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
1.0Haskell GHC #7 2.812.823,0121550  2% 1% 0% 100%
1.0C++ g++ #5 2.902.911,1881543  1% 1% 0% 100%
1.1Fortran Intel #4 2.992.992601327  1% 1% 1% 100%
1.1Haskell GHC #5 3.043.054,8521378  10% 54% 27% 100%
1.1C gcc #5 3.233.246641261  1% 0% 1% 100%
1.2Haskell GHC #2 3.303.302,476979  0% 2% 1% 100%
1.3C gcc #6 3.773.781,8281914  1% 1% 0% 100%
1.5C++ g++ #2 4.284.291,1321105  1% 0% 0% 100%
1.5Ada 2005 GNAT #5 4.314.311,7002186  1% 1% 0% 100%
1.5C++ g++ #3 4.324.331,1881286  1% 0% 0% 100%
1.6Fortran Intel #3 4.424.435241190  1% 0% 1% 100%
1.7Java  #4 4.804.8124,8361507  1% 1% 0% 100%
1.7C++ g++ 4.854.851,1361033  0% 1% 1% 100%
1.8Java  #5 4.974.9831,8482457  1% 1% 0% 100%
1.8C gcc #4 5.025.026641221  1% 0% 0% 100%
1.8Rust 5.155.156,0921211  1% 0% 0% 100%
2.1Haskell GHC #6 5.945.954,3201567  1% 1% 1% 100%
2.2C++ g++ #4 6.266.265961266  0% 1% 1% 100%
2.3Fortran Intel 6.336.345241155  0% 0% 1% 100%
2.3Scala #3 6.436.4429,8801053  1% 1% 1% 100%
2.3Go #3 6.536.531,5521344  1% 1% 1% 100%
2.5C gcc 7.047.056681185  1% 1% 0% 100%
2.7C# Mono #2 7.477.4839,4561180  0% 1% 1% 100%
2.7Java  #2 7.527.5325,1001240  1% 0% 1% 100%
2.8Lisp SBCL #6 7.847.857,8361751  1% 0% 1% 100%
2.8Pascal Free Pascal #4 7.937.9381112  1% 1% 0% 100%
3.0Ada 2005 GNAT 8.538.541,6361346  1% 0% 0% 100%
3.1Dart 8.708.7023,4921386  0% 1% 1% 100%
3.1Go 8.768.777641036  0% 0% 1% 100%
3.6C# Mono #4 10.2610.2798,4921505  0% 1% 1% 100%
3.7Scala 10.2910.3029,7361080  1% 0% 1% 100%
3.9Clojure #6 10.9610.9754,7841653  1% 1% 1% 100%
3.9F# Mono 10.9911.0040,608978  0% 0% 1% 100%
4.2Lisp SBCL #3 11.7211.737,8441579  0% 0% 1% 100%
4.2Go #2 11.8011.8110,2961388  0% 1% 1% 100%
4.3OCaml #3 12.0512.066001042  0% 0% 1% 100%
4.5Clojure #5 12.6012.6156,8961839  1% 1% 0% 100%
4.8Racket #3 13.4113.4222,1761276  1% 14% 2% 100%
5.3Lisp SBCL 14.8514.8624,4921419  0% 1% 0% 100%
5.7Lisp SBCL #2 16.0516.0624,4841617  1% 0% 1% 100%
7.9JavaScript V8 #2 22.2822.3029,800923  0% 1% 1% 100%
16Smalltalk VisualWorks 46.1246.1426,3681315  0% 0% 0% 100%
18Erlang HiPE #2 49.2249.2511,1481164  1% 0% 0% 100%
18Racket 50.4850.5019,1321054  0% 0% 0% 100%
26JavaScript V8 71.7471.768,488791  0% 1% 1% 100%
32Erlang HiPE 88.9488.9710,4641039  1% 0% 1% 100%
35Perl 99.6899.7251,388838  1% 0% 0% 100%
39Python 3 #3 108.42108.464,328977  0% 0% 1% 100%
42PHP #3 118.32118.362,5881030  0% 0% 1% 100%
45Python 3 #5 126.89127.022,477,1481933  1% 1% 0% 100%
82Python 3 229.21229.294,288792  1% 1% 1% 100%
82Ruby JRuby 231.53231.81633,836760  0% 1% 1% 100%
86Ruby #5 241.85241.945,080987  0% 1% 1% 100%
86Ruby #4 242.5216 min198,008904  1% 1% 0% 100%
90Perl #4 254.30254.402,264934  1% 1% 0% 100%
101Ruby #2 284.32284.41128,228732  0% 0% 1% 100%
117Perl #2 5 min5 min2,264886  1% 1% 0% 100%
132PHP #2 6 min6 min2,5841006  1% 0% 1% 100%
C CINT Bad Output1163
Haskell GHC #4 Bad Output1413
Haskell GHC Bad Output1421
Lua Failed1049
OCaml #6 Failed1161
"wrong" (different) algorithm / less comparable programs
0.7Perl #5 1.981.9814,9961113
0.9C gcc #2 2.402.401,2761169
4.2Haskell GHC #3 11.8311.831,9441408

 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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