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 fasta benchmark ≈240MB N=25,000,000

Each chart bar shows how many times slower, one ↓ fasta program was, compared to the fastest program.

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
1.0Fortran Intel #4 3.183.182601327  0% 1% 0% 100%
1.1Haskell GHC #2 3.363.362,364979  0% 0% 0% 100%
1.3C++ g++ #2 4.104.116201105  0% 0% 0% 100%
1.3C++ g++ #3 4.224.238721286  0% 0% 0% 100%
1.3Ada 2005 GNAT #5 4.234.241,2322186  0% 0% 1% 100%
1.4Fortran Intel #3 4.584.585241190  1% 0% 0% 100%
1.5C++ g++ 4.634.636201033  2% 2% 1% 100%
1.5Java 7  #4 4.924.9214,9321507  0% 1% 0% 100%
1.6C gcc #4 4.924.932921221  0% 1% 1% 100%
1.6ATS 5.205.202882104  0% 1% 0% 100%
2.0Fortran Intel 6.366.372521155  0% 0% 0% 100%
2.1Scala #3 6.546.5519,5881053  0% 1% 0% 100%
2.1C++ g++ #4 6.576.582921266  0% 0% 0% 100%
2.2C gcc 6.906.912921185  0% 0% 1% 100%
2.3C# Mono #2 7.427.4314,2921180  1% 0% 0% 100%
2.5Java 7  #2 7.827.8314,3561240  0% 1% 1% 100%
2.5Pascal Free Pascal #4 7.927.9381112  1% 1% 0% 100%
2.6Lisp SBCL #6 8.178.178,2681751  0% 0% 0% 100%
3.0Ada 2005 GNAT 9.609.611,2321346  0% 0% 0% 100%
3.1Dart 9.859.85288,7681421  0% 0% 0% 100%
3.2Scala 10.3110.3219,6641080  0% 0% 0% 100%
3.3F# Mono 10.6110.6115,132978  1% 0% 0% 100%
3.7OCaml #3 11.7511.751,6361042  0% 0% 1% 100%
4.1Lisp SBCL #3 13.0113.0230,2161579  0% 0% 0% 100%
4.3Racket #3 13.7513.7617,2521276  0% 0% 0% 100%
4.8Lisp SBCL 15.1315.1430,3641419  0% 0% 0% 100%
5.1Lisp SBCL #2 16.2216.2430,3601617  0% 0% 0% 100%
5.3Go 16.6816.691,0121036  0% 0% 0% 100%
6.1JavaScript V8 19.4219.437,548791  0% 0% 0% 100%
6.7Clojure #5 21.2621.2778,6601839  0% 0% 0% 100%
6.7JavaScript V8 #2 21.3421.3630,184923  0% 0% 0% 100%
14Smalltalk VisualWorks 44.6344.6621,9561315  0% 1% 1% 100%
16Lua 49.7149.721,1121049  0% 1% 0% 100%
16Erlang HiPE #2 49.9850.007,6321164  0% 0% 0% 100%
16Racket 50.8650.8917,5961054  0% 0% 0% 100%
23PHP #4 71.9671.992,5241110  0% 0% 0% 100%
27Erlang HiPE 85.7285.767,6281039  0% 0% 0% 100%
29Perl 92.5592.5999,672838  0% 0% 0% 100%
50PHP #3 160.25163.422,5201030  0% 0% 1% 100%
56Ruby 2.0 #6 179.05181.61188,088772  0% 0% 0% 100%
66Ruby 2.0 #4 210.91213.87428,168904  0% 1% 0% 100%
73Ruby 2.0 #5 231.53234.854,872987  0% 1% 1% 99%
79Ruby JRuby 250.90254.52583,812760  0% 0% 0% 100%
81Perl #4 258.42258.551,992934  0% 0% 0% 100%
82Python 3 #2 259.48262.344,672788  0% 1% 1% 100%
83Python 3 263.96266.444,668792  0% 0% 0% 100%
98Ruby 2.0 #2 5 min5 min248,984732  0% 1% 1% 100%
110Perl #2 5 min5 min1,988886  0% 1% 1% 100%
133PHP #2 7 min7 min2,5201006  0% 0% 0% 100%
C CINT Bad Output1163
Haskell GHC #4 Bad Output1413
Haskell GHC Bad Output1421
OCaml #6 Failed1161
"wrong" (different) algorithm / less comparable programs
0.7Perl #5 2.072.0715,0761113
0.7C gcc #2 2.382.384161169
3.4Haskell GHC #3 10.6910.701,8441408

 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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