October 2012

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About a year ago, I wrote a simple prime testing algorithm to test the speed of several languages.   I just added Julia (windows binary) to the list.

Time Language

0.3  Julia
0.3  VB 6.0 Compiled
0.3  VC++ 6.0
0.4  Digital Mars C
0.5  GHC Haskell Compiled with -O2 flag
0.7  Netbeans 6.9 Java
0.8  VB 6.0 (Interpreted strong typed)
1.3  Mathematica 8 compiled with Compilation Target->”C” 
1.9  Matlab (R2010a)
2.5  GHC Haskell Compiled
3.6  “Compiled” Mathematica 8 
3.7  QiII SBC
5.0  Python IDLE 2.6.4
6    1992 Turbo C
7    Compiled PLT Scheme
7    VB 6.0 (Interpreted no type info)
7    Excel VBA (Iterp)
9    Clojure (Clojure Box 1.2 with type coersion)
11   "Compiled" Mathematica 7
19   PLT Scheme
20   netbeans python
20   ruby 1.8.6 for Windows
25   QiII Clisp
40   Emacs lisp using Cygwin
117  Mathematica 7
131  Mathematica 8
185  GHC Haskell Interactive Mode

If you are ready for more complexity classes, the complexity zoo is for you.

Andrew Ng / Stanford has a great wiki tutorial on sparse deep neural nets.




If you use the integer detection relation algorithm, please leave a comment on how you used it.  (The Euclidean algorithm does not count!)

I think the fast multipole algorithm is used by electrical engineers.  If you use it, please leave a comment.

I came across this video from NIPS 2011 titled “Big Learning – Algorithms, Systems, & Tools Workshop: Vowpal Wabbit Tutorial”.  Vowpal Wabbit is a fast machine learning toolbox for large data sets which uses stochastic gradient descent (i.e. perceptron algorithm), L-BFGS, and other ML algorithms.  Another video from NIPS 2011 describes spark, another tool for big data machine learning.

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