Parallel Computing Question

Fri Apr 16 17:24:51 EST 1993

   Much of the problem with parallel algorithms is that they are machine 
   specific. There have been attempts at standardization of the parallel
   languages (F90, Fortran D, CMFortran), but communication calls are 
   far from standard. If you are porting code between very different 
   architectures, often the datasets will need to be restructured to insure
   reasonable performance. When you ask about code already written, you
   should also inquire as to which platform it was developed on. 

PCN , developed between Caltech and Argonne Labs allows for the same
program to run with NO modification on numerous uniprocessor platforms as
well as a number of popular hypercubes. It is available for anonymous ftp
from: in pub/pcn

   >    2. Is parallel computing on campus something we would use?

   In general, if you have a problem that requires a significant amount
   of interprocessor communication, a serial machine might give you better

Hmm, I beg to disagree. I spent a summer 2 years ago parallelizing an
fcc-lattice algorithm to predict tertiary protein structures. My parallel
version (developed with PCN) ran worlds faster.

Terry Brannon   tbrannon at
medical biology via acupunctural bioelectrics
primitive reigns supreme over nearly everyone

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