ways of getting around allocMatrix limit?

[David Romano]

I need to multiply to very large, nonsparse matrices, and so get the
error "allocMatrix: too many elements specified".

Is there a way to set the limit for allocMatrix?

In my case, the two matrices, A and B, are nxm and mxp where m is
small, so I could subdivide each into blocks of submatrices
A=rbind(A1,A2,...) and B=cbind(B1,B2,...) then multiply each pair of
submatrices, but I was thinking there must be a better way to get
around the allocMatrix limit.   I'd be grateful for any suggestions!

Thanks,
David

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[Prof Brian Ripley]

On 31/07/2012 15:10, David Romano wrote:
> I need to multiply to very large, nonsparse matrices, and so get the
> error "allocMatrix: too many elements specified".
>
> Is there a way to set the limit for allocMatrix?

No:  see ?'Memory-limits'.

      There are also limits on individual objects.  On all builds of R,
      the maximum length (number of elements) of a vector is 2^31 - 1 ~
      2*10^9, as lengths are stored as signed integers.

and of course a matrix is just a vector with some attributes.

In R-devel you can get more: but don't bother unless you have 64+GB of
RAM as the limit currently is a 16GB matrix and you'll need space for
more than one.  (All the support for larger object is work-in-progress,
and reducing the number of copies is going on in parallel.)

> In my case, the two matrices, A and B, are nxm and mxp where m is
> small, so I could subdivide each into blocks of submatrices
> A=rbind(A1,A2,...) and B=cbind(B1,B2,...) then multiply each pair of
> submatrices, but I was thinking there must be a better way to get
> around the allocMatrix limit.   I'd be grateful for any suggestions!
>
> Thanks,
> David
>
> ______________________________________________
> [hidden email] mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

--
Brian D. Ripley,                  [hidden email]
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  [phone] (self)
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