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 2.442.445121327  1% 0% 1% 100%
1.4C gcc #5 3.293.297481261  0% 0% 1% 100%
1.4Haskell GHC #7 3.453.453,7761550  0% 1% 1% 100%
1.5Haskell GHC #2 3.623.632,712979  0% 0% 0% 100%
1.5Haskell GHC #5 3.643.647,0961378  1% 1% 0% 100%
1.7C gcc #6 4.054.051,9321914  1% 0% 0% 100%
1.7Ada 2005 GNAT #5 4.064.072,0242186  0% 0% 1% 100%
1.7C++ g++ #3 4.224.231,4961286  0% 1% 0% 100%
1.8Fortran Intel #3 4.314.315081190  1% 1% 1% 100%
1.8C++ g++ #2 4.444.441,4361105  1% 0% 1% 100%
1.9C++ g++ 4.664.671,4921033  0% 0% 1% 100%
2.1Rust 5.035.046,2681211  1% 0% 1% 100%
2.1Java  #4 5.145.1531,3761507  1% 1% 0% 100%
2.2Java  #5 5.425.4339,0242457  1% 0% 1% 100%
2.5Fortran Intel 6.036.035081155  1% 0% 0% 100%
2.5C gcc #4 6.036.048241221  2% 1% 0% 100%
2.5OCaml #6 6.046.05204,5201161  0% 1% 1% 100%
2.5Go #3 6.086.092,9121344  0% 1% 1% 100%
2.5C++ g++ #4 6.126.127481266  1% 0% 0% 100%
2.6Go #2 6.316.319,9921388  0% 0% 1% 100%
2.6C# Mono #2 6.366.3640,5441180  0% 1% 0% 100%
2.6Haskell GHC #6 6.436.436,5641567  1% 0% 0% 100%
2.9C gcc 7.037.038241185  1% 1% 1% 100%
2.9Go 7.187.181,7721036  0% 2% 1% 100%
3.1Scala #3 7.507.5136,7441053  0% 0% 1% 100%
3.1Lisp SBCL #6 7.627.626,8841751  1% 0% 0% 100%
3.2Clojure #6 7.727.7376,6081692  1% 1% 0% 100%
3.3Java  #2 8.018.0132,8681240  0% 1% 0% 100%
3.3Ada 2005 GNAT 8.058.051,9361346  1% 1% 0% 100%
3.5F# Mono 8.418.4242,192978  2% 0% 1% 100%
3.6OCaml #3 8.798.799601042  1% 0% 0% 100%
3.7Dart 9.029.0329,2081386  0% 1% 1% 100%
4.0Lisp SBCL #3 9.779.786,6321579  1% 1% 0% 100%
4.2C# Mono #4 10.0710.1486,8961505  0% 0% 1% 99%
4.5Clojure #5 10.8610.8780,1681964  0% 1% 1% 100%
4.5Scala 10.9810.9936,7281080  0% 0% 2% 100%
4.6Pascal Free Pascal #4 11.1311.1381112  1% 0% 0% 100%
7.1Racket #3 17.2517.2631,7361276  1% 0% 1% 100%
7.2Lisp SBCL #2 17.6117.626,6201617  1% 1% 0% 100%
7.3Lisp SBCL 17.7717.786,6201419  1% 1% 0% 100%
10JavaScript V8 #2 25.4725.5143,104956  0% 0% 1% 100%
11Hack #4 26.0526.07118,0121109  1% 1% 1% 100%
13Erlang HiPE #2 32.2032.2114,6561164  1% 0% 1% 100%
18Hack #3 43.2943.31118,1761029  0% 1% 1% 100%
20Smalltalk VisualWorks 47.8447.8654,1921315  1% 0% 0% 100%
22Hack #2 53.3053.32116,2721003  1% 1% 0% 100%
22Racket 53.3353.3623,0161054  0% 1% 0% 100%
23Rust #2 56.7656.7923,7201887  0% 1% 0% 100%
27JavaScript V8 66.2966.3213,228831  0% 0% 1% 100%
37Ruby JRuby #3 89.5889.69719,248973  1% 1% 1% 100%
39Python 3 #3 95.9796.005,628977  0% 1% 0% 100%
40Perl 96.5196.5452,084838  1% 0% 0% 100%
40Erlang HiPE 96.6096.6414,8761039  0% 1% 0% 100%
40Ruby #3 96.8796.9159,620973  1% 0% 1% 100%
48PHP #3 116.35116.383,3641030  0% 0% 1% 100%
64Ruby #5 155.80157.237,212987  1% 1% 1% 99%
65Ruby #4 158.45158.60235,044904  0% 1% 1% 100%
71Python 3 #5 120.02173.713,289,2481933  16% 11% 17% 98%
76Ruby #2 184.92184.99204,120732  1% 1% 1% 100%
82Python 3 198.82198.905,584792  1% 0% 1% 100%
82Ruby JRuby 198.39200.11661,884760  1% 1% 1% 100%
108Perl #4 261.37263.073,160934  1% 1% 1% 100%
148Perl #2 6 min6 min3,152886  1% 1% 0% 100%
152PHP #2 6 min6 min3,3721006  1% 1% 1% 100%
Haskell GHC Bad Output1421
Haskell GHC #4 Bad Output1413
Lua Failed1049
"wrong" (different) algorithm / less comparable programs
0.8Perl #5 1.881.8824,8721113
1.0C gcc #2 2.422.431,3441169
1.2C++ g++ #5 2.912.911,5121543
5.6Haskell 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

  Home   Conclusions   License   Play