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 fasta benchmark ≈240MB N=25,000,000

Each chart bar shows how many times more Code, one ↓ fasta program used, compared to the program that used least Code.

These are not the only programs that could be written. These are not the only compilers and interpreters. These are not the only programming languages.

Column × shows how many times more each program used compared to the benchmark program that used least.

    sortsortsort 
  ×   Program Source Code CPU secs Elapsed secs Memory KB Code B ≈ CPU Load
1.0Ruby #2 270.96271.73176,156732  1% 59% 1% 41%
1.0Ruby JRuby 246.02241.84612,796760  23% 37% 31% 16%
1.1Python 3 #2 241.56246.324,324788  30% 24% 15% 33%
1.1Python 3 248.61253.034,324792  22% 24% 25% 31%
1.1Perl 116.40116.4599,960838  0% 94% 0% 7%
1.2Perl #2 7 min7 min2,280886  62% 0% 38% 0%
1.2Ruby #4 218.28221.88190,380904  21% 34% 23% 25%
1.3Perl #4 5 min5 min2,280934  1% 0% 100% 1%
1.3F# Mono 10.2010.2116,184978  0% 1% 0% 100%
1.3Haskell GHC #2 3.943.662,464979  4% 100% 3% 4%
1.3Ruby #5 217.79221.465,284987  36% 18% 33% 15%
1.4PHP #2 6 min6 min2,5921006  39% 13% 5% 45%
1.4PHP #3 148.94152.272,5881030  42% 27% 10% 21%
1.4C++ g++ 4.814.826321033  1% 0% 0% 100%
1.4Go 16.6616.667241036  22% 28% 100% 12%
1.4Erlang HiPE 95.1095.128,6561039  99% 0% 2% 0%
1.4OCaml #3 12.1612.171,6561042  1% 0% 1% 100%
1.4Scala #3 6.526.4120,3721053  91% 1% 11% 1%
1.4Racket 50.6350.6216,3641054  0% 1% 100% 0%
1.5Scala 10.3910.2620,4841080  1% 85% 1% 16%
1.5C++ g++ #2 4.234.236321105  0% 0% 100% 1%
1.5PHP #4 68.8868.912,5961110  0% 90% 10% 1%
1.5Pascal Free Pascal #4 7.947.9581112  0% 0% 0% 100%
1.6Fortran Intel 6.346.352521155  0% 0% 1% 100%
1.6Erlang HiPE #2 49.7449.758,7881164  0% 100% 0% 1%
1.6C# Mono #2 7.927.9215,3601180  0% 1% 100% 0%
1.6C gcc 7.057.062961185  0% 1% 100% 0%
1.6Fortran Intel #3 4.544.555241190  0% 0% 1% 100%
1.7C gcc #4 5.045.052961221  0% 1% 100% 0%
1.7Java  #2 7.927.8216,7121240  54% 1% 46% 1%
1.7C++ g++ #4 6.566.562961266  0% 1% 100% 0%
1.7Racket #3 13.9013.9117,6601276  0% 0% 100% 0%
1.8Rust 4.714.726761283  1% 0% 0% 100%
1.8C++ g++ #3 4.224.238841286  1% 0% 0% 100%
1.8Fortran Intel #4 3.183.192601327  0% 0% 2% 100%
1.8Ada 2005 GNAT 9.049.051,2361346  1% 0% 1% 100%
1.9Dart 9.089.0249,1601386  1% 0% 100% 2%
1.9Lisp SBCL 14.8714.8820,2961419  1% 100% 0% 0%
2.1C# Mono #4 10.0210.0341,0361505  1% 90% 0% 10%
2.1Java  #4 5.135.0516,4441507  2% 1% 1% 100%
2.2Lisp SBCL #3 12.7512.763,9441579  1% 100% 0% 0%
2.2Lisp SBCL #2 15.8615.8620,2961617  1% 0% 1% 100%
2.3Clojure #6 11.049.7050,2081653  25% 79% 6% 5%
2.4Lisp SBCL #6 8.058.054,1321751  0% 100% 1% 0%
2.5Clojure #5 12.6111.1453,7641839  75% 23% 10% 6%
3.0Ada 2005 GNAT #5 4.254.251,2362186  1% 0% 1% 100%
Haskell GHC #4 Bad Output1413
Haskell GHC Bad Output1421
OCaml #6 Failed1161
"wrong" (different) algorithm / less comparable programs
1.5Perl #5 2.302.3015,3081113
1.6C gcc #2 2.422.425561169
1.9Haskell GHC #3 12.5911.571,9401408

 fasta benchmark : Generate and write random DNA sequences

diff program output N = 1000 with this 10KB output file to check your program is correct before contributing.

We are trying to show the performance of various programming language implementations - so we ask that contributed programs not only give the correct result, but also use the same algorithm to calculate that result.

Each program should

We'll use the generated FASTA file as input for other benchmarks (reverse-complement, k-nucleotide).

Random DNA sequences can be based on a variety of Random Models (554KB pdf). You can use Markov chains or independently distributed nucleotides to generate random DNA sequences online.

Revised BSD license

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