[R] Working with massive matrices in R
jholtman at gmail.com
Tue Apr 19 00:22:15 CEST 2011
It is probably contiguous memory, I always suggest that you have 3-4X
memory than your largest object to ensure that you have room for
copies that might be made. So make a request for about 50GB of
On Mon, Apr 18, 2011 at 4:10 PM, svrieze <vrie0006 at umn.edu> wrote:
> I'm (eventually) attempting a singular value decomposition of a 3200 x
> 527829 matrix in R version 2.10.1. The script is as follows:
> ###---------Begin Script here-------###
> snps <- 527829 ## Number of SNPs
> N <- 3200 ## Sample size
> y <- rnorm(N, 100,1) ## simulated phenotype
> ## read in matrix 3200 x 527829
> x <- scan("gedi7.raw", what=rep(0,snps), nmax=N*snps, skip=1))
> system.time(x <- matrix(x,nrow=N,ncol=snps, byrow=TRUE))
> print(object.size(x), units="Mb")
> ###--------End Script----------------####
> The scan function finishes without a problem. "x" is in double precision
> floating point format and takes up 12886.5Mb of memory at the first
> object.size() statement.
> When I convert it to a matrix I get an error stating that I cannot allocate
> a vector of size 12.6Gb. I have requested 31Gb of memory on the server.
> 12.6+ 12.8 = 25.4Gb of used memory. Is it that R is using considerable
> memory for operations not directly related to storing the matrix objects
> here? Or is this perhaps a problem of contiguous memory?
> Any help is greatly appreciated.
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> and provide commented, minimal, self-contained, reproducible code.
Data Munger Guru
What is the problem that you are trying to solve?
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