"Almost there" version of TDPL updated on Safari Rough Cuts

[Sean Kelly]

dsimcha Wrote:

> == Quote from Sean Kelly (sean at invisibleduck.org)'s article
> > dsimcha Wrote:
> > >
> > > This is great for super-scalable concurrency, the kind you need for things like
> > > servers, but what about the case where you need concurrency mostly to exploit data
> > > parallelism in a multicore environment?  Are we considering things like parallel
> > > foreach, map, reduce, etc. to be orthogonal to what's being discussed here, or do
> > > they fit together somehow?
> > I think it probably depends on the relative efficiency of a message passing
> approach to one using a thread pool for the small-N case (particularly for very
> large datasets).  If message passing can come close to the thread pool in
> performance then it's clearly preferable.  It may come down to whether pass by
> reference is allowed in some instances.  It's always possible to use casts to
> bypass checking and pass by reference anyway, but it would be nice if this weren't
> necessary.
> 
> What about simplicity?  Message passing is definitely safer.  Parallel foreach
> (the kind that allows implicit sharing of basically everything, including stack
> variables) is basically a cowboy approach that leaves all safety concerns to the
> programmer.  OTOH, parallel foreach is a very easy construct to understand and use
> in situations where you have data parallelism and you're doing things that are
> obviously (from the programmer's perspective) safe, even though they can't be
> statically proven safe (from the compiler's perspective).

I'd like to think it isn't necessary to expose the internals of the algorithm to the user.  Parallel foreach (or map, since they're the same thing), could as easily divide up the dataset and send slices to worker threads via messages as with a more visible threading model.  The only issue I can think of is that for very large datasets you really have to pass references of one kind or another.  Scatter/gather with copying just isn't feasible when you're at the limits of virtual memory.