fasta benchmark ≈240MB N=25,000,000

Each chart bar shows how many times more Memory, one ↓ fasta program used, compared to the program that used least Memory.

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.

    sortsort sort
  ×   Program Source Code CPU secs Elapsed secs Memory KB Code B ≈ CPU Load
1.0Pascal Free Pascal #4 7.937.9381112  0% 100% 1% 0%
32Fortran Intel 6.346.352521155  0% 0% 1% 100%
33Fortran Intel #4 3.183.192601327  0% 0% 2% 100%
36C gcc #5 3.293.292841261  2% 1% 1% 100%
36C gcc #4 5.055.052841221  1% 100% 1% 1%
36C gcc 7.047.042841185  0% 100% 0% 1%
36C++ g++ #4 6.566.562841266  0% 0% 1% 100%
66Fortran Intel #3 4.544.555241190  0% 0% 1% 100%
78C++ g++ 4.744.756201033  0% 100% 1% 2%
78C++ g++ #2 4.284.286201105  0% 100% 0% 1%
97Go 16.4516.457721036  0% 0% 100% 1%
109C++ g++ #3 4.214.228721286  0% 100% 0% 1%
151Ada 2005 GNAT 9.099.101,2081346  1% 0% 100% 1%
151Ada 2005 GNAT #5 4.244.241,2082186  0% 1% 1% 100%
173C gcc #6 5.221.801,3841914  96% 89% 99% 9%
207OCaml #3 12.1612.171,6561042  1% 0% 1% 100%
285Perl #2 7 min7 min2,280886  62% 0% 38% 0%
285Perl #4 5 min5 min2,280934  1% 0% 100% 1%
308Haskell GHC #2 3.943.662,464979  4% 100% 3% 4%
324PHP #3 148.94152.272,5881030  42% 27% 10% 21%
324PHP #2 6 min6 min2,5921006  39% 13% 5% 45%
541Python 3 #2 241.56246.324,324788  30% 24% 15% 33%
541Python 3 248.61253.034,324792  22% 24% 25% 31%
585Rust 4.994.994,6761224  1% 1% 0% 100%
674Ruby #5 235.44235.545,388987  47% 18% 37% 0%
966Lisp SBCL #3 11.8811.887,7281579  1% 1% 100% 0%
998Lisp SBCL #6 8.208.217,9801751  1% 1% 0% 100%
1,082Erlang HiPE 95.1095.128,6561039  99% 0% 2% 0%
1,099Erlang HiPE #2 49.7449.758,7881164  0% 100% 0% 1%
2,046Racket 50.6350.6216,3641054  0% 1% 100% 0%
2,208Racket #3 13.9013.9117,6601276  0% 0% 100% 0%
2,371Dart 8.918.8518,9641386  1% 1% 1% 100%
2,427C# Mono #2 7.167.1719,4121180  1% 100% 1% 1%
2,550F# Mono 10.1210.1220,400978  1% 0% 100% 1%
2,755Java  #4 5.145.0622,0401507  2% 1% 3% 98%
2,837Java  #2 7.927.8122,6961240  1% 8% 92% 1%
2,944Scala 10.3810.2423,5521080  1% 16% 85% 1%
2,964Scala #3 6.506.3923,7081053  5% 97% 2% 1%
3,144Lisp SBCL #2 16.1216.1325,1521617  1% 1% 100% 0%
3,145Lisp SBCL 14.7014.7125,1561419  0% 1% 1% 100%
3,638Java  #5 5.231.7329,1042457  70% 68% 95% 70%
5,421C# Mono #4 9.589.5943,3681505  1% 90% 0% 11%
6,837Clojure #6 11.089.6954,6961653  6% 7% 96% 7%
7,527Clojure #5 13.0011.2660,2161839  5% 10% 96% 7%
12,495Perl 116.40116.4599,960838  0% 94% 0% 7%
23,174Ruby #2 5 min5 min185,388732  0% 1% 42% 59%
24,918Ruby #4 240.02240.25199,340904  32% 42% 26% 2%
76,314Ruby JRuby 234.92229.49610,508760  31% 16% 21% 38%
Haskell GHC #4 Bad Output1413
Haskell GHC Bad Output1421
OCaml #6 Failed1161
"wrong" (different) algorithm / less comparable programs
50C gcc #2 2.462.464001169
243Haskell GHC #3 12.5911.571,9401408
1,914Perl #5 2.302.3015,3081113

 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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