similar to: 64-bit R on Opteron [was Re: Windows R 1.8.0 hangs when M em Usage >1.8GB]

> From: Douglas Bates > > How does the Opteron perform on floating point? Can you try something > like > > > mm = matrix(rnorm(1e6), nc = 1e3) > > system.time(crossprod(mm)) > [1] 0.51 0.02 0.53 0.00 0.00 > > system.time(crossprod(mm)) > [1] 0.37 0.03 0.40 0.00 0.00 > > system.time(crossprod(mm)) > [1] 0.38 0.02 0.40 0.00 0.00 > >

rsync.r-project.org (alias bates4.stat.wisc.edu) seems to be unreachable right now. is this only my problem? will it be reachable soon again? -- Erich Neuwirth, Computer Supported Didactics Working Group Visit our SunSITE at http://sunsite.univie.ac.at Phone: +43-1-4277-38624 Fax: +43-1-4277-9386

My computers at my office will no longer be able to connect directly to web sites etc. I will be going through a proxy server. The particular server is running squid on port 3128. I have managed to configure web browsers, ssh, apt, svn and a whole lot of other tools to use the proxy server but I haven't been able to configure rsync. My usual method of updating my copy of the R-devel

The rsync site is back up. It may take a while for the new location to percolate through the DNS servers. The site should be bates at bates4:~$ host rsync.r-project.org rsync.r-project.org is an alias for bates4.stat.wisc.edu. bates4.stat.wisc.edu has address 128.105.174.134 and not the previous site, franz.stat.wisc.edu, which was comprised.

Hi, I was wondering if anyone has had good experiences using R on Linux with dual AMD64 (Opteron) processors. I'm thinking of buying a couple of such servers, but I'd like to make sure R would work fine. The "R Installation and Administration" guide notes that there may be some problems with BLAS libraries. That's all I could find about R on AMD64. Please share your

ABCD are four matrix. A * Inverse((Transpose(A)*Tranpose(B)*B*A+C)) * Transpose(A) * Transpose(B) * D how to write in R in an efficient way? --------------------------------- [[alternative HTML version deleted]]

The following is at least as much out of intellectual curiosity as for practical reasons. On reviewing some code written by novices to R, I came across: crossprod(x, y)[1,1] I thought, "That isn't a very S way of saying that, I wonder what the penalty is for using 'crossprod'." To my surprise the penalty was substantially negative. Handily the client had S-PLUS as

Dear R-help, Can some one tell me if it's possible to have conditional importFrom() in the package NAMESPACE file? Basically I'd like to know if it's possible to make the NAMESPACE file compatible with R 1.9.0 and those 1.8.1 and earlier. The problem is that I want to import cmdscale(), which is in `mva' prior to 1.9.0 but in `stats' post 1.9.0. Any pointer much appreciated!

I have a loop that increases the size of an object after each iteration. When the Windows Task Manager shows "Mem Usage" about 1.8GB, the Rgui.exe process no longer responds. I use: "C:\Program Files\R\rw1080\bin\Rgui.exe" --max-mem-size=4000M --min-vsize=10M --max-vsize=3000M --min-nsize=500k --max-nsize=1000M I have a dual Xeon 2.8GHz processor box with 4GB of memory and

Hi, is it possible to get the benchmark-results from anybody is using a common amd dual opteron with windows or linux, R.1.8.1 or 1.9.0? http://www.sciviews.org/other/benchmark/R2.R many thanks & regards, christian

Note that if you force a garbage collection each iteration the times are more stable. However, on the average it is faster to let the garbage collector decide when to leap into action. mb_gc <- microbenchmark::microbenchmark(gc(), { x <- as.list(sin(1:5e5)); x <- unlist(x) / cos(1:5e5) ; sum(x) }, times=1000, control=list(order="inorder")) with(mb_gc,

The large value for maximum time may be due to garbage collection, which happens periodically. E.g., try the following, where the unlist(as.list()) creates a lot of garbage. I get a very large time every 102 or 51 iterations and a moderately large time more often mb <- microbenchmark::microbenchmark({ x <- as.list(sin(1:5e5)); x <- unlist(x) / cos(1:5e5) ; sum(x) }, times=1000)

R-Devel, I store and retrieve a large amount of financial data (millions of rows) in a PostgreSQL database keyed by date (and represented in R by class Date). Unfortunately, I frequently find that a great deal of processing time is spent converting dates from character representations to Date class representations in R, presumably because strptime is not fast for large vectors (>10,000

For those interested: I compiled R-1.9.0beta_2004-04-02 with pgf77/gcc/g++ and g77/gcc/g++, both _without_ fast BLAS. Both passed make check-all. Simple crossprod(m) for fairly large `m' shows that the version compiled with pgf77 is about 15% faster: [andy@leo:scratch]% echo "set.seed(1); m <- matrix(runif(5e7), 1e4); gc(); system.time(crossprod(m))" | R-1.9.0-PGI/bin/R

Using ATLAS with R is an old topic quite covered in the "R Administration" manual (and by R's "configure" script collection). I still do not easily manage to build R properly on our new AMD Opteron (2-processor). I did work with the current Atlas 3.6.0, configured manually (but "express" version) to build a threaded ATLAS version, and successfully ran Atlas'

Running "as.character" on a large POSIXct causes a segfault on my 2.11 (2010-04-22) install. Seems to crash at around 9e4 ... on OSX and Ubuntu at least. > invisible(as.character(Sys.time()+1:7e4)) > invisible(as.character(Sys.time()+1:8e4)) > invisible(as.character(Sys.time()+1:9e4)) Error: segfault from C stack overflow > invisible(as.character(Sys.time()+1:5e5)) Error:

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

Dear R-help, Let's say `x1' and `x2' are very long vectors (length=5e5, say) with same set of names but in different order. If I want to sort `x2' in the order of `x1', I would do x2[names(x1)] but the amount of time that takes is quite prohibitive! Does anyone have any suggestion on a more efficient way to do this? If the two vectors are exactly the same length (as I

Dear R-devel, Has anyone played with this? http://www.amd.com/us-en/Processors/DevelopWithAMD/0,,30_2252_2282,00.html <http://www.amd.com/us-en/Processors/DevelopWithAMD/0,,30_2252_2282,00.html> . I'll probably give it a shot... Best, Andy Andy Liaw, PhD Biometrics Research PO Box 2000, RY33-300 Merck Research Labs Rahway, NJ 07065 mailto:andy_liaw@merck.com

I have this problem: my screen seems not wide enough in R. My true computer monitor is very wide, so I wish that I can line up the text when I stretch it wide. i.e.: This is typical R returns: > summary(a) V1 V2 V3 V4 F:625 Min. :20020103 EMC : 34 Min. : 9300300 L:944 1st Qu.:20020530 BRW : 27 1st Qu.: 9323865