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.

    sort sortsort
  ×   Program Source Code CPU secs Elapsed secs Memory KB Code B ≈ CPU Load
1.0Fortran Intel #4 2.692.702441327  0% 0% 0% 100%
1.3C gcc #5 3.403.403641261  1% 0% 1% 100%
1.3Haskell GHC #2 3.623.632,712979  0% 0% 0% 100%
1.4Haskell GHC #5 3.643.647,0961378  1% 1% 0% 100%
1.5Ada 2005 GNAT #5 4.104.111,4962186  1% 0% 0% 100%
1.6C++ g++ #3 4.234.231,0721286  1% 0% 1% 100%
1.6C gcc #6 4.324.329481914  1% 1% 0% 100%
1.6C++ g++ #2 4.434.448241105  0% 1% 1% 100%
1.7Fortran Intel #3 4.464.475081190  0% 0% 0% 100%
1.7C++ g++ 4.674.688281033  0% 1% 1% 100%
1.8Rust 4.904.904,9601214  0% 1% 0% 100%
2.0Java  #5 5.355.3632,9162457  0% 1% 1% 100%
2.0Java  #4 5.365.3726,1601507  1% 0% 1% 100%
2.2Fortran Intel 5.985.985081155  0% 1% 1% 100%
2.3C gcc #4 6.066.073641221  1% 1% 1% 100%
2.3Go #3 6.166.161,5521344  1% 0% 1% 100%
2.3Go #2 6.226.2210,1081388  0% 0% 1% 100%
2.3C++ g++ #4 6.246.253601266  1% 0% 1% 100%
2.3C# Mono #2 6.326.3220,2121180  0% 0% 1% 100%
2.4Haskell GHC #6 6.436.436,5641567  1% 0% 0% 100%
2.4Scala #3 6.456.4531,0041053  1% 1% 0% 100%
2.7C gcc 7.267.263641185  1% 0% 1% 100%
2.7Go 7.317.311,0241036  0% 1% 1% 100%
2.9Clojure #6 7.727.7367,4601653  1% 1% 1% 100%
2.9Lisp SBCL #6 7.797.808,8641751  1% 1% 0% 100%
3.1F# Mono 8.278.2723,544978  0% 1% 0% 100%
3.1Java  #2 8.348.3523,9961240  2% 0% 0% 100%
3.3Dart 9.009.0018,6841386  1% 0% 1% 100%
3.5C# Mono #4 9.319.3248,4561505  1% 1% 0% 100%
3.6Lisp SBCL #3 9.819.8210,6721579  1% 1% 0% 100%
3.9OCaml #6 10.5210.53201,7801161  0% 0% 0% 100%
4.0Scala 10.6810.6931,2201080  1% 1% 1% 100%
4.1Pascal Free Pascal #4 11.1311.1381112  1% 0% 0% 100%
4.4Ada 2005 GNAT 11.7711.781,4921346  1% 0% 1% 100%
4.4Clojure #5 11.8511.8671,4841839  1% 1% 0% 100%
5.0OCaml #3 13.4113.423,1241042  0% 0% 0% 100%
6.4Racket #3 17.2217.2324,5841276  0% 1% 0% 100%
6.6Lisp SBCL 17.8017.8110,6761419  1% 1% 0% 100%
6.7Lisp SBCL #2 18.1018.1110,6641617  1% 0% 0% 100%
9.5JavaScript V8 #2 25.6225.6542,532923  0% 1% 1% 100%
10Hack #4 27.3627.37330,5481109  0% 1% 1% 100%
11Erlang HiPE #2 30.5230.5313,3161164  1% 2% 0% 100%
16Hack #3 43.2043.22342,8641029  0% 1% 1% 100%
18Smalltalk VisualWorks 47.2447.2541,2841315  0% 0% 0% 100%
19Racket 49.9349.9621,4241054  0% 1% 1% 100%
23Erlang HiPE 60.7160.7415,0561039  1% 0% 0% 100%
23Hack #2 60.8160.8374,5681003  1% 0% 1% 100%
25JavaScript V8 67.4667.4810,392791  1% 0% 0% 100%
36Perl 96.4396.46100,036838  0% 0% 0% 100%
55Ruby #5 147.56147.637,672987  1% 1% 1% 100%
56PHP #3 148.29151.553,3321030  0% 0% 0% 100%
57Ruby #4 152.84152.99247,348904  1% 2% 2% 100%
59Python 3 156.10160.135,572792  1% 0% 0% 100%
63Python 3 #2 165.35170.105,580788  1% 0% 0% 100%
72Ruby #2 193.51193.58204,596732  0% 1% 0% 100%
74Ruby JRuby 198.39200.11661,884760  1% 1% 1% 100%
99Perl #4 267.46267.562,352934  0% 0% 0% 100%
146Perl #2 6 min6 min2,356886  0% 0% 0% 100%
160PHP #2 7 min7 min3,3361006  0% 0% 0% 100%
Haskell GHC Bad Output1421
Haskell GHC #4 Bad Output1413
Lua Failed1049
"wrong" (different) algorithm / less comparable programs
0.7Perl #5 1.881.8824,9521113
1.7C gcc #2 4.664.664921169
5.1Haskell GHC #3 13.6313.632,1041408

 fasta benchmark : Generate and write random DNA sequences

You can write your own program for this task and contribute to the benchmarks game by following these general instructions.

More specifically:

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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