Yes it's silly, but there were some worthwhile points:
a. Benchmarks require care. e.g. exclude the time to
generate the random numbers; in fact, exclude
everything you can except for the operations you
are comparing.
b. Regarding your second paragraph ("Does J reduce
thinking time? Not really in this case. ...")
Depends on what you mean by "this case".
b.1 It used to be that MatLab has a small limit (2 or 3)
on the rank (dimensionality) of an array, so that if you
want to do inner product of higher-ranked arrays J does
have a thinking advantage. In fact, knowing that there
is such a limit the thinking is more likely to be,
why would I want to do that?
b.2 J permits inner products on other operations, such
as ~:/ .* or *./ .> .
b.3 If you consider matrix inversion as part of "this case"
then the Hilbert matrix example may be a plus on the
J side. I don't whether MatLab can invert the 40-by-40
Hilbert matrix but if it does not have extended precision
it would not be able to.
det=: -/ .*
0j_10 ": det % 1 + +/~ i.40x
1.0971114170e_932
----- Original Message -----
From: John Randall <[EMAIL PROTECTED]>
Date: Friday, November 9, 2007 3:07
Subject: Re: [Jprogramming] Re: speed of matrix*vector operation
To: Programming forum <[email protected]>
> Are such contests silly? Yes, unless you are modelling the
> universe.Then you need better hardware.
>
> Does J reduce thinking time? Not really in this
> case. J and MATLAB
> have builtin functions for matrix multiplication and
> inversion. If
> you were writing in C, you would need a bit more thinking time for
> matrix multiplication and a lot more for inversion.
>
> Even though it is heresy, it may be the case that MATLAB can do
> matrix multiplication faster than J. The reason is the
> BLAS (Basic
> Linear Algebra Subprograms), used for linear algebra in scientific
> computing (for example, it underpins LAPACK). The BLAS is
> tuned to
> a particular CPU chip, since the algorithm used may depend on cache
> size, ability to pipeline, etc. Some versions will fine tune
> themselves from the actual system.
>
> MATLAB makes a big point of this, for example a feature of
> version 7.5
> is
>
> Upgraded Linear Algebra Package library (LAPACK 3.1) on all platforms,
> plus upgraded optimized Basic Linear Algebra Subprogram libraries
> (BLAS) on AMD processors (AMCL 3.6)
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