Quoting [EMAIL PROTECTED]: > > > 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 >
Hi Elijah, Thanks for your reply. I checked internal memory limits and it seems there is no maxima set for consecutive cells or vector heap so i guess only limit is machine resources. Also I set the "--max-ppsize" to the maximum value allowed with the hope that it might help, it didn't change, still can not allocate memory. Below I pasted ulimit -a output, maybe it helps for diagnostics. Further more, I changed the stack size to "unlimited", that didn't help either. core file size (blocks, -c) 0 data seg size (kbytes, -d) unlimited max nice (-e) 0 file size (blocks, -f) unlimited pending signals (-i) 32759 max locked memory (kbytes, -l) 32 max memory size (kbytes, -m) unlimited open files (-n) 1024 pipe size (512 bytes, -p) 8 POSIX message queues (bytes, -q) 819200 max rt priority (-r) 0 stack size (kbytes, -s) 10240 cpu time (seconds, -t) unlimited max user processes (-u) 32759 virtual memory (kbytes, -v) unlimited file locks (-x) unlimited cheers altuna ______________________________________________ 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.
