fannkuch-redux benchmark N=12

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

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.

    sortsort sort
  ×   Program Source Code CPU secs Elapsed secs Memory KB Code B ≈ CPU Load
1.0Fortran Intel 66.4266.43520590  0% 1% 1% 100%
1.1C++ g++ #3 57.3657.38564593  1% 1% 100% 1%
1.1C++ g++ #7 24.4424.455881150  0% 100% 1% 1%
1.2OCaml #2 83.3483.36604473  0% 1% 1% 100%
1.2OCaml 154.52154.55604524  1% 1% 1% 100%
1.3C gcc 73.8773.89656508  1% 0% 0% 100%
1.3C gcc #4 24.3324.346721183  100% 0% 0% 0%
1.3C gcc #3 48.2548.27680567  1% 0% 0% 100%
1.3Pascal Free Pascal 67.5416.936961018  100% 100% 100% 100%
1.5Go 103.1825.97760900  99% 99% 100% 100%
1.7C gcc #2 54.2814.138721557  100% 89% 99% 97%
2.7C gcc #5 39.4910.061,388910  99% 99% 95% 100%
2.7C++ g++ #5 50.9313.021,4121440  100% 94% 99% 100%
2.7C++ g++ #4 50.8613.041,4161439  99% 93% 98% 100%
3.4Perl 46 min46 min1,768457  21% 0% 79% 1%
4.9PHP #2 40 min40 min2,556441  99% 1% 1% 2%
5.0PHP 53 min53 min2,588482  0% 1% 1% 100%
6.6Haskell GHC #3 54.3613.893,4241153  98% 98% 100% 95%
7.1Haskell GHC #5 80.2520.473,712834  98% 99% 95% 100%
7.6Ada 2005 GNAT #3 50.4512.663,9282100  100% 100% 100% 100%
8.0Python 3 #6 45 min45 min4,180385  0% 100% 1% 1%
9.7Haskell GHC #2 7 min143.655,020808  75% 76% 75% 75%
10Ruby 47 min47 min5,172384  97% 1% 4% 0%
18OCaml #4 0.0133.609,4281004  100% 100% 100% 100%
18Haskell GHC 10 min8 min9,592553  25% 44% 18% 42%
19Haskell GHC #4 89.3686.6210,088658  2% 1% 1% 100%
20PHP #3 41 min10 min10,5161150  100% 99% 99% 100%
23Rust #2 46.6411.9012,2041191  98% 100% 95% 99%
24Perl #2 39 min9 min12,380565  100% 100% 99% 99%
24Fortran Intel #3 75.1818.8512,4641148  100% 100% 100% 100%
25Erlang HiPE 6 min102.5312,9441038  100% 98% 98% 100%
32Racket 5 min5 min16,876649  0% 26% 1% 75%
33Lisp SBCL #3 68.5768.5917,068821  1% 0% 1% 100%
35Racket #3 5 min83.6318,3761096  97% 99% 98% 100%
36Ruby #2 1h 13 min18 min18,5281426  98% 96% 100% 97%
36OCaml #3 0.0127.0818,9601017  100% 100% 100% 100%
40Dart #2 76.6076.0120,856495  0% 2% 2% 100%
42Lisp SBCL #5 62.3462.3621,860674  0% 0% 100% 0%
43Racket #2 5 min5 min22,432903  0% 1% 100% 0%
46Java  #2 73.9673.9223,796514  1% 1% 99% 1%
49Lisp SBCL #4 61.3815.7925,4961518  95% 98% 98% 99%
50Java  67.5617.1325,8041282  100% 98% 99% 98%
54Python 3 #4 43 min10 min28,068944  100% 99% 98% 98%
55Scala 101.06101.0028,520459  92% 8% 1% 1%
61Scala #2 66.0716.8631,8121017  98% 98% 99% 97%
74C# Mono #2 47.6647.6738,336564  1% 100% 1% 1%
74C# Mono 85.8285.8538,364520  0% 0% 100% 1%
76C# Mono #3 112.6428.7739,3641096  99% 99% 98% 96%
76F# Mono #4 69.9669.9839,508612  100% 1% 1% 0%
79Lisp SBCL #2 159.13159.2141,084513  1% 0% 100% 1%
79F# Mono #2 102.87102.9041,276548  1% 63% 38% 0%
81F# Mono 182.26182.4341,908551  1% 9% 92% 1%
90F# Mono #3 120.9632.4546,616945  94% 97% 87% 95%
103Clojure #3 144.5937.0253,3361491  97% 98% 99% 97%
109Clojure #2 258.8076.9156,9041088  85% 85% 83% 83%
1,271Ruby JRuby #2 43 min12 min661,1681426  91% 89% 98% 86%
1,305Ruby JRuby 20 min20 min678,724384  48% 16% 23% 16%
C++ g++ Make Error1059
"wrong" (different) algorithm / less comparable programs
1.2C++ g++ #6 36.3536.36628894
53Java  #3 41.2910.5327,3521633
54Python 3 #3 2286.85578.4928,040773
62Lisp SBCL 53.3413.4932,3641607
74C# Mono #4 93.0693.0938,584710
78C# Mono #5 133.3533.9940,5841400

 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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