> I'm trying to run generalized singular value decomposition (GSVD) > function from LAPACK library. Basically my problem is that I can not run > it for large matrices, I get a memory error. I'm using R 2.5.1. I tried > this on intel centos5 machines with 2 GB memory and 8 GB memory. I have > unlimited max memory,cpu time and virtual memory. > >> res=GSVD( matrix(1:35000,5000,6), matrix(1:35000,5000,6) ) #runs >> without > problems >> res=GSVD( matrix(1:36000,6000,6), matrix(1:36000,6000,6) ) > Error: cannot allocate vector of size 274.7 Mb
Did you examine R's internal memory limits, e.g. ?memory for help... that should help. [You should, most likely, be able to allocate a ~274MB vector on a 2GB machine... but you might have to coerce R into taking that much memory from the system, rather than trying to be conservative.] --elijah ______________________________________________ R-help@r-project.org 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.
