perf: Improve Xor method performance by ~20% for big sets #1
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Handling larger bitsets in 8-batches is more efficient on modern CPUs.
I assume it's related to instruction-level parallelism.
goos: darwin
goarch: arm64
pkg: github.com/KernelPryanic/bitmask
cpu: Apple M1 Max
│ old.txt │ new.txt │
│ sec/op │ sec/op vs base │
BitSet_Xor/empty-10 2.498n ± 4% 2.493n ± 3% ~ (p=0.372 n=6)
BitSet_Xor/5-10 2.491n ± 1% 2.492n ± 1% ~ (p=0.729 n=6)
BitSet_Xor/10k-10 76.10n ± 1% 49.79n ± 1% -34.57% (p=0.002 n=6)
BitSet_Xor/1m-10 8.453µ ± 0% 5.112µ ± 1% -39.52% (p=0.002 n=6)
geomean 44.73n 35.46n -20.72%
│ old.txt │ new.txt │
│ B/op │ B/op vs base │
BitSet_Xor/empty-10 0.000 ± 0% 0.000 ± 0% ~ (p=1.000 n=6) ¹
BitSet_Xor/5-10 0.000 ± 0% 0.000 ± 0% ~ (p=1.000 n=6) ¹
BitSet_Xor/10k-10 0.000 ± 0% 0.000 ± 0% ~ (p=1.000 n=6) ¹
BitSet_Xor/1m-10 0.000 ± 0% 0.000 ± 0% ~ (p=1.000 n=6) ¹
geomean ² +0.00% ²
¹ all samples are equal
² summaries must be >0 to compute geomean
│ old.txt │ new.txt │
│ allocs/op │ allocs/op vs base │
BitSet_Xor/empty-10 0.000 ± 0% 0.000 ± 0% ~ (p=1.000 n=6) ¹
BitSet_Xor/5-10 0.000 ± 0% 0.000 ± 0% ~ (p=1.000 n=6) ¹
BitSet_Xor/10k-10 0.000 ± 0% 0.000 ± 0% ~ (p=1.000 n=6) ¹
BitSet_Xor/1m-10 0.000 ± 0% 0.000 ± 0% ~ (p=1.000 n=6) ¹
geomean ² +0.00% ²
¹ all samples are equal
² summaries must be >0 to compute geomean
KernelPryanic
approved these changes
Feb 16, 2025
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Handling larger bitsets in 8-batches is more efficient on modern CPUs.
I assume it's related to instruction-level parallelism.
This technique can effectively be applied to most bitset methods and functions.