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From: gary@chpc.utexas.edu (Gary Smith)
Newsgroups: comp.sys.super
Subject: Re: Massively Parallel LINPACK on the Intel Touchstone Delta machine
Message-ID: <1991Jun10.144354.695@chpc.utexas.edu>
Date: 10 Jun 91 14:43:54 GMT
References: <1991Jun5.120653.7852@hubcap.clemson.edu> <1991Jun05.185818.1071@convex.com> <1991Jun6.144903.20456@chpc.utexas.edu> <1991Jun06.205144.22611@ariel.unm.edu>
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In article <1991Jun06.205144.22611@ariel.unm.edu>, john@spectre.unm.edu (John Prentice) writes:
|> In article <1991Jun6.144903.20456@chpc.utexas.edu> gary@chpc.utexas.edu (Gary Smith) writes:
|>
|> >Again, it's time for the advocates of the promise of massive parallelism
|> >to acknowledge Synder's "corollary of modest potential."
|> >
|> 
|> So what would you suggest as an alternative.  By this analysis, anyway
|> you cut it, a serial processor will still take p times longer to do the
|> same problem (of course, you have ignored overhead, but that works in 
|> favor of your argument).  If I can do it 64,000 times faster on a CM-2
|> and I don't have any choice but to do the problem, then I am going to
|> use the CM-2.  The alternative is to just not do the problem. 
|> 
|> Your are both right and wrong about what the goal is in scientific
|> computing.  For many applications, the goal isn't to run bigger problems,
|> it is to make current ones less expensive.

Using Speedup(f,p) = 1/[(1-f)+(f/p)], with f being the fraction of code
parallelized and p being the number of processors, and unrealistically
assuming no overhead, a speedup of 64000 using 65536 processors requi-
res that the problem be 99.9999634% parallel.  How many problems do you
know of that are that parallel?

---Gary

Randolph Gary Smith                       Internet: gary@chpc.utexas.edu
Systems Group                             Phonenet: (512) 471-2411
Center for High Performance Computing     Snailnet: 10100 Burnet Road
The University of Texas System                      Austin, Texas 78758-4497