Hello,
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-------###
library(Matrix)
snps <- 527829 ## Number of SNPs
N <- 3200 ## Sample size
y <- rnorm(N, 100,1) ## simulated phenotype
system.time(
## 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.
-Scott
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