We'll start looking into it here at NIST later this summer.  We have some
expressions on the order of 10,000 terms and things do tend to slow down ;>


William

On Tue, Jun 22, 2010 at 2:50 PM, Kevin Hunter <khun...@sandia.gov> wrote:

> If you haven't programmed a multi-execution style algorithm before,
> it's a bit of a mental leap.  However, the thought process involved
> with multi-threading vs multi-processing vs multi-machine scales.
> There is a growing movement to teach college students and younger
> folks to think "in parallel" from the get-go, but there will be a
> delay while the ecosystem waits for the current core of linearly-
> trained professors and teachers to retire.  (i.e. Parallel is here to
> stay.  Programmers and engineers not trained to think in parallel are
> effectively wasting compute power.)
>
> In the meantime, Python has some direct support for this.  For example
>
> http://docs.python.org/library/subprocess.html
> http://docs.python.org/library/multiprocessing.html
>
> However, if you're looking for the pragma style "this loop is SIMD, do
> the work for me," I'm not aware that Python has that.  (SIMD = Single
> Instruction Multiple Data, such as an increment of 1 to every element
> in an array.  Check out the Wikipedia on OpenMP for more info:
> http://en.wikipedia.org/wiki/OpenMP )
>
> Do you have to completely rewrite algorithms?  Depends on what you
> want to do.  Without delving into SymPy code (which I unfortunately
> can't do at the moment), I'd guess that your analysis is correct:
> implementing it wouldn't be a win except for some compute intensive
> areas, especially since it sounds like the coder base doesn't have a
> whole lot of experience thinking in parallel.
>
> I will say, that a good chunk of the /well written/ Python code that
> I've run across lends itself very well to parallel interpretation.  On
> the flip side, I find that folks who think more in an imperative
> style, tend to write much more linear-restricted algorithms and code.
> Often this boils down to reimplementing the many wheels of their
> programs, but I digress.
>
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