Simon Peyton-Jones writes:

> Another approach is to compete not head-to-head on speed, but on
> cunning.  Get a good library of numeric procedures (e.g. Mathlab),
> interface them to Haskell, and use Haskell as the glue code to make
> it really fast to write complex numerical algorithms.  99% of the
> time will still be spent in the library, so the speed of the Haskell
> implementation is not very important.  This looks like a jolly
> productive line to me.

I don't know if it is better to go with a commercial product here
(like Mathlab) or one of the semi-public domain (Reduce) or wholly
public domain tools here.  It would be a shame if Haskell were
publically available but the thing that made it useful for scientific
computing was not.

                                        Dave Barton <*>
                                        [EMAIL PROTECTED] )0(
                                        http://www.intermetrics.com/~dlb


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