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 2.690.77262,7641009  92% 86% 83% 87%
1.0PyPy 2 2.690.78264,1481009  87% 84% 87% 91%
1.1PyPy 2 2.720.82262,1521009  79% 81% 80% 94%
1.1PyPy 3 #2 2.860.83267,9521008  81% 99% 82% 84%
1.1PyPy 3 #2 2.860.83266,3201008  82% 98% 81% 85%
1.2PyPy 3 2.940.94267,7721271  75% 76% 88% 77%
1.2PyPy 3 #2 2.890.94267,7361008  75% 74% 88% 72%
1.3PyPy 3 2.990.99266,6961271  90% 70% 73% 71%
1.3PyPy 3 3.011.00265,7961271  69% 73% 90% 72%
1.3PyPy 3 #3 3.531.03268,984894  83% 96% 81% 83%
1.3PyPy 3 #3 3.601.04270,404894  86% 84% 95% 82%
1.4PyPy 3 #3 3.571.07268,268894  80% 81% 79% 96%
1.5PyPy 3 #4 4.011.13273,9921069  87% 86% 99% 82%
1.5PyPy 3 #6 1.171.1756,524552  0% 100% 0% 1%
1.5PyPy 3 #6 1.171.1756,516552  100% 1% 0% 0%
1.5PyPy 3 #6 1.171.1856,892552  0% 1% 0% 100%
1.5PyPy 3 #4 3.941.19272,3001069  96% 76% 80% 79%
1.6PyPy 3 #4 4.061.24271,8041069  80% 92% 76% 81%
3.5Cython 10.202.6653,6121027  96% 97% 94% 98%
3.5Cython 10.102.6654,4161027  95% 95% 92% 97%
3.5Nuitka #4 10.042.6762,4961069  95% 94% 91% 97%
3.5Nuitka #3 10.002.6760,636894  94% 96% 91% 94%
3.5Cython 10.162.6952,7681027  93% 94% 94% 97%
3.5Nuitka #4 10.112.7060,7561069  95% 93% 97% 90%
3.5Nuitka #3 10.022.7159,956894  92% 93% 96% 89%
3.5Nuitka #3 10.082.7258,700894  89% 97% 92% 93%
3.5Nuitka #4 10.142.7261,0441069  94% 92% 97% 90%
3.5Pyston 10.352.73158,5601009  95% 93% 99% 94%
3.7Pyston 10.382.83157,8721009  92% 89% 95% 91%
3.8Pyston 10.422.89157,5841009  87% 90% 89% 96%
4.3Python 3 #3 12.423.3153,996894  93% 91% 98% 93%
4.3Python 3 #3 12.483.3253,564894  94% 92% 97% 93%
4.3Python 3 #3 12.493.3253,548894  97% 92% 95% 93%
4.4Python 3 #4 12.833.3652,6561069  94% 97% 95% 97%
4.4Python 3 #4 12.993.3951,9641069  95% 97% 99% 92%
4.4Python 3 #4 12.913.3952,7081069  95% 96% 98% 92%
4.8Nuitka #2 14.003.6760,0401008  97% 95% 96% 93%
4.8Nuitka #2 14.063.7261,0201008  97% 92% 95% 94%
4.8Nuitka #2 14.153.7259,7961008  92% 96% 94% 98%
4.9Python development version #3 14.293.7649,848894  96% 95% 96% 92%
4.9Python development version #3 14.273.7851,924894  95% 94% 92% 97%
4.9Python development version #3 14.453.8151,844894  98% 95% 96% 92%
5.0Python development version #4 14.823.8649,7201069  98% 96% 97% 93%
5.0Python development version #4 14.763.8649,7761069  97% 96% 93% 98%
5.1Python development version #4 15.003.9151,8081069  94% 99% 95% 96%
5.4Python 2 15.914.1342,7081009  95% 97% 96% 98%
5.4Python 2 16.224.1642,2281009  99% 98% 95% 98%
5.5Nuitka 16.454.2761,8041271  95% 98% 96% 97%
5.6Nuitka 16.514.3260,7721271  94% 99% 95% 95%
5.6Nuitka 16.614.3257,8841271  94% 98% 95% 97%
5.6Python 2 16.654.3442,0441009  95% 96% 95% 97%
5.8Nuitka #6 4.494.4910,564552  100% 0% 0% 0%
5.8Nuitka #6 4.504.5010,160552  0% 100% 0% 0%
5.8Nuitka #6 4.504.5010,596552  0% 100% 0% 0%
6.0Python 3 #2 18.274.6652,5161008  98% 98% 99% 97%
6.1Python 3 #2 18.334.7152,2001008  97% 99% 98% 96%
6.2Python 3 #2 18.334.7753,4841008  96% 97% 97% 95%
7.2Python development version #2 21.025.5249,6961008  96% 97% 93% 95%
7.3Python development version #2 21.555.6149,6761008  98% 96% 97% 94%
7.3Python development version #2 21.705.6149,7201008  98% 94% 98% 96%
7.5Python 3 22.335.7852,5441271  96% 97% 96% 98%
7.5Python 3 22.405.8052,6681271  98% 95% 97% 96%
7.6Python 3 22.665.8753,4161271  97% 95% 98% 96%
7.7Python 3 #6 5.925.928,580552  1% 100% 0% 0%
7.7Python 3 #6 5.955.958,568552  0% 19% 0% 81%
7.9Python 3 #6 6.066.068,560552  0% 0% 100% 0%
8.5Python development version 25.536.5751,8801271  98% 97% 98% 96%
8.6Python development version 25.526.6051,8161271  97% 97% 95% 98%
9.0Python development version 26.616.9150,0361271  97% 95% 97% 96%
9.1Python development version #6 6.997.007,676552  0% 0% 100% 0%
9.1Python development version #6 7.027.027,660552  0% 33% 0% 67%
9.3Python development version #6 7.167.167,476552  100% 0% 0% 0%
11MicroPython #6 8.258.254,240552  0% 81% 0% 19%
11MicroPython #6 8.268.264,248552  0% 11% 0% 89%
11MicroPython #6 8.298.294,176552  100% 0% 0% 0%
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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