Path: utzoo!mnetor!uunet!seismo!sundc!pitstop!sun!amdcad!ames!ll-xn!husc6!hao!gatech!hubcap!"Eugene
From: brooks@LLL-CRG.LLNL.GOV (Eugene D. Brooks III)
Newsgroups: comp.hypercube
Subject: Re: Difficulty of programming in parallel
Message-ID: <959@hubcap.UUCP>
Date: 11 Feb 88 13:01:31 GMT
Sender: fpst@hubcap.UUCP
Lines: 21
Keywords: Survey of experience
Approved: hypercube@hubcap.clemson.edu

In article <832@hubcap.UUCP> segall%clash.rutgers.edu@RELAY.CS.NET (Ed Segall) writes:
>One of the strong selling points (or claims, anyway) for many 'parallel'
>computers, especially shared memory multiprocessors and vector
>processors with vectorizing compilers, is that these are much easier
>to program than distributed memory multiprocessors.

Take if from someone with a lot of experience with hypercubes,
shared memory multiprocessors, and vector processors.  Shared
memory multiprocessors are much easier to program, with the right
language support you can have common source code between shared
memory multiprocessors and serial machines, and be efficient on both.
The program architecture required for a distributed system is VERY
DIFFERENT than that of a serial program, and you can't slowly evolve
a serial program into a parallel program for a distributed architecture,
as you can for a shared memory machine.  In terms of programming ease
the shared memory machine, with a uniform and finely interleaved
shared memory, is the hands down winner.

						Eugene Brooks
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P.S.  Before you hypercube types get your backs up, check the history