regex-dna benchmark N=10,000

Each chart bar shows how many times slower, one ↓ regex-dna 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
1.0Python 2 #5 0.030.03?501  100% 0% 0% 0%
1.0Python 2 #5 0.030.03?501  0% 100% 0% 0%
1.3Python 2 #5 0.040.04?501  80% 0% 20% 0%
1.5Python development version #5 0.050.05?524  0% 100% 0% 0%
1.5Python development version #5 0.050.05?524  0% 0% 0% 100%
1.6Python development version #5 0.050.05?524  0% 0% 50% 67%
1.6Python 3 #5 0.050.05?524  0% 100% 0% 0%
1.6Python 3 #5 0.050.05?524  0% 100% 0% 0%
1.6Cython #5 0.050.05?524  0% 0% 0% 100%
1.6Python 3 #5 0.050.05?524  0% 100% 0% 0%
1.6Cython #5 0.050.05?524  0% 17% 100% 0%
1.6Cython #5 0.050.05?524  0% 100% 17% 0%
2.4Pyston #5 0.080.08?501  0% 0% 0% 100%
2.4Pyston #5 0.080.08?501  13% 0% 0% 100%
2.5Pyston #5 0.080.08?501  11% 13% 0% 89%
4.3PyPy 2 #5 0.140.14?501  100% 0% 0% 0%
4.3PyPy 2 #5 0.140.14?501  0% 7% 100% 7%
4.8Python 2 0.100.16?612  24% 13% 25% 27%
5.1Python 2 0.110.16?612  31% 6% 13% 6%
5.1PyPy 2 #5 0.160.16?501  0% 0% 94% 6%
5.2Python 2 0.110.17?612  13% 35% 12% 19%
5.3Python 3 0.110.17?573  47% 12% 6% 6%
5.3Python development version 0.120.17?573  17% 18% 24% 29%
5.7Python development version 0.130.18?573  11% 17% 50% 6%
5.7Python development version 0.130.18?573  12% 39% 11% 15%
5.8Nuitka 0.130.18?573  28% 35% 6% 15%
5.9Cython 0.150.19?573  33% 20% 17% 39%
6.0Nuitka 0.140.19?573  30% 11% 39% 15%
6.0Nuitka 0.140.19?573  11% 16% 55% 20%
6.2Cython 0.140.20?573  50% 11% 11% 5%
6.2Cython 0.140.20?573  10% 45% 5% 15%
6.2Python 3 0.140.20?573  10% 42% 20% 10%
6.3Python 3 0.140.20?573  10% 50% 14% 5%
6.6PyPy 3 #5 0.210.211,132524  38% 86% 100% 45%
6.9PyPy 3 #5 0.210.2210,172524  100% 100% 50% 64%
7.7Pyston 0.200.2594,660612  71% 21% 35% 27%
7.8Pyston 0.210.2594,996612  12% 23% 16% 60%
8.3Pyston 0.220.2694,520612  15% 62% 11% 12%
9.5PyPy 2 0.310.30204,672612  7% 69% 10% 13%
9.8PyPy 2 0.330.32204,116612  12% 10% 73% 13%
10PyPy 2 0.340.331,584612  41% 42% 9% 9%
16PyPy 3 #5 0.270.5259,944524  96% 94% 100% 96%
17PyPy 3 0.550.5470,868573  15% 83% 11% 11%
17PyPy 3 0.570.5669,772573  14% 11% 89% 9%
22IronPython #5 0.700.7046,832501  3% 29% 44% 32%
23IronPython #5 0.730.7344,844501  8% 3% 100% 5%
23IronPython #5 0.730.7345,660501  5% 100% 3% 6%
37PyPy 3 0.971.1774,292573  97% 99% 97% 95%
44Jython #5 3.401.41173,756501  50% 56% 52% 96%
44Jython #5 3.351.42176,284501  46% 92% 52% 57%
49Jython #5 3.701.57190,872501  69% 52% 72% 64%
missing benchmark programs
Shedskin No program
Numba No program
MicroPython No program
Grumpy No program

 regex-dna benchmark : Match DNA 8-mers and substitute nucleotides for IUB codes

diff program output for this 100KB input file (generated with the fasta program N = 10000) with this 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.

We use FASTA files generated by the fasta benchmark as input for this benchmark. Note: the file may include both lowercase and uppercase codes.

Each program should

Revised BSD license

  Home   Conclusions   License   Play