To bcast.Robj, Rmpi uses serialize() to pack the object into "raw", which
operates as a vector of bytes. R supports vectors up to 2^31 elements. Your
object, serialized, is close to that. I'm a little puzzled though,
350x350000 matrix works for me; perhaps there's more to your actual call.

Setting up the slave environment explicitly seems to me to be better
practice, i.e. using mpi.bcast.Robj2Slave and related calls, then the
applyLB() doesn't contain the data. As I'm reading it, I think the way this
is set up currently will send the data to a slave for each application of
the apply.

If you're facing larger data sizes, a solution is to explicitly cut up the
object, mpi.bcast.Robj2Slave the pieces in turn, and then use an
mpi.bcast.cmd to collect them together. Another approach would be to write
to data to a file, and direct the slaves to read it into their environments
with an mpi.bcast.cmd.

As a comment: I can't tell your application from the code, but if the
slaves are to be working each on only part of the data, it's better to send
the slave just the part of the data it needs.

    cheers,
       jim




On Tue, Aug 6, 2013 at 6:37 PM, Ei-ji Nakama <nakama@ki.rim.or.jp> wrote:

> Hi,
>
> <WARNING>
> It is not yet completed...
> </WARNING>
> http://prs.ism.ac.jp/~nakama/Rhpc/
>
> 2013/8/7, Xiaochun Sun <xiaoch.sun@gmail.com>:
> > The same code worked fine for smaller dataset, such as 350x25000. Does
> that
> > mean the current Rmpi don't allow long vectors to be passed to slaves?
> Any
> > idea on that or any alternatives to Rmpi?
>
> Its can treat the considerably big data.
>
> --
> EI-JI Nakama  <nakama (a) ki.rim.or.jp>
> "\u4e2d\u9593\u6804\u6cbb"  <nakama (a) ki.rim.or.jp>
>
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>

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