Benchmark Report

• Platform: macOS-26.2-arm64-arm-64bit

• Python: 3.9.6

• External exact edit-distance baseline: Edlib Python binding with mode="NW", task="distance".

• These graphs cover short global edit-distance workloads.

Benchmark Summary

• Core engine: deterministic short-DNA assignment with explicit unique, ambiguous, none, and invalid outcomes.

• Assignment throughput: indexed fixed-window rows reach multi-million-read/sec cases in the regenerated native and batch benchmarks, with zero assignment mismatches in native Edlib validation.

• Public assay evidence: CRISPR, barcode, BCL, feature-barcode, amplicon, oligo/adapter, and perturb-seq reports are generated from raw command artifacts and gated by scope-specific checks.

• Comparator scope: guide-counter, MAGeCK, Cutadapt-style, exact-slice, Edlib, exact-hash, and BK-tree comparators are reported where semantics are comparable; speed ratios are evidence, not universal replacement claims.

Graphs

Workflow Reports

• Evidence gallery and report examples

• Native Edlib assignment report

• Experimental GPU acceleration report

• Public CRISPR guide-counting report

• CRISPR multi-dataset comparison report

• Barcode demultiplexing report

• Raw BCL demultiplexing report

• Oligo/adapter public prefix-assignment report

• Perturb-seq/CRISPR guide-capture public assignment report

• Feature-barcode public assignment report

• Amplicon/panel public primer-start assignment report

Assay-lane coverage and public-evidence gaps are tracked in docs/assay-evidence.json and checked by make assay-evidence-ready. The gate inspects the listed raw CSV artifacts for data rows, command and exit-code provenance where present, and zero validation mismatch fields where recorded.

Exact Distance Mean Speedup

len	speedup_vs_edlib
16	1.78
24	1.83
32	1.89
64	2.23

Threshold Best Cases

len	k	err	dotmatch_ns	edlib_ns	speedup_vs_edlib
64	1	0.00	850.30	2713.20	3.19
64	0	0.00	851.20	2690.10	3.16
64	1	0.01	892.30	2667.50	2.99
64	1	0.03	857.20	2522.80	2.94
64	0	0.01	907.50	2590.90	2.85
64	0	0.03	856.50	2304.80	2.69
64	0	0.10	817.70	2150.00	2.63
32	0	0.00	812.30	1992.00	2.45

Batch Assignment Top Throughput Rows

tool	len	k	n_targets	reads_per_sec
dotmatch_indexed	8	0	96	18181679.7
dotmatch_indexed	8	0	384	10818699.2
dotmatch_indexed	8	0	4096	10000011.2
dotmatch_indexed	8	0	737	9429805.2
dotmatch_indexed	12	0	96	8545456.2
dotmatch_indexed	12	0	384	8333310.3
dotmatch_indexed	12	0	4096	7549866.5
dotmatch_indexed	12	0	737	7549866.5
dotmatch_indexed	16	0	384	6350805.1
dotmatch_indexed	16	0	737	6249997.9
dotmatch_indexed	16	0	96	5670499.8
dotmatch_indexed	16	0	4096	5634914.7

Scope

These results cover short-DNA global edit-distance and threshold matching against Edlib’s Python binding. Native-library comparator records are tracked in docs/benchmarks/native/README.md and docs/native-comparator-scope.md.