fasta benchmark ≈24MB N=2,500,000

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
1.0PyPy 3 #4 1.791.7960,0001698  0% 1% 0% 100%
1.0PyPy 3 #4 1.811.8160,5641698  1% 0% 100% 1%
1.0PyPy 3 #4 1.821.8260,5201698  1% 67% 0% 34%
1.3PyPy 2 2.252.2574,940900  100% 0% 0% 0%
1.3PyPy 2 2.292.2974,796900  0% 0% 0% 100%
1.3PyPy 2 2.292.3074,988900  99% 0% 1% 0%
1.5PyPy 3 2.712.7168,996904  0% 100% 0% 0%
1.5PyPy 3 #2 2.722.7268,592889  0% 87% 0% 14%
1.5PyPy 3 2.722.7368,640904  100% 0% 0% 0%
1.5PyPy 3 #2 2.732.7468,112889  100% 0% 0% 0%
1.6PyPy 3 2.772.7768,448904  100% 0% 0% 0%
1.6PyPy 3 #2 2.852.8568,108889  99% 0% 0% 1%
1.7PyPy 3 #3 3.113.1160,2521647  100% 0% 0% 0%
1.7PyPy 3 #3 3.123.1260,6881647  0% 0% 100% 0%
1.8PyPy 3 #3 3.133.1360,2521647  0% 100% 0% 0%
1.9PyPy 3 #5 5.763.41296,5802016  40% 35% 57% 39%
1.9PyPy 3 #5 5.823.43296,3442016  40% 32% 57% 43%
1.9PyPy 3 #5 5.843.46296,2642016  36% 38% 60% 37%
2.3Python 3 #5 9.204.1479,4322016  73% 71% 57% 23%
2.4Python 3 #5 9.014.2372,0482016  80% 83% 32% 21%
2.4Python 3 #5 9.234.2481,3362016  68% 90% 22% 40%
2.4Cython 4.284.289,036945  100% 0% 0% 0%
2.4Cython 4.294.299,012945  100% 0% 0% 0%
2.4Cython 4.314.318,792945  0% 0% 100% 0%
2.5Python development version #5 9.874.4791,1282016  66% 73% 25% 57%
2.5Python development version #5 9.964.5189,8282016  61% 67% 75% 19%
2.6Python development version #5 10.034.5791,7162016  63% 73% 75% 10%
2.6Pyston 4.614.6132,988900  100% 0% 0% 0%
2.6Pyston 4.624.6333,028900  100% 0% 0% 0%
2.6Pyston 4.634.6332,960900  0% 26% 0% 74%
3.3Python 3 #4 5.985.988,8841698  0% 100% 0% 0%
3.4Python 3 #4 6.016.019,1041698  100% 0% 0% 0%
3.4Python 3 #4 6.016.018,8561698  71% 29% 0% 0%
3.6Python 2 6.406.4013,320900  0% 0% 100% 0%
3.6Python 2 6.466.4613,432900  0% 75% 0% 25%
3.6Python 2 6.466.4713,124900  0% 77% 23% 0%
3.6Python 3 #3 6.506.509,0841647  100% 0% 0% 0%
3.7Python 3 #3 6.526.529,0601647  0% 0% 100% 0%
3.7Python 3 #3 6.536.538,9681647  0% 0% 0% 100%
3.7Nuitka 6.696.6910,304904  0% 0% 0% 100%
3.8Nuitka #2 6.766.7610,452889  0% 0% 0% 100%
3.8Nuitka 6.786.7810,524904  0% 100% 0% 0%
3.8Nuitka #2 6.856.8510,212889  0% 0% 100% 0%
3.9Python development version #4 7.027.027,8201698  0% 94% 0% 6%
3.9Python development version #4 7.027.027,7761698  100% 0% 0% 0%
3.9Python development version #4 7.037.037,5201698  0% 25% 29% 46%
4.0Python development version #3 7.187.187,7721647  0% 19% 0% 81%
4.0Python development version #3 7.207.207,5361647  0% 100% 0% 0%
4.0Python development version #3 7.207.207,4921647  69% 0% 31% 0%
4.0Nuitka #2 7.227.2310,532889  0% 86% 0% 14%
4.3Nuitka 7.647.6510,324904  0% 0% 100% 0%
4.5Python 3 8.018.018,812904  0% 87% 0% 13%
4.5Python 3 8.078.079,044904  100% 0% 0% 0%
4.6Python 3 #2 8.178.188,804889  0% 56% 1% 44%
4.7Python 3 #2 8.378.379,048889  100% 0% 0% 0%
4.7Python 3 8.428.428,812904  0% 22% 0% 79%
4.8Python 3 #2 8.508.508,984889  0% 32% 0% 68%
4.9Python development version 8.688.687,732904  0% 51% 0% 49%
4.9Python development version 8.708.707,428904  0% 100% 0% 0%
4.9Python development version 8.788.787,480904  100% 0% 0% 0%
5.2Python development version #2 9.389.387,684889  0% 0% 100% 0%
5.3Python development version #2 9.419.417,640889  100% 0% 0% 0%
5.3Python development version #2 9.429.427,528889  0% 0% 0% 100%
12MicroPython 20.8220.824,188904  0% 60% 0% 40%
12MicroPython 20.8620.864,340904  100% 0% 0% 0%
12Jython 24.7620.91305,304900  41% 22% 27% 28%
12Jython 25.4021.24316,384900  31% 32% 36% 20%
12MicroPython 21.4921.504,228904  7% 6% 70% 17%
12MicroPython #2 21.8621.864,336889  0% 0% 100% 0%
12Jython 25.9521.93299,620900  21% 45% 29% 24%
12MicroPython #2 22.2722.274,196889  0% 17% 0% 83%
13MicroPython #2 22.5322.544,440889  11% 68% 0% 21%
missing benchmark programs
IronPython No program
Shedskin No program
Numba No program
Grumpy No program

 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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