🚀 go-pugleaf

In article <l9p02vINNorv@almaak.usc.edu> ajayshah@almaak.usc.edu (Ajay Shah) writes:
>... I know
>exactly one person who uses parallel hardware.  Every single person I
>know who does scientific computation uses single-CPUs.

This just means you don't know people with big enough problems.

>Parallel hardware is obviously a way to get revolutionary gains in
>compute power, but Bill Joy's law suggests that single CPUs will give
>tremendous gains without paying any software irritations (they
>certainly have done great in the last five years).

There is a limit. Have you noticed that all the screaming "uniprocessors" are
going superscalar? SPARCs are already starting down the multiprocessing road.

Now I'm not trying to tell you that most scientific computing is parallel, or
anything similarly off-planet. But don't think that parallel computing is
going to go away anytime soon. Eventually, you hit the Boltzmann limit and then
the _only_ performance gain is parallelization. Your enthusiasm for single
CPU performance gains just means that you'll hit this wall sooner, rather than
later.
>
> I suspect most
>scientific computation out there does not know or care about parallel
>hardware.

You aren't talking about the major leaguers here, are you? In my experience,
places with graduate programs specializing in scientific computation are also
hotbeds of parallelization research and cross-fertilization.

Later,
Andrew Mullhaupt