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 1.901.9066,5361698  1% 100% 1% 0%
1.0PyPy 3 #4 1.901.9066,7361698  69% 0% 31% 0%
1.0PyPy 3 #4 1.961.9666,8721698  43% 1% 58% 1%
1.2PyPy 2 2.342.3477,648900  1% 3% 100% 0%
1.2PyPy 2 2.362.3677,848900  0% 0% 3% 97%
1.3PyPy 2 2.382.3977,848900  0% 0% 100% 0%
1.4PyPy 3 #2 2.722.7269,860889  0% 100% 1% 1%
1.4PyPy 3 #2 2.722.7270,268889  0% 0% 0% 100%
1.4PyPy 3 2.732.7370,260904  52% 0% 48% 0%
1.4PyPy 3 2.752.7569,636904  65% 0% 37% 3%
1.5PyPy 3 #2 2.782.7869,520889  4% 97% 1% 0%
1.5PyPy 3 2.862.8669,404904  98% 0% 0% 2%
1.7PyPy 3 #3 3.203.2066,4161647  0% 1% 100% 0%
1.7PyPy 3 #3 3.223.2267,1681647  90% 1% 11% 1%
1.7PyPy 3 #3 3.243.2466,8401647  0% 3% 98% 0%
2.0PyPy 3 #5 6.253.8277,4882016  28% 51% 53% 34%
2.0PyPy 3 #5 6.273.8477,8442016  37% 81% 34% 14%
2.0PyPy 3 #5 6.263.8477,6642016  48% 34% 22% 63%
2.2Python 3 #5 8.964.2486,7282016  64% 68% 31% 52%
2.2Python 3 #5 9.284.2790,8202016  47% 75% 74% 25%
2.3Cython 4.284.289,036945  100% 0% 0% 0%
2.3Cython 4.294.299,012945  100% 0% 0% 0%
2.3Python 3 #5 9.494.2993,1562016  78% 54% 46% 48%
2.3Cython 4.314.318,792945  0% 0% 100% 0%
2.4Python development version #5 9.874.4791,1282016  66% 73% 25% 57%
2.4Python development version #5 9.964.5189,8282016  61% 67% 75% 19%
2.4Python development version #5 10.034.5791,7162016  63% 73% 75% 10%
2.4Pyston 4.614.6132,988900  100% 0% 0% 0%
2.4Pyston 4.624.6333,028900  100% 0% 0% 0%
2.4Pyston 4.634.6332,960900  0% 26% 0% 74%
3.1Python 3 #4 5.925.929,0841698  0% 100% 0% 0%
3.2Python 3 #4 6.116.119,0841698  0% 0% 0% 100%
3.3Python 3 #4 6.256.268,8841698  0% 0% 0% 100%
3.4Python 2 6.406.4013,320900  0% 0% 100% 0%
3.4Python 2 6.466.4613,432900  0% 75% 0% 25%
3.4Python 2 6.466.4713,124900  0% 77% 23% 0%
3.4Python 3 #3 6.526.529,1281647  1% 100% 0% 1%
3.4Python 3 #3 6.536.548,9401647  14% 1% 87% 0%
3.4Python 3 #3 6.556.558,9961647  13% 0% 87% 0%
3.6Nuitka 6.746.7410,588904  1% 100% 3% 2%
3.6Nuitka 6.766.7610,224904  2% 62% 3% 40%
3.6Nuitka #2 6.816.8210,528889  3% 69% 1% 33%
3.6Nuitka 6.816.8210,644904  1% 1% 100% 4%
3.6Nuitka #2 6.836.8310,300889  100% 4% 2% 1%
3.6Nuitka #2 6.866.8610,628889  100% 3% 3% 1%
3.7Python development version #4 7.027.027,7761698  100% 0% 0% 0%
3.7Python development version #4 7.027.027,8201698  0% 94% 0% 6%
3.7Python development version #4 7.037.037,5201698  0% 25% 29% 46%
3.8Python development version #3 7.187.187,7721647  0% 19% 0% 81%
3.8Python development version #3 7.207.207,5361647  0% 100% 0% 0%
3.8Python development version #3 7.207.207,4921647  69% 0% 31% 0%
4.1Python 3 7.737.748,948904  1% 1% 100% 1%
4.1Python 3 7.747.749,084904  0% 100% 0% 0%
4.1Python 3 7.867.869,172904  1% 1% 100% 1%
4.4Python 3 #2 8.348.359,084889  58% 0% 42% 0%
4.4Python 3 #2 8.368.369,036889  1% 100% 1% 0%
4.4Python 3 #2 8.388.399,036889  1% 100% 0% 0%
4.6Python development version 8.688.687,732904  0% 51% 0% 49%
4.6Python development version 8.708.707,428904  0% 100% 0% 0%
4.6Python development version 8.788.787,480904  100% 0% 0% 0%
4.9Python development version #2 9.389.387,684889  0% 0% 100% 0%
5.0Python development version #2 9.419.417,640889  100% 0% 0% 0%
5.0Python development version #2 9.429.427,528889  0% 0% 0% 100%
11MicroPython 20.8220.824,188904  0% 60% 0% 40%
11MicroPython 20.8620.864,340904  100% 0% 0% 0%
11Jython 24.7620.91305,304900  41% 22% 27% 28%
11Jython 25.4021.24316,384900  31% 32% 36% 20%
11MicroPython 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%
12MicroPython #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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