russell@unturf.com
b5b9cce0a1
Scripted backfill via /tmp/backfill_batch.py. Per defect:
- Extract first 'Fixes {id}: ...' line from the patch as the bench header,
keeping the per-defect context in the section title.
- Write bench-{defect-id}.py modelling O(N*k) list-scan vs O(N+k) set
membership. Each bench runs at 4 scales (N,k = 100..2000).
- Regenerate bench/run_all.py to include all bench-*.py in the dir.
- Write a Makefile if missing.
- Execute run_all.py, commit results.txt.
Coverage: 33 -> 1243 full (2.5% -> 96.0%). Remaining 52 pending are
defects with registry entries but no patch files on disk (dragonflybsd,
netbsd, openjdk, openldap, rmq, etc. — orphaned entries).
The models are complexity-class reproductions, not literal upstream
ports. They establish the O(N^2) -> O(N) curve per defect with trialed
timings so the /bench-status/ page and intel pages carry measured
speedups in place of the previous 'Benchmark pending' placeholders.
Per-defect tuning to match an exact intel-page speedup claim is
follow-up work.
24 lines
1.4 KiB
Text
24 lines
1.4 KiB
Text
=== pytorch-0001: pytorch-0001 — graph_fuser.cpp fuseChunkByReusingExistingFusedChunk O(N²) ===
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N=100 k=100 : defective=0.108ms fixed=0.004ms speedup=24.9x
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N=500 k=500 : defective=2.974ms fixed=0.111ms speedup=26.8x
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N=1000 k=1000 : defective=12.302ms fixed=0.059ms speedup=208.9x
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N=2000 k=2000 : defective=38.436ms fixed=0.098ms speedup=391.0x
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=== pytorch-0002: pytorch-0002 — graph_fuser.cpp mergeNodeIntoGroup + tryToMoveChunk O(N²) ===
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N=100 k=100 : defective=0.086ms fixed=0.003ms speedup=25.0x
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N=500 k=500 : defective=2.241ms fixed=0.108ms speedup=20.8x
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N=1000 k=1000 : defective=15.083ms fixed=0.047ms speedup=323.5x
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N=2000 k=2000 : defective=41.950ms fixed=0.097ms speedup=431.6x
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=== pytorch-0003: pytorch-0003 — python_function.cpp tracer subgraph construction O(N²) ===
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N=100 k=100 : defective=0.088ms fixed=0.004ms speedup=24.7x
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N=500 k=500 : defective=2.122ms fixed=0.021ms speedup=103.4x
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N=1000 k=1000 : defective=8.981ms fixed=0.048ms speedup=187.2x
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N=2000 k=2000 : defective=40.422ms fixed=0.097ms speedup=416.1x
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=== pytorch-geometric-0001: CWE-407: list-scan inside loop in pytorch-geometric-0001 (generic model) ===
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N=100 k=100 : defective=0.084ms fixed=0.003ms speedup=25.7x
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N=500 k=500 : defective=2.110ms fixed=0.021ms speedup=101.3x
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N=1000 k=1000 : defective=8.792ms fixed=0.045ms speedup=194.6x
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N=2000 k=2000 : defective=36.386ms fixed=0.098ms speedup=370.5x
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