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From: dmocsny@minerva.che.uc.edu (Daniel Mocsny)
Newsgroups: comp.arch
Subject: Re: Be Prepared...
Keywords: Lots Of Memory
Message-ID: <7517@uceng.UC.EDU>
Date: 21 Feb 91 18:20:23 GMT
References: <1991Feb13.160718.25759@visix.com> <3197@crdos1.crd.ge.COM> <46049@mips.mips.COM>
Sender: news@uceng.UC.EDU
Organization: University of Cincinnati, Cin'ti., OH
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In article <46049@mips.mips.COM> mash@mips.COM (John Mashey) writes:
>Elsewhere, there was a question about desktop applications that might
>want this.  I thought I posted a long discussion on this, but
>let me resummarize:
>	1) Databases
>	2) Video
>	3) Image
>	4) CAD
>	5) G.I.S.
>	6) Technical number-crunch

Pardon me if I am repeating points you made earlier, but let me
emphasize that having ridiculous amounts of memory available could
potentially speed up lots of things.

For example, in chemical engineering we often simulate processes
that require a program to evaluate equations of state, physical
property correlations, etc., repeatedly at similar conditions.
Depending on the form of the equation of state or property
correlation, the evaluation may be somewhat lengthy, and/or
implicit (i.e., requiring numerical convergence).

A good-sized simulation evaluates an equation of
state many times (once per grid point, per time step). Since conditions
may not change appreciably over a few grid points or time steps, much
of the calculation will be redundant. Researchers exploit this to
speed up iterative calculations, i.e., by using the result of the
previous solution for the grid point to guess a starting value for
the next one. However, no matter how fast the equation of state
routine is, a table-lookup routine would be faster. Even with an
interpolation for more precision, it will usually be better, especially
when the alternative is a routine requiring convergence.

So then, given unlimited memory, we can extend the notion of "caching"
to include any potentially redundant calculation. *Many* application
programs involve some element of redundancy. People don't solve
completely unique problems every time they fire up a computer. So if
I wanted to do a bunch of simulation runs, I would be happy to build
up a set of large interpolation tables that could speed things up by
a factor of 10 or 100. Since these tables would be multi-variable, and
precision would be nice also, no meaningful upper bound exists on
the amount of memory that might be potentially useful. In principle,
I'd like to have lookup tables containing every potentially-useful
computed result in my field.

Similarly, enormous amounts of memory could help personal computers
and workstations cope with the "bursty" workload of the typical user. 
While the user is twiddling her thumbs, the CPU need not be idling. 
Instead, it can be stockpiling its memory with all sorts of potentially 
useful things. Later, when the user happens to request one of those
things, the CPU will get it much faster from memory than if it had to
build it up from scratch again. The more memory available, the better
such a "work-ahead" strategy could work. By compiling statistics on
the user's work habits, the computer could possibly anticipate the
user's next likely command(s), and get a head-start during idle
periods.


--
Dan Mocsny				
Internet: dmocsny@minerva.che.uc.edu


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