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https://github.com/cwinfo/matterbridge.git
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.. | ||
arith_386.s | ||
arith_amd64.s | ||
arith_arm64.s | ||
arith_arm.s | ||
arith_decl.go | ||
arith_mips64x.s | ||
arith_mipsx.s | ||
arith_ppc64x.s | ||
arith_s390x.s | ||
fermat.go | ||
fft.go | ||
LICENSE | ||
README | ||
scan.go |
Benchmarking math/big vs. bigfft Number size old ns/op new ns/op delta 1kb 1599 1640 +2.56% 10kb 61533 62170 +1.04% 50kb 833693 831051 -0.32% 100kb 2567995 2693864 +4.90% 1Mb 105237800 28446400 -72.97% 5Mb 1272947000 168554600 -86.76% 10Mb 3834354000 405120200 -89.43% 20Mb 11514488000 845081600 -92.66% 50Mb 49199945000 2893950000 -94.12% 100Mb 147599836000 5921594000 -95.99% Benchmarking GMP vs bigfft Number size GMP ns/op Go ns/op delta 1kb 536 1500 +179.85% 10kb 26669 50777 +90.40% 50kb 252270 658534 +161.04% 100kb 686813 2127534 +209.77% 1Mb 12100000 22391830 +85.06% 5Mb 111731843 133550600 +19.53% 10Mb 212314000 318595800 +50.06% 20Mb 490196000 671512800 +36.99% 50Mb 1280000000 2451476000 +91.52% 100Mb 2673000000 5228991000 +95.62% Benchmarks were run on a Core 2 Quad Q8200 (2.33GHz). FFT is enabled when input numbers are over 200kbits. Scanning large decimal number from strings. (math/big [n^2 complexity] vs bigfft [n^1.6 complexity], Core i5-4590) Digits old ns/op new ns/op delta 1e3 9995 10876 +8.81% 1e4 175356 243806 +39.03% 1e5 9427422 6780545 -28.08% 1e6 1776707489 144867502 -91.85% 2e6 6865499995 346540778 -94.95% 5e6 42641034189 1069878799 -97.49% 10e6 151975273589 2693328580 -98.23%