On 02/04/14 04:30 PM, Greg Woods wrote:
On Wed, 2014-04-02 at 16:02 -0400, Digimer wrote:
In short, I don't know if there is anything that can sum the
computational power of multiple systems and transparently make it look
like a single super fast machine.
My experience says there isn't. Granted I am not an expert in parallel
computing, but I work for a supercomputing site. About 15 years ago,
high performance computing hit the wall with regard to how fast a single
processor can be. We had CRAY computers that used vector processing;
that means executing the same instructions on a range of memory words at
the same time in one instruction cycle. This means that code like
for i = 1,100 do
a[i]=a[i]*2
done
would execute at the same speed as "x=x*2" (in this admittedly trivial
example, you get a factor of 100 speedup). That was a lot easier to
program for than multiprocessing, but even that required careful
attention when writing code so that it would vectorize and get the
performance boost.
After single processor computing hit the wall, we and every other HPC
site had to go to parallel processing (modern supercomputers have tens
of thousands of processors running on thousands of separate nodes). This
too requires special coding, so that your program will naturally break
up into separate tasks that can be executed in parallel. That is true
whether you are talking about using multiple processors on a single
machine, or spreading a code over multiple systems. There are MPI
libraries to make this task easier, but it is never as simple as "OK,
now execute this unmodified code five times as fast using five machines
instead of one".
How difficult it is to parallelize the code depends, as has already been
said here, on the particular application to be parallelized.
--Greg
This confirms my understanding, thanks. :)
--
Digimer
Papers and Projects: https://alteeve.ca/w/
What if the cure for cancer is trapped in the mind of a person without
access to education?
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