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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 2.692.702441327  0% 0% 0% 100%
1.3Haskell GHC #2 3.593.602,740979  0% 0% 2% 100%
1.5Ada 2005 GNAT #5 4.054.061,5002186  1% 0% 0% 100%
1.6C++ g++ #3 4.194.191,0761286  0% 1% 0% 100%
1.6C++ g++ #2 4.404.418321105  1% 2% 1% 100%
1.7Fortran Intel #3 4.464.475081190  0% 0% 0% 100%
1.7C++ g++ 4.624.638321033  0% 0% 0% 100%
1.7Rust 4.664.667801283  0% 1% 1% 100%
2.0Java  #4 5.375.3720,8881507  0% 1% 1% 100%
2.2Fortran Intel 5.985.985081155  0% 1% 1% 100%
2.2C gcc #4 6.016.013761221  0% 0% 1% 100%
2.3C++ g++ #4 6.196.193721266  0% 0% 1% 100%
2.4Scala #3 6.466.4727,2041053  0% 1% 1% 100%
2.4C# Mono #2 6.496.4916,1361180  1% 1% 1% 100%
2.5Go 6.606.619921036  0% 0% 1% 100%
2.7C gcc 7.217.223721185  1% 0% 0% 100%
2.8Lisp SBCL #6 7.657.655,0361751  0% 1% 1% 100%
3.1F# Mono 8.258.2517,352978  1% 0% 1% 100%
3.1Java  #2 8.378.3720,3321240  1% 1% 1% 100%
3.3Ada 2005 GNAT 8.778.771,4961346  0% 0% 1% 100%
3.4Dart 9.209.21293,7241386  0% 1% 1% 100%
3.5C# Mono #4 9.449.4542,1801505  0% 1% 0% 100%
3.9Lisp SBCL #3 10.4010.414,7921579  0% 0% 1% 100%
3.9OCaml #6 10.5210.53201,7801161  0% 0% 0% 100%
4.0Scala 10.7110.7127,0961080  0% 0% 0% 100%
4.1Pascal Free Pascal #4 11.1711.1781112  0% 0% 0% 100%
5.0OCaml #3 13.4113.423,1241042  0% 0% 0% 100%
6.3Clojure #6 16.9316.95111,4601653  1% 0% 1% 100%
6.3Lisp SBCL 16.9616.974,7921419  0% 0% 1% 100%
6.4Racket #3 17.2217.2324,5841276  0% 1% 0% 100%
6.4Lisp SBCL #2 17.2717.274,7921617  0% 0% 1% 100%
6.6JavaScript V8 17.6617.679,472791  0% 1% 0% 100%
7.8JavaScript V8 #2 20.8820.9040,460923  0% 1% 1% 100%
7.9Clojure #5 21.3821.40102,6401839  0% 1% 1% 100%
11Erlang HiPE #2 29.0729.0911,9161164  0% 0% 0% 100%
13Hack #4 34.4534.47303,9641109  1% 0% 0% 100%
17Lua 44.5944.601,4801049  0% 0% 0% 100%
18Smalltalk VisualWorks 47.2447.2541,2841315  0% 0% 0% 100%
19Racket 49.9349.9621,4241054  0% 1% 1% 100%
21Hack #3 56.7456.77303,9521029  1% 0% 0% 100%
22Erlang HiPE 58.1058.1311,9241039  0% 0% 0% 100%
24PHP #4 63.3663.383,6001110  0% 0% 0% 100%
25Hack #2 68.3268.3555,6081003  1% 0% 0% 100%
36Perl 96.4396.46100,036838  0% 0% 0% 100%
54Ruby #5 144.98149.947,512987  1% 1% 0% 100%
55PHP #3 148.29151.553,3321030  0% 0% 0% 100%
56Ruby #4 149.87155.05243,360904  2% 1% 1% 100%
58Python 3 156.10160.135,572792  1% 0% 0% 100%
61Python 3 #2 165.35170.105,580788  1% 0% 0% 100%
76Ruby #2 203.65203.72202,920732  0% 0% 1% 100%
80Ruby JRuby 216.29220.27650,292760  0% 1% 1% 100%
99Perl #4 267.46267.562,352934  0% 0% 0% 100%
146Perl #2 6 min6 min2,356886  0% 0% 0% 100%
159PHP #2 7 min7 min3,3361006  0% 0% 0% 100%
Haskell GHC Bad Output1421
Haskell GHC #4 Bad Output1413
"wrong" (different) algorithm / less comparable programs
0.7Perl #5 1.881.8824,9521113
0.9C gcc #2 2.422.424921169
5.0Haskell GHC #3 13.5913.602,1161408

 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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