🚀 go-pugleaf

In article <9119@batcomputer.tn.cornell.edu> kahn@batcomputer.tn.cornell.edu (Shahin Kahn) writes:
 
>If you have scalar dominated code that fits in a workstation's memory
>and you dont want to run more than one job at a time, then you are right.

Note: some of this discussion has seemed to assume that micro == workstation.
To help unconfuse people, let us remember that the same CPU chip can be
used in various different configurations, only some of which are
workstations.  Note that desktop workstations are unlikely to get enouhg
memory to keep real supercomputer users happy, given the usual cost
tradeoffs.  This might not be true of big desksides, and is least

>A 256 MB micro can cost you some.  And not so little.  And all that
>for just one user.  I am not sure the numbers come out.  And how about IO 
>bandwidth and file-size.  maybe your application doesnt need any.  
Again, note that the issue is not necessarily single-user workstations
versus supercomputers, it's mixtures of desktops, desksides, and servers
versus supercomputers..


I.e., a whole lot of this discussion has seemed like a classic "domain-of-
discourse" argument: in which the argument:
	A is true
gets heated replies of "No, it isn't"
should be converted to:
	In domain 1 (not very vectorizable), A is true. (micros are tough)
	But domain 2 (elsewhere), A is not true. (micros are not so tough)
which makes clear that the real argument is more like:

	How big are domains 1 & 2?  Will that change? 

THUS:
	FOR SUPERCOMPUTER USERS:
	a) How much of your code is vectorizable?
	b) How much is parallelizable?
	c) How much mostly needs big memories?
	d) How much is dominated by turnaround time, cost-is-no-object
		processing?
	e) Do you have some more data points, i.e.,
	SUPERCOMPUTER X versus microprocessor-based-system Y,
	including elapsed times & costs?

In most of this dicussion, we've gotten a few data points.  more would help.
-- 
-john mashey	DISCLAIMER: <generic disclaimer, I speak for me only, etc>
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