Thoughts on parallel programming?

[dsimcha]

== Quote from Tobias Pfaff (nospam at spam.no)'s article
> On 11/11/2010 08:10 PM, Russel Winder wrote:
> > On Thu, 2010-11-11 at 18:24 +0100, Tobias Pfaff wrote:
> > [ . . . ]
> >> Unfortunately I only know about the standard stuff, OpenMP/OpenCL...
> >> Speaking of which: Are there any attempts to support lightweight
> >> multithreading in D, that is, something like OpenMP ?
> >
> > I'd hardly call OpenMP lightweight.  I agree that as a meta-notation for
> > directing the compiler how to insert appropriate code to force
> > multithreading of certain classes of code, using OpenMP generally beats
> > manual coding of the threads.  But OpenMP is very Fortran oriented even
> > though it can be useful for C, and indeed C++ as well.
> >
> > However, given things like Threading Building Blocks (TBB) and the
> > functional programming inspired techniques used by Chapel, OpenMP
> > increasingly looks like a "hack" rather than a solution.
> >
> > Using parallel versions of for, map, filter, reduce in the language is
> > probably a better way forward.
> >
> > Having a D binding to OpenCL (and OpenGL, MPI, etc.) is probably going
> > to be a good thing.
> >
> Well, I am looking for an easy & efficient way to perform parallel
> numerical calculations on our 4-8 core machines. With C++, that's OpenMP
> (or GPGPU stuff using CUDA/OpenCL) for us now. Maybe lightweight was the
> wrong word, what I meant is that OpenMP is easy to use, and efficient
> for the problems we are solving. There actually might be better tools
> for that, honestly we didn't look into that much options -- we are no
> HPC guys, 1000-cpu clusters are not a relevant scenario and we are happy
> that we even started parallelizing our code at all :)
> Anyways, I was thinking about the logical thing to use in D for this
> scenario. It's nothing super-fancy, in cases just a parallel_for we
> will, and sometimes a map/reduce operation...
> Cheers,
> Tobias

I think you'll be very pleased with std.parallelism when/if it gets into Phobos.
The design philosophy is exactly what you're looking for:  Simple shared memory
parallelism on multicore computers, assuming no fancy/unusual OS-, compiler- or
hardware-level infrastructure.  Basically, it's got parallel foreach, parallel
map, parallel reduce and parallel tasks.  All you need to fully utilize it is DMD
and a multicore PC.

As a reminder, the docs are at
http://cis.jhu.edu/~dsimcha/d/phobos/std_parallelism.html and the code is at
http://dsource.org/projects/scrapple/browser/trunk/parallelFuture/std_parallelism.d .
 If this doesn't meet your needs in its current form, I'd like as much
constructive criticism as possible, as long as it's within the scope of simple,
everyday parallelism without fancy infrastructure.