fannkuch-redux benchmark N=12

Each chart bar shows how many times more Code, one ↓ fannkuch-redux program used, compared to the program that used least Code.

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.

    sortsortsort 
  ×   Program Source Code CPU secs Elapsed secs Memory KB Code B ≈ CPU Load
1.0Ruby 47 min47 min5,172384  97% 1% 4% 0%
1.0Ruby JRuby 50 min50 min658,916384  32% 20% 19% 32%
1.0Python 3 #6 45 min45 min4,180385  0% 100% 1% 1%
1.1PHP #2 40 min40 min2,556441  99% 1% 1% 2%
1.2Perl 46 min46 min1,768457  21% 0% 79% 1%
1.2Scala 100.0099.9422,296459  1% 99% 0% 1%
1.2OCaml #2 83.3483.36604473  0% 1% 1% 100%
1.3PHP 53 min53 min2,588482  0% 1% 1% 100%
1.3Dart #2 76.6076.0120,856495  0% 2% 2% 100%
1.3C gcc 57.8857.90316508  0% 100% 1% 1%
1.3Lisp SBCL #2 159.13159.2141,084513  1% 0% 100% 1%
1.3Java  #2 75.3675.3220,052514  1% 1% 100% 0%
1.4C# Mono 88.8288.8418,624520  0% 100% 1% 0%
1.4OCaml 154.52154.55604524  1% 1% 1% 100%
1.4F# Mono #2 102.17102.2020,968548  0% 100% 0% 1%
1.4F# Mono 168.29168.2423,536551  1% 51% 50% 1%
1.4Haskell GHC 10 min8 min9,592553  25% 44% 18% 42%
1.5C# Mono #2 64.4964.5118,616564  1% 0% 100% 0%
1.5Perl #2 39 min9 min12,380565  100% 100% 99% 99%
1.5C gcc #3 47.9847.99316567  0% 100% 1% 1%
1.5Fortran Intel 66.4266.43520590  0% 1% 1% 100%
1.5C++ g++ #3 57.9157.93284593  1% 0% 0% 100%
1.6F# Mono #4 72.0872.1119,124612  0% 1% 100% 1%
1.7Racket 5 min5 min16,876649  0% 26% 1% 75%
1.7Haskell GHC #4 89.3686.6210,088658  2% 1% 1% 100%
1.8Lisp SBCL #5 62.3462.3621,860674  0% 0% 100% 0%
2.1Haskell GHC #2 7 min143.655,020808  75% 76% 75% 75%
2.1Lisp SBCL #3 68.5768.5917,068821  1% 0% 1% 100%
2.2Haskell GHC #5 80.2520.473,712834  98% 99% 95% 100%
2.3Go 103.1825.97760900  99% 99% 100% 100%
2.4Racket #2 5 min5 min22,432903  0% 1% 100% 0%
2.4C gcc #5 38.269.75340910  100% 99% 99% 95%
2.5Python 3 #4 43 min10 min28,068944  100% 99% 98% 98%
2.5F# Mono #3 125.0432.7623,212945  93% 98% 95% 97%
2.6OCaml #4 0.0133.609,4281004  100% 100% 100% 100%
2.6Scala #2 60.3615.4223,1041017  98% 97% 98% 98%
2.6OCaml #3 0.0127.0818,9601017  100% 100% 100% 100%
2.7Pascal Free Pascal 67.5416.936961018  100% 100% 100% 100%
2.7Erlang HiPE 6 min102.5312,9441038  100% 98% 98% 100%
2.8Clojure #2 258.8076.9156,9041088  85% 85% 83% 83%
2.9Racket #3 5 min83.6318,3761096  97% 99% 98% 100%
2.9C# Mono #3 114.9829.2819,7881096  99% 99% 98% 98%
3.0Fortran Intel #3 75.1818.8512,4641148  100% 100% 100% 100%
3.0C++ g++ #7 27.2727.282841150  0% 100% 0% 1%
3.0PHP #3 41 min10 min10,5161150  100% 99% 99% 100%
3.0Haskell GHC #3 54.3613.893,4241153  98% 98% 100% 95%
3.1C gcc #4 27.2627.273161183  0% 0% 1% 100%
3.1Rust 45.7511.6910,9601188  95% 98% 100% 99%
3.3Java  64.3816.3319,9081282  98% 100% 98% 99%
3.7Ruby #2 1h 13 min18 min18,5281426  98% 96% 100% 97%
3.7Ruby JRuby #2 46 min13 min784,8201426  95% 89% 88% 90%
3.7C++ g++ #4 52.4813.371,0361439  100% 100% 99% 95%
3.8C++ g++ #5 50.0312.881,0361440  99% 99% 100% 99%
3.9Clojure #3 144.5937.0253,3361491  97% 98% 99% 97%
4.0Lisp SBCL #4 61.3815.7925,4961518  95% 98% 98% 99%
4.1C gcc #2 54.7714.243441557  91% 98% 100% 96%
5.5Ada 2005 GNAT #3 39.299.871,6562100  100% 100% 100% 100%
C++ g++ Failed1059
Rust #2 Make Error1102
"wrong" (different) algorithm / less comparable programs
1.8C# Mono #4 86.1686.1718,884710
2.0Python 3 #3 2286.85578.4928,040773
2.3C++ g++ #6 36.5036.52284894
3.6C# Mono #5 113.5828.8921,0721400
4.2Lisp SBCL 53.3413.4932,3641607
4.3Java  #3 46.2911.7622,5801633

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

You can write your own program for this task and contribute to the benchmarks game by following these general instructions.

More specifically:

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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