🚀 go-pugleaf

I followed the articles for some time and want to mention some points.

1. Hardware costs are only a fraction of the cost. To do real big problems you
   need lots of support software and you relie on it. So if you use a PC
   you will have to write more code (or buy spezialised code at a high price)
   and trust your version. This is hard because numeric mathematic is not so
   easy as it seems and if your aircraft comes down or your bridge cracks, its
   to late to blame yourself.

2. Parallel computers will need a Pascal (C,Modula,Ada,..) like language, which
   can be compiled and run on a scalable architekture. Nobody wants to rewrite
   all programs, if he gets more processors. It would be even better to have
   it scaled at runtime, so the process runs faster, if the no other users want
   the processors too.
   I know only the Connection Machine doing that, and this machine is not as
   general purpose as a Workstation. (What OS has the CM ? What Languages ?
   Can you compile a CM program to work on other Computers ? (not simulated)

3. Some Problems are just to big for a PC. Even if you have a more
   sophisticated system then the normal Primitiv Computer, there are a lot
   of problems which have been scaled down to run on supercomputers. So further
   downscaling is not possible without a substantial loss of accuracy.
   (accuracy is not only the length of a floating point. Its how much points
    can your grids have? What differential equations are possible ? What about
    error control ? (Its useless getting wrong results faster. You have to know
    about the error range.))

My opinion is, supercomputers will exist a long time in future and MICROS still
have a long way to go, to match the performance.
Most people comparing the power don't think of the background of the
numbercrunchers and that are lots of software packages and big disks to record
the results, what is a big part of the machines cost.

Don't get me wrong: I'm a Micro User (OS9-680x0) and I like it, but I know that
things are not so easy in the supercomputing area as some people might think.

Knut Grunwald, Raiffeisenstr. 8, 7555 Elchesheim-Illingen, West-Germany