From help-request at octave dot org Fri Feb 18 14:11:05 2005
Subject: Re: C++ using Octave headers, mkoctfile
From: Przemek Klosowski <przemek at jazz dot ncnr dot nist dot gov>
To: help at octave dot org, sct@ucsd.edu
Date: Fri, 18 Feb 2005 15:16:09 -0500 (EST)

Francesco said 

   > Perhaps, before trying to produce C++ code, you should try to learn how
   > to use Octave's vector abilities at their best.  For example, the code
   > you wrote can be vectorialised as:
   > 
   > N=30; W=exp(j*2*pi*[0:N-1]'*[1:N]/N);
   > 
   > and it runs faster.

   You are absolutely correct.  But this code snippet was to serve as an
   example only.  Let me simplify the question:

Francesco's point may have been obscured by his wording--so at a risk of
restating the obvious, I would like to observe this: on vectorized code,
octave takes a small interpretation hit when parsing the vector statement,
and then it dives into usually well-optimized execution loop, often simply
passing into super-optimized basic linear algebra library routines. 

The consequence of that is that hand-written C++ code might end up
being slower than a vectorized Octave statement---I will tip my hat to
anyone who can sit down and write competitive matrix multiplication code
in C++ that would outrun Atlas. I am not saying it's impossible, just unlikely;
after all, Atlas is known to be sometimes faster than vendor libraries.

I think that for optimization, the recommended course is to vectorize the
heck out of it, before rewriting. When rewriting, vectorization should be
actually helpful in writing concise and fast code.

I am reminded of those two rules of optimization that I have seen somewhere:

  Rule 1:   don't

  Rule 2:   not yet



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