similar to: improve R memory under linux

Dear all, I am using ubuntu linux 32 with 4 Gb.  I am running a very small script and I always got the same error message:  CAN NOT ALLOCATE A VECTOR OF SIZE 231.8 Mb. I have reading carefully the instruction in ?Memory.  Using the function gc() I got very low numbers of memory (please sea below).  I know that it has been posted several times at r-help

Dear all, I am using ubuntu linux 32 with 4 Gb.  I am running a very small script and I always got the same error message:  CAN NOT ALLOCATE A VECTOR OF SIZE 231.8 Mb. I have reading carefully the instruction in ?Memory.  Using the function gc() I got very low numbers of memory (please sea below).  I know that it has been posted several times at r-help

Dear all, I am using ubuntu linux 32 with 4 Gb.  I am running a very small script and I always got the same error message:  CAN NOT ALLOCATE A VECTOR OF SIZE 231.8 Mb. I have reading carefully the instruction in ?Memory.  Using the function gc() I got very low numbers of memory (please sea below).  I know that it has been posted several times at r-help

Dear R-ers, somehow it is not possible to increase nsize to more than 20000k. When I specify e.g. > R --vsize=10M --nsize=21000K the result is: free total (Mb) Ncells 99658 350000 6.7 Vcells 1219173 1310720 10.0 Maybe I have overlooked s.th.... Marcus -- +------------------------------------------------------- | Marcus Eger | E-Mail: eger.m at gmx.de (NEW) |

I have a question concerning memory. I understood that R takes a fixed amount of memory at startup (which I can influence with --vsize --nsize) and that gc() shows the memory still free of the total memory reserved for R. However, if I create a long vector of character data, gc() only seem to reflect the space needed for a vector of pointers to char, the space used for the character data itself

Dear Group I'm still trying to bring many data into R (see older postings). After solving some troubles with the database I do most of the work in MySQL. But still I could be nice to work on some data using R. Therefore I can use a dedicated Server with Gentoo Linux as OS hosting only R. This Server is a nice machine with two CPU and 4GB RAM which should do the job: Dual Intel XEON 3.06 GHz

Hello everyone - I have a couple of questions about memory management of large objects. Thanks in advance for your response. I'm running R version 1.9.1 on solaris 8, compiled as a 32 bit app. My system has 12.0 GB of memory, with usually ~ 11GB free. I checked system limits using ulimit, and there is nothing set that would limit the maximum amount of memory for a process (with the

Hi, I am trying to minimize a rather complex function of 5 parameters with gafit and nlm. Besides some problems with both optimization algorithms (with respect to consistantly generating similar results), I tried to run this optimization about a hundred times for yet two other parameters. Unfortunately, as the log below shows, during that batch process R starts to eat up all my RAM,

I am running R version ??? under Redhat 5.2. It seems as though the --nsize object has no effct on the size of the allocated Ncells as determined using gc(). Yes, I have that much data.... That is if I envoke R with R --vsize 100 --nsize 5000000 then type gc() I get free total Ncells 92202 200000 Vcells 12928414 13107200 Thanks Tony Long Ecology and Evolutionary Biology Steinhaus

I don't know whether this belongs to r-devel or rather r-help. Under RW1.11 --nsize=8M --vsize=512M I could n <- 500000 m <- 20 x <- matrix(rnorm(n*m), ncol=m, nrow=n) gc() > n <- 500000 > m <- 20 > x <- matrix(rnorm(n*m), ncol=m, nrow=n) > gc() free total (Mb) Ncells 8190509 8388608 160 Vcells 57033698 67108864 512 # under RW1.20 --vanilla

Just wanted to start a discussion on whether R could ship with more appropriate GC parameters. Right now, loading the recommended package Matrix leads to: > library(Matrix) > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 1076796 57.6 1368491 73.1 1198505 64.1 Vcells 1671329 12.8 2685683 20.5 1932418 14.8 Results may vary, but here R needed 64MB of N cells and 15MB

Martin Morgan discussed this a year or so ago and as I recall bumped up these values to the current defaults. I don't recall details about why we didn't go higher -- maybe Martin does. I suspect the main concern would be with small memory machines in student labs and less developed countries. If there was a way on all platforms to identify how much memory is available that might help to

I am trying to upload into R 143 Affymetrix chips onto using R on the NIH Nimbus server. I can load 10 chips without a problem, however, when I try to load 143 I receive a error message: cannot create a vector of 523263 KB. I have expanded the memory of R as follows: R --min-vsize=10M --max-vsize=2500M --min-nsize=10M -max-nsize=50M (as specified in help in R). After running this command the

Full_Name: Viktor Moravetski Version: Version 1.2.0 (2000-12-13) OS: Win-NT 4.0 SP5 Submission from: (NULL) (209.128.81.199) I've started R (v.1.20) with command: rgui --vsize 450M --nsize 40M Then at the command prompt: > gc() used (Mb) gc trigger (Mb) Ncells 358534 9.6 41943040 1120 Vcells 3469306 26.5 58982400 450 >df <- data.frame(x=1:30000,y=2,z=3)

Dear all, I am working on a 64 bits Linux system. I issue the following R commands: > rm(list=ls()) # To remove all objects in the workspace. > gc() # To free memory. used (Mb) gc trigger (Mb) max used (Mb) Ncells 124250 6.7 350000 18.7 350000 18.7 Vcells 124547 1.0 786432 6.0 476934 3.7 > gc() # I had to do it again, don't know why! used (Mb) gc trigger (Mb) max used (Mb) Ncells

I am using ESS on a unix system for my analysis. My R environment contains a 90118 by 94 dataframe. I am trying to calculate the mean of a column in this data frame and I am getting the following error: Error: can not allocate a vector of size 704 Kb I have tried options(memory=1000000000000000000) and this does not help. when I call gc() this is what is returned > gc() used

Windows users note: the rw-faq says |1.8) Can I use rw0xx with ESS and emacs? | |Yes. Some time soon versions of ESS (5.1.3 has a `somewhat rough' |prototype for rw0632) will come with support for this version of R. If |yours does not, edit essd-r.el to have | | (inferior-ess-start-args . "--ess")) | |and make sure you give the full path to Rterm.exe as the R executable.

Sorry, but I lost this thread, so I sending this as a new message. This is really a follow-up to a post from a couple days ago saying that fisher.test from the ctest library crashed on the following data set: > T [,1] [,2] [1,] 2 1 [2,] 2 1 [3,] 4 0 [4,] 8 0 [5,] 6 0 [6,] 0 0 [7,] 1 0 [8,] 1 1 [9,] 7 1 [10,] 8 2 [11,]

I've looked through all of the posts about this issue (and there are plenty!) but I am still unable to solve the error. ERROR: cannot allocate vector of size 455 Mb I am using R 2.6.2 - x86_64 on a Linux x86_64 Redhat cluster system. When I log in, based on the specs I provide [qsub -I -X -l arch=x86_64] I am randomly assigned to a x86_64 node. I am using package GenABEL. My data (~ 650,000

Hi, when doing as.double() on an object that is already a double, the object seems to be copied internally, doubling the memory requirement. See example below. Same for as.character() etc. Is this intended? Example: % R --vanilla > x <- double(1e7) > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 234019 6.3 467875 12.5 350000 9.4 Vcells 10103774 77.1