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 3.141.0482,1801009  76% 73% 73% 90%
1.0PyPy 2 3.151.0981,9081009  73% 69% 90% 67%
1.0PyPy 2 3.151.0981,9721009  73% 93% 69% 67%
1.2PyPy 3 3.291.2779,3081271  61% 57% 91% 57%
1.2PyPy 3 #6 1.271.2968,184552  4% 74% 2% 25%
1.3PyPy 3 3.331.3079,2121271  60% 57% 90% 57%
1.3PyPy 3 3.331.3179,3241271  59% 92% 54% 55%
1.3PyPy 3 #6 1.281.3168,152552  31% 2% 3% 72%
1.3PyPy 3 #6 1.311.3368,248552  6% 2% 1% 99%
1.3PyPy 3 #2 3.401.3477,6081008  56% 96% 54% 55%
1.3PyPy 3 #2 3.371.3678,0681008  87% 64% 53% 52%
1.3PyPy 3 #2 3.411.3777,8441008  87% 52% 66% 51%
1.5PyPy 3 #3 4.311.5580,196894  68% 92% 62% 65%
1.6PyPy 3 #4 4.391.6178,8081069  66% 64% 92% 63%
1.6PyPy 3 #4 4.441.6279,2161069  64% 93% 63% 64%
1.6PyPy 3 #4 4.381.6278,6641069  65% 91% 58% 63%
1.6PyPy 3 #3 4.361.6280,616894  66% 91% 61% 61%
1.6PyPy 3 #3 4.331.6481,256894  93% 61% 62% 57%
2.6Pyston 10.352.73158,5601009  95% 93% 99% 94%
2.7Pyston 10.382.83157,8721009  92% 89% 95% 91%
2.8Pyston 10.422.89157,5841009  87% 90% 89% 96%
2.9Nuitka #3 11.763.0550,776894  98% 99% 97% 98%
2.9Nuitka #3 11.663.0651,008894  98% 98% 94% 99%
3.0Nuitka #4 11.923.0853,3881069  98% 99% 98% 98%
3.0Nuitka #3 11.793.1450,500894  98% 94% 97% 94%
3.1Graal #6 3.633.18434,028552  18% 41% 13% 48%
3.1Graal #6 3.653.20433,960552  18% 54% 7% 42%
3.1Graal #6 3.663.21434,020552  21% 81% 4% 15%
3.1Nuitka #4 12.103.2152,7641069  98% 95% 96% 95%
3.1Nuitka #4 12.113.2253,2161069  95% 95% 97% 94%
3.3Python 3 #3 13.033.4448,036894  97% 99% 91% 99%
3.3Python 3 #3 13.173.4747,392894  97% 99% 91% 99%
3.4Python 3 #3 13.093.4848,124894  100% 92% 96% 95%
3.4Python development version #3 13.233.5047,140894  98% 98% 92% 99%
3.4Python development version #3 13.263.5146,752894  99% 95% 96% 97%
3.4Python development version #3 13.363.5346,800894  98% 98% 93% 99%
3.4Python 3 #4 13.573.5547,9481069  94% 98% 98% 99%
3.4Python 3 #4 13.653.5847,5121069  98% 99% 92% 99%
3.5Python development version #4 13.623.5947,3441069  98% 99% 92% 99%
3.5Python development version #4 13.813.6046,6641069  98% 99% 96% 99%
3.5Python 3 #4 13.623.6348,6321069  99% 93% 95% 95%
3.5Python development version #4 13.893.6447,1441069  97% 100% 96% 99%
3.8Nuitka #2 14.953.9351,3121008  98% 96% 97% 96%
3.8Nuitka #2 15.243.9450,6281008  99% 98% 98% 98%
3.8Nuitka #2 15.073.9850,6521008  96% 96% 97% 95%
4.2Python 2 16.554.3741,9321009  97% 98% 96% 96%
4.2Python 2 16.304.3743,2921009  96% 95% 94% 95%
4.5Python 2 17.084.6543,6201009  97% 96% 98% 97%
4.5Nuitka 17.904.6952,7801271  98% 98% 95% 98%
4.5Nuitka 18.094.6952,2081271  99% 97% 98% 98%
4.5Nuitka #6 4.704.709,660552  5% 100% 0% 0%
4.5Nuitka 17.904.7151,8001271  96% 98% 98% 94%
4.6Nuitka #6 4.764.769,620552  4% 0% 100% 0%
4.6Nuitka #6 4.764.779,764552  5% 0% 100% 0%
4.7Python development version #2 18.364.8547,0001008  96% 99% 98% 95%
4.7Python development version #2 18.714.8646,5001008  99% 99% 99% 99%
4.8Python development version #2 18.554.9547,0241008  96% 98% 97% 94%
4.9Python 3 #2 19.625.0848,0881008  98% 99% 96% 99%
4.9Python 3 #2 19.305.1047,8561008  99% 94% 96% 96%
4.9Python 3 #2 19.765.1148,0241008  99% 99% 97% 99%
5.5Python development version 21.665.6647,5281271  99% 98% 96% 99%
5.5Python development version 21.515.7046,8321271  97% 99% 97% 93%
5.5Python development version 21.485.7046,9361271  96% 99% 97% 94%
5.8Python 3 23.276.0548,1321271  98% 99% 96% 99%
5.9Python 3 23.676.0848,0881271  99% 100% 98% 99%
5.9Python development version #6 6.106.117,832552  6% 1% 1% 100%
5.9Python 3 23.146.1247,5481271  100% 96% 96% 94%
5.9Python development version #6 6.166.167,788552  5% 1% 100% 1%
6.0Python development version #6 6.196.257,960552  26% 1% 78% 1%
6.0Python 3 #6 6.256.268,864552  4% 1% 100% 0%
6.0Python 3 #6 6.256.268,964552  5% 87% 1% 13%
6.1Python 3 #6 6.316.318,416552  5% 0% 100% 0%
8.1MicroPython #6 8.348.354,164552  1% 7% 100% 2%
8.3MicroPython #6 8.358.574,184552  31% 61% 1% 14%
8.3MicroPython #6 8.368.644,236552  1% 77% 2% 27%
missing benchmark programs
Jython No program
IronPython No program
Cython No program
Shedskin No program
Numba No program
Grumpy No program
RustPython 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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