Re: Remote fork() and Parallel programming

Larry McVoy (linker@nightshade.ml.org)
Tue, 16 Jun 1998 17:24:16 -0400 (EDT)


On Mon, 15 Jun 1998, Larry McVoy wrote:

> Here's another data point: scientific programmers on SMP machines
> frequently use MPI instead of shared memory. The programming model
> is simple, fast, and it works. Doesn't that seem completely crazy?
> Use message passing on a SMP? I wonder why they do that.

I dont know about anyone else, but I would dare to guess their feelings
are like mine:

I realized that I might someday want to run my app on a 100 node cluster
insted of just my SMP system... MPI seemed to be a better (performance
wise) solution to cluster programming, although it did require non-trivial
effort to program using it at first.

It seemed wiser to write my software for MPI and deal with the
difficulties and it being non-optimum on my smp system. (Although I've
never tested it, I'm sure that shared memory on a smp system is *MUCH*
faster then MPI)...

It was a matter of not having to reprogram it down the road. I could deal
with lower smp performance today for better cluster support tommorrow..

People like a single interface. Frankly, I feel that both choices should
be available to programmers. I know how to use PVM, Shared memory, and
MPI. I can pick the best one for the task.

(Btw- anyone know anyone working on parallel pov? I want to do radiosity
rendering, but that breaks the course granined box-o-pixels pvm model..
I'de like to recode it using MPI so that radiosity works).

> : I've read all the DIPC code (have you ?) and I think its close to meeting
> : that stated aim.
>
> Whether I've read it or not is completely beside the point - we are
> talking about programming models, not programming model implementations.
>
> But yes, Alan, I've read it. I've also read and used mether, the Rice
> DSM, Erlichson's DSM, SCI, to mention a few others. I've worked with
> most of the national labs on clusters, had extensive discussions with
> 100's of real cluster users working on real, not imagined, problems,
> ranging from scientific fortran jobs, to jet engine simulations, to
> market trading systems, and even parallel remote make (since that's
> what I care about, of course).
>
> I was having these debates before Linux existed. As far as I can tell,
> nothing has changed. It's the same old "shared memory is easy" claim,
> which strangely enough never seems to be made by the people that are
> actually working in the clustering area.
>
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