fannkuch-redux benchmark N=10

Each chart bar shows how many times slower, one ↓ fannkuch-redux 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 2 2.820.89285,6001009  78% 75% 97% 72%
1.0PyPy 2 2.830.90288,1481009  82% 76% 76% 86%
1.1PyPy 2 2.860.9480,4041009  71% 72% 67% 96%
1.4PyPy 3 3.201.2575,8041271  63% 65% 57% 81%
1.4PyPy 3 #2 3.181.2675,1961008  62% 92% 64% 62%
1.4PyPy 3 #2 3.181.2775,3401008  98% 64% 68% 63%
1.5PyPy 3 #6 1.261.2864,424552  9% 16% 84% 6%
1.5PyPy 3 #6 1.291.3164,796552  9% 8% 98% 10%
1.5PyPy 3 #2 3.221.3475,1681008  67% 86% 93% 70%
1.5PyPy 3 #6 1.321.3564,788552  17% 47% 13% 66%
1.6PyPy 3 3.301.3877,5401271  61% 58% 91% 59%
1.6PyPy 3 3.321.3877,4721271  59% 91% 57% 58%
1.6PyPy 3 #3 3.921.4175,144894  64% 96% 65% 66%
1.6PyPy 3 #3 3.861.4576,144894  69% 88% 64% 65%
1.7PyPy 3 #3 3.941.5275,412894  59% 60% 66% 90%
1.9PyPy 3 #4 4.361.6675,5201069  69% 69% 93% 69%
1.9PyPy 3 #4 4.431.6775,3921069  85% 70% 66% 75%
2.0PyPy 3 #4 4.451.8175,2161069  70% 92% 73% 75%
3.0Cython 10.052.6654,9081027  94% 96% 96% 98%
3.0Cython 10.032.6653,6281027  96% 94% 97% 97%
3.0Cython 10.092.6654,4561027  99% 96% 93% 98%
3.1Pyston 10.352.73158,5601009  95% 93% 99% 94%
3.1Nuitka #4 10.212.7861,4241069  96% 93% 98% 97%
3.2Nuitka #3 10.042.8060,280894  92% 94% 93% 95%
3.2Nuitka #3 10.082.8060,528894  95% 95% 94% 92%
3.2Nuitka #3 10.112.8260,452894  97% 90% 95% 93%
3.2Pyston 10.382.83157,8721009  92% 89% 95% 91%
3.3Pyston 10.422.89157,5841009  87% 90% 89% 96%
3.4Nuitka #4 10.903.0061,3681069  93% 96% 95% 96%
3.4Nuitka #4 10.743.0462,0441069  92% 94% 91% 96%
3.7Python 3 #3 12.623.2953,628894  99% 94% 98% 97%
3.8Python 3 #3 12.573.3353,100894  95% 96% 98% 92%
3.8Python 3 #3 12.653.4053,480894  91% 96% 93% 96%
3.9Python 3 #4 13.083.4152,7641069  97% 97% 99% 94%
3.9Python 3 #4 13.033.4754,1121069  95% 96% 92% 95%
4.0Python 3 #4 13.083.5354,4001069  93% 95% 93% 93%
4.3Python development version #3 14.293.7649,848894  96% 95% 96% 92%
4.3Python development version #3 14.273.7851,924894  95% 94% 92% 97%
4.3Python development version #3 14.453.8151,844894  98% 95% 96% 92%
4.4Python development version #4 14.823.8649,7201069  98% 96% 97% 93%
4.4Python development version #4 14.763.8649,7761069  97% 96% 93% 98%
4.4Python development version #4 15.003.9151,8081069  94% 99% 95% 96%
4.5Nuitka #2 14.504.0260,8441008  96% 95% 94% 95%
4.7Nuitka #2 14.864.1360,6681008  95% 92% 95% 93%
4.7Python 2 15.914.1342,7081009  95% 97% 96% 98%
4.7Nuitka #2 14.964.1660,9441008  93% 92% 98% 95%
4.7Python 2 16.224.1642,2281009  99% 98% 95% 98%
4.9Python 2 16.654.3442,0441009  95% 96% 95% 97%
5.1Nuitka 16.824.5458,6401271  96% 97% 97% 96%
5.1Nuitka 16.554.5558,6241271  97% 93% 96% 96%
5.2Nuitka 16.674.5959,5561271  95% 95% 96% 97%
5.3Nuitka #6 4.644.6610,476552  5% 6% 100% 4%
5.3Nuitka #6 4.674.6810,512552  6% 51% 53% 5%
5.3Nuitka #6 4.714.7310,200552  34% 6% 56% 24%
5.4Python 3 #2 18.444.7753,6321008  99% 96% 99% 98%
5.4Python 3 #2 18.324.8053,9081008  97% 95% 99% 97%
5.5Python 3 #2 18.244.8653,8041008  96% 95% 94% 96%
6.2Python development version #2 21.025.5249,6961008  96% 97% 93% 95%
6.3Python 3 21.375.5753,5441271  98% 97% 98% 95%
6.3Python 3 21.515.5954,0801271  96% 97% 96% 99%
6.3Python development version #2 21.555.6149,6761008  98% 96% 97% 94%
6.3Python development version #2 21.705.6149,7201008  98% 94% 98% 96%
6.4Python 3 21.375.6253,3201271  96% 97% 98% 96%
6.8Python 3 #6 5.975.989,024552  2% 2% 1% 100%
6.8Python 3 #6 6.016.029,048552  2% 1% 100% 1%
6.8Python 3 #6 6.036.048,844552  100% 1% 1% 1%
7.4Python development version 25.536.5751,8801271  98% 97% 98% 96%
7.5Python development version 25.526.6051,8161271  97% 97% 95% 98%
7.8Python development version 26.616.9150,0361271  97% 95% 97% 96%
7.9Python development version #6 6.997.007,676552  0% 0% 100% 0%
7.9Python development version #6 7.027.027,660552  0% 33% 0% 67%
8.1Python development version #6 7.167.167,476552  100% 0% 0% 0%
9.6MicroPython #6 8.438.464,188552  87% 15% 7% 6%
9.7MicroPython #6 8.548.584,048552  6% 58% 6% 49%
9.8MicroPython #6 8.618.654,192552  88% 19% 7% 7%
missing benchmark programs
Jython No program
IronPython No program
Shedskin No program
Numba No program
Grumpy No program

 fannkuch-redux benchmark : Indexed-access to tiny integer-sequence

diff program output N = 7 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.

For N = 7 programs should generate these permutations (40KB) - which, incidentally, seem to be in the same order as permutations generated by the Tompkins-Paige algorithm, see pages 150-151 Permutation Generation Methods Robert Sedgewick.

The fannkuch benchmark is defined by programs in Performing Lisp Analysis of the FANNKUCH Benchmark, Kenneth R. Anderson and Duane Rettig.

Each program should

The conjecture is that this maximum count is approximated by n*log(n) when n goes to infinity.

FANNKUCH is an abbreviation for the German word Pfannkuchen, or pancakes, in analogy to flipping pancakes.


Thanks to Oleg Mazurov for insisting on a checksum and providing this helpful description of the approach he took -

Revised BSD license

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