2023-03-09 13:48:00 -08:00
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This library is a toy proof-of-concept implementation of the
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well-known Schonhage-Strassen method for multiplying integers.
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It is not expected to have a real life usecase outside number
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theory computations, nor is it expected to be used in any production
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system.
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If you are using it in your project, you may want to carefully
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examine the actual requirement or problem you are trying to solve.
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# Comparison with the standard library and GMP
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2022-01-30 15:27:37 -08:00
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Benchmarking math/big vs. bigfft
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Number size old ns/op new ns/op delta
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1kb 1599 1640 +2.56%
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10kb 61533 62170 +1.04%
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50kb 833693 831051 -0.32%
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100kb 2567995 2693864 +4.90%
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1Mb 105237800 28446400 -72.97%
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5Mb 1272947000 168554600 -86.76%
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10Mb 3834354000 405120200 -89.43%
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20Mb 11514488000 845081600 -92.66%
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50Mb 49199945000 2893950000 -94.12%
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100Mb 147599836000 5921594000 -95.99%
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Benchmarking GMP vs bigfft
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Number size GMP ns/op Go ns/op delta
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1kb 536 1500 +179.85%
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10kb 26669 50777 +90.40%
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50kb 252270 658534 +161.04%
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100kb 686813 2127534 +209.77%
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1Mb 12100000 22391830 +85.06%
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5Mb 111731843 133550600 +19.53%
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10Mb 212314000 318595800 +50.06%
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20Mb 490196000 671512800 +36.99%
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50Mb 1280000000 2451476000 +91.52%
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100Mb 2673000000 5228991000 +95.62%
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Benchmarks were run on a Core 2 Quad Q8200 (2.33GHz).
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FFT is enabled when input numbers are over 200kbits.
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Scanning large decimal number from strings.
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(math/big [n^2 complexity] vs bigfft [n^1.6 complexity], Core i5-4590)
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Digits old ns/op new ns/op delta
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1e3 9995 10876 +8.81%
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1e4 175356 243806 +39.03%
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1e5 9427422 6780545 -28.08%
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1e6 1776707489 144867502 -91.85%
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2e6 6865499995 346540778 -94.95%
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5e6 42641034189 1069878799 -97.49%
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10e6 151975273589 2693328580 -98.23%
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