Erlang-style message-passing in R: Rmpi, Snow, NetWorkSpaces, etc.

taskPR was an attempt to get 'free' parallelism out of already
existing programs by using simple data dependencies to figure out
which individual statements in a program can be run in parallel.
The name comes from the description of the program as exploiting
task-level parallelism.

Ah, and thus your reference to Tomasulo's algorithm, interesting.
Thanks for straightening me out there.

  http://users.ece.gatech.edu/~gte810u/Parallel-R/

(If anybody actually uses or has successfully used this package, I
would love to hear about it, btw.  While the package *does* work,
there are probably few cases where it is worth it.)

What would you say typically limits taskPR's approach, not finding
enough instruction-level parallelism at the R script level, or the
communications overhead (probably latency) of trying to make use of
it?

If latency, then perhaps taskPR would work better in a multi-threaded
R interpreter, rather than across a TCP/IP network fabric.  To roughly
test that empirically (assuming you are in fact using MPI for the
communications), I suppose you could start up your several R processes
on a single fat SMP node, and use an MPI that sends messages through
fast shared memory.  That's probably still slower than
thread-to-thread communications, but it should be much lower latency
than TCP/IP.  Maybe you already tried something like that?

Andrew Piskorski <atp at piskorski.com>
http://www.piskorski.com/