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- all benchmarks - binary-trees chameneos-redux fannkuch fasta k-nucleotide mandelbrot meteor-contest n-body nsieve nsieve-bits partial-sums pidigits recursive regex-dna reverse-complement spectral-norm startup sum-file thread-ring - all languages - Ada 2005 GNAT C Cyclone C GNU gcc C Tiny C# Mono C++ GNU g++ Clean D Digital Mars D GNU Dylan Gwydion Eiffel SmartEiffel Erlang HiPE Forth bigForth Forth GNU GForth Fortran G95 Haskell GHC Icon Io Java 1.4 -server Java 6 -client Java 6 -server Java 6 -Xint Java GNU gcj JavaScript JavaScriptCore JavaScript SpiderMonkey Lisp SBCL Lua Matlab GNU Octave Mozart/Oz Nice Oberon-2 OO2C Objective-C GNU OCaml OCaml (bytecode) Parrot PIR Pascal Free Pascal Perl PHP Pike Prolog SWI Python CPython Python IronPython Python Psyco Rexx Regina Ruby MRI S-Lang Scala Scheme Bigloo Scheme Chicken Scheme PLT Smalltalk GNU SML MLton SML SML/NJ Tcl

"For every complex problem there is an answer that is clear, simple, and wrong."  H. L. Mencken

What fun! Increase the Code multiplier! Ignore Memory! Zero out those benchmarks that push your favourite language to the bottom!

Which balance between Code-used and Time-used and Memory-used is best for you? Zero out those benchmarks which are unlike what your programs do!

×   language implementation GM missing 1.0 C GNU gcc 1.12   1.1 C++ GNU g++ 1.29   1.3 D GNU 1.44 1 1.3 D Digital Mars 1.47   1.5 Eiffel SmartEiffel 1.65 4 1.5 Oberon-2 OO2C 1.65 6 1.5 Pascal Free Pascal 1.67   1.5 Clean 1.70 3 1.7 OCaml 1.89 2 1.7 C Tiny 1.96 3 1.8 Java 1.4 -server 2.07 1 1.8 SML MLton 2.07 2 1.9 Java 6 -server 2.16 1 1.9 SML SML/NJ 2.18 7 2.0 Java 6 -client 2.20 2 2.0 Ada 2005 GNAT 2.24 4 2.0 Objective-C GNU 2.24 7 2.2 Lisp SBCL 2.53 1 2.5 Scala 2.81   2.6 C# Mono 2.87   3.0 Java GNU gcj 3.39 1 3.0 Nice 3.42 5 3.2 Fortran G95 3.55 4 3.7 Haskell GHC 4.21 3 5.8 Python Psyco 6.55 1 13 Forth GNU GForth 14.11 2 13 Erlang HiPE 14.60 2 13 Pike 14.61 5 14 OCaml (bytecode) 15.46 2 14 Parrot PIR 15.51 4 17 Java 6 -Xint 18.93 2 17 Lua 18.97 2 18 Python CPython 19.69 1 18 Scheme PLT 19.74 3 19 Scheme Chicken 21.03 7 19 S-Lang 21.42 6 25 Mozart/Oz 28.42   26 Perl 28.74 1 33 Smalltalk GNU 37.03 2 34 JavaScript JavaScriptCore 37.67 4 39 Python IronPython 43.51 6 41 JavaScript SpiderMonkey 46.24 3 57 Tcl 63.82 2 61 PHP 68.64 2 62 Ruby MRI 70.26   115 Prolog SWI 129.08 5

data for largest N full data - smaller and largest N multipliers Time secs Memory KB Code B benchmark weight binary-trees chameneos-redux fannkuch fasta k-nucleotide mandelbrot meteor-contest n-body nsieve nsieve-bits partial-sums pidigits recursive regex-dna reverse-complement spectral-norm startup sum-file thread-ring

 Which is best for you?

Which balance between Code-used and Time-used and Memory-used is best for you?

Read "How not to lie with statistics: the correct way to summarize benchmark results" (pdf).

For each benchmark, B is the best measurement; for each language implementation, the best measurement L is then normalized to ^L/_B

GM is the Weighted Geometric Mean of those ^L/_B ratios.

missing : Language implementations with more than a couple of Timeouts (at the largest workload) distort the ranking - so they have been excluded. They can still be compared directly against another language implementation.

There are other ways to analyse and present this data: ask Which programming languages have the fastest programs? or look for patterns in Code-used Time-used Shapes or take the Summary Data and do your own analysis!