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From: eugene@wilbur.nas.nasa.gov (Eugene N. Miya)
Newsgroups: comp.parallel
Subject: Re: terminology (again) 8) <- see I do wear glasses
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Date: 6 Jun 90 18:30:32 GMT
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In article <9223@hubcap.clemson.edu> art@cs.bu.edu (Al Thompson) writes:
>It's an arbitrary thing.
>They are arbitrary, but they make a certain amount of sense.
>they are as good as anything else.
>other serious scientist) would not consider a machine that synched at 19
>instructions to be fine grained while one that synched at 21 to be medium.
>It doesn't make any sense except to the anally pedantic.  If you are going
>to have terms like "grain" floating around it's a good idea to have AGREED
>(not natural, whatever that means) definitions.  Agreed, simply so that
>when we encounter the terms in isolation from other scientists we will
>"know" what they mean.
>
>One of the problems in computing is this lack of well defined terms.  As a
>scientist trained in another discipline (biophysics) I am continually
>appalled at the lexical anarchy in the computing "sciences". << AGREED.
>In fact I
>was so startled by this that I undertook a study of just what it is that
>constitutes "knowledge" from the point of view of an established science.
>What comes through clearly is the newness of computing.	<< AGREED.
>KUHN.  He makes the important point that you know a
>true paradigm has been defined when the basic definitions appear in the
>"standard" textbooks.  This has the effect of schooling a generation of
>scientists who think that the words they use are somehow invariant.  This
>is not true, but it does start them off that way.  Only later when they
>are faced with paradigm crisis and shift do they truly confront this
>issue.  I suggest that that is exactly where "computer science", "computer
>engineering" and "computational science (the new kid on the block)" are
>today.  If you don't believe me, look at the textbooks, particularly look
>for agreement from author to author.  The more agreement you see the
>closer we are.  Now, as an exercise, look at the books of twenty years
>ago and repeat the comparison.

I just posted a note about this with regard to the recent architecture
symp. (in comp.arch).  More respected architects are also encountering
this communications problem.  They too are having he problem with PAPERs
and TEXTS.  The purpose of my note was that I didn't
care for the emphasis on synchronizing cycles, too control flow oriented.
And if you have never studied dataflow where the synchronizations
can occur many cycles away.....  I hope you get the picture.

The problem isn't simply terminology (I think enough readers of
comp.parallel have seen me post on the problem of terminology).
Comp.arch is having another "super-linear speed-up" discussion,
another use of bad terminology.  But consider that some concepts
are completely foreign to some people: imagine working on a word oriented
machine all your life then working on a byte oriented machine.
See my comp.arch posting if this example is too vague.

I do not think we should be too arbitrary.  We must be careful and we
will get burned on occasion.  Fortran was somewhat arbitrary, we didn't
know about programming languages back then.  We know more now.  Backus
and others thought one could make a PL based on simple algebra (not enough).

I came from math (and nuclear engineering).  Our use of language has
become so precise it's stilting: an "ideal" probably means one thing
to most people, but mathematicians its meaning is "refined."  This is
offered as a comment to your comment on invariance.  It's not simply
invariant or arbitrary.

I empathize with your frustration.  Computer science isn't.  Part of
the problem is simultaneous over- and under- emphasis on math
and under emphasis on empirical work/construction.  This is changing.
There are also economic considerations and in the high performance
arena, there are "political" considerations.  There are companies
(some read the net, others don't) whose best economic interests
are served by maintaining confusion.  That's how economic works 8).
That's not science.  I only point to benchmarking as one example of this
problem (i.e. performance measurement).


Your moderator (Steve) pointed me to an excellent book: The Language of
Thought (which I'm picking away at).  Remember that "parallel computing"
isn't, either.  It's parallel, part of the time.  My officemate George
is always harping on me about "notation" with Whitehead as an example.
We do have to agree upon definitions so we can move on,
economic/political considerations be damned.  If we want science, if we
want faster machines, etc.

Keep policing the language.

--e. nobuo miya, NASA Ames Research Center, eugene@orville.nas.nasa.gov
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