As I mentioned last week, I've been developing a package that I call
Rdsm ("R distributed shared memory"), modeled after a similar package,
PerlDSM, I wrote for Perl some years ago. It is now in alpha form, so
I'm not uploading to CRAN yet, but it is definitely usable, and I am
releasing it at
http://heather.cs.ucdavis.edu/~matloff/R/Rdsm
I hope many try it out, and give me some feedback.
Note that the word "distributed" here means that the memory is not
really shared, but instead is an abstraction, to give the programmer a
shared-memory view even though the program may be running on several
separate machines. For C/C++ this is generally accomplished by
manipulation of the virtual memory hardware. For R, I do this by
redefining functions such as "[" and "[<-" for a new
class.
Rdsm is intended as an alternative for those who favor the shared-memory
view of things. In the parallel processing community, there has always
been a debate between advocates of the two main programming paradigms,
shared memory and message passing. Shared memory advocates claim
greater clarity of code, while the message passing people point to that
paradigm's greater flexibility. I happen to be of the shared-memory
school. Given the popularity of OpenMP for C/C++/FORTRAN, I believe
Rdsm will be of interest to many for R. Indeed, in the next few months,
I will be extending Rdsm with functions that give it the "look and
feel"
of OpenMP.
Norm Matloff
UC Davis
----- End forwarded message -----
