"Samuel Walters" <swalters_usenet at yahoo.com> wrote in message
news:pan.2004. at yahoo.com...
As I see it, when one considers which language is best for one's needs,
one considers a couple of things:

1) Does the language have the semantics I want.
2) Does the language have the primitives I need.
3) Can I *easily* build any missing or suboptimal primitives. True.
One would assume that Fortran has the proper semantics for numerical
processing because it seems to have been wildly successful for a long
period of time.
That, in my opinion, is wrong: Fortran is successful because it was there

There exists a very large set of actively supported and proven libraries,
NAG f.ex., which nobody will ever bother to port to another language just
for the sake of it, and Fortran has been around for so long that it is well
understood how best to optimise and compile Fortran code. It is easy enough
to link with NAG if one needs to use it.
Fortran naturally comes with the primitives for numerical processing,
because numerical processing is its stated goal. ("FORmula TRANslation")
...or maybe the name sounded cool ;-)
Whether one uses Fortran, Python, or any other language, all primitives
are eventually implemented in either C or assembly. At some point or
another, we end up scraping bare metal and silicon to get our answers.
Exactly - Fortran in itself does not do something that another language
cannot do as well. It is just the case that Fortran is better understood
when applied to numering processing than other languages because more
"numerics" people used it than any other language.

On DSP architectures, f.ex., I doubt that one would have better performance
using Fortran in comparison with the C/C++ tools, DSP's usually ship with -
because DSP's were "born" when C/C++ was hot.

A lot of real, serious DSP work is done in Mathlab - thus skipping the issue
of language choice and getting right onto getting the job done. This is good

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