I am just asking myself which of the many hash algorithms performs best, so I can use
it to index my translation strings.
So I wrote a test script. It iterates over an array of 3.917.116 strings calculating
the hash of each.
Here you have the results, with run time, and run time relative to hash length
(smaller is better).
Interesting that the tiger hashes seem to perform well.
There were only collisions with adler32 (many), crc32 and crc32b.
/Str.
Name Length Timing t/Byte (skal.)
crc32 8 2,2150330544 276,9
crc32b 8 2,2309110165 278,9
adler32 8 2,4038968086 300,5
md4 32 2,9871790409 93,3
md5 32 3,0691349506 95,9
tiger128,3 32 3,4266569614 107,1
tiger160,3 40 3,5735139847 89,3
tiger128,4 32 3,6424109936 113,8
tiger192,3 48 3,6483809948 76,0
sha1 40 3,6727621555 91,8
tiger160,4 40 3,7693319321 94,2
tiger192,4 48 3,8536069393 80,3
ripemd128 32 3,9478549957 123,4
ripemd256 64 4,2519729137 66,4
salsa20 128 4,4366490841 34,7
salsa10 128 4,4819700718 35,0
ripemd160 40 4,8140711784 120,4
sha224 56 5,2336411476 93,5
ripemd320 80 5,2477719784 65,6
sha256 64 5,3834650517 84,1
haval128,3 32 5,8804600239 183,8
haval160,3 40 5,9342179298 148,4
haval192,3 48 6,0202069283 125,4
haval224,3 56 6,0966057777 108,9
haval256,3 64 6,2231030464 97,2
sha384 96 6,4372200966 67,1
sha512 128 6,7605450153 52,8
haval128,4 32 7,0831079483 221,3
haval160,4 40 7,1777567863 179,4
haval192,4 48 7,2292518616 150,6
haval224,4 56 7,3201220036 130,7
haval256,4 64 7,4621391296 116,6
whirlpool 128 7,4762940407 58,4
haval128,5 32 7,9410018921 248,2
haval160,5 40 8,028870821 200,7
haval192,5 48 8,102463007 168,8
haval224,5 56 8,1795060635 146,1
haval256,5 64 8,3195581436 130,0
gost 64 12,0381391048 188,1
snefru 64 14,0808851719 220,0
snefru256 64 14,1807420254 221,6
md2 32 17,4794299603 546,2
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