(query.len(), LANES) + 1; | ||
| let (x, y) = coord(max_index, data_width); | ||
| println!("x: {}; y: {}", x - 1, y - x); | ||
| let mut query_result = Vec::new(); | ||
| let mut target_result = Vec::new(); | ||
| char | ||
| }) | ||
| .take(1000) | ||
| .collect(); | ||
|
|
||
| traceback( | ||
| &data, | ||
| &query, | ||
| &target, | ||
| x, | ||
| y, | ||
| data_width, | ||
| &mut query_result, | ||
| &mut target_result, | ||
| scores, | ||
| ); | ||
| let lm = find_alignment_simd_lowmem::<LANES>(&query, &target, scores); | ||
| let sd = find_alignment_simd::<LANES>(&query, &target, scores); | ||
|
|
||
| println!("Query: {:?}", query_result); | ||
| println!("Target: {:?}", target_result); | ||
| assert_eq!(lm, sd); | ||
| } | ||
| } |