similar to: Linking With External Lapack: Segfault

Hello. I am a Linux neophyte and know almost nothing ?about compiling, so I would appreciate any help and advice y'all would care to offer. I am trying to compile the 64 bit version of R using a tuned ATLAS and LAPACK (ATLAS 3.9.24). I am running Ubunto 10.04 LTS (through wubi, FWIW). The ATLAS and LAPACK files (atlas.so, f77blas.so, lapack.so, and cblas.so) are sitting in the folder

Hello All, In general when we use Rprof for performance evaluation on Multicore systems the output provides the time on the basis of the "user" time and the sampling time is equal to the the user time as reported by system.time. This does not seem right behavior when R is linked to BLAS/Lapack or other libraries which are optimized for parallel or multicore architectures as

Hello All, In general when we use Rprof for performance evaluation on Multicore systems the output provides the time on the basis of the "user" time and the sampling time is equal to the the user time as reported by system.time. This does not seem right behavior when R is linked to BLAS/Lapack or other libraries which are optimized for parallel or multicore architectures as

Greetings, I have a computer with the following setup: 1)cblfs (pure 64-bit (amd64) linux), kernel2.6.34 gcc4.4.2 2)R-2.11.1 I compiled R with BLAS and lapack using the switched ( --with-blas="- lpthread -latlas -lfptf77blas" --with-lapack="-llapack -lcblas" ). (( http://cran.r-project.org/doc/manuals/R-admin.html#Linear-algebra) ) Prior to compiling R-2.11.1 sh

Dear R-help list members, I am hoping to get you help in reproducing a problem I am having That is only reproducible on a large-memory machine. Whenever I run the following lines, get a segfault listed below: *** caught segfault *** address 0x7f092cc46e40, cause 'invalid permissions' Traceback: 1: La.svd(x, nu, nv) 2: svd(X) 3: ginv(bigmatrix) Here is the code that I run:

Dear All, Under Debian GNU/Linux La.svd (with method = "dgesdd") sometimes gives the error "Error in La.svd(data, nu = 0, nv = min(nrow, ncol), method = "dgesdd") : LAPACK routine DGESDD gave error code -12" It seems not to depend on the data per se, but on the relationship between numbers of rows and columns. For example, if the number of columns is 100,

Dear all Some computations gave a matrix. The single value decomposition of it worked fine previously, after an system upgrade I get the following error: ----- > La.svd(x,256,256) Error in La.svd(x, nu, nv) : BLAS/LAPACK routine 'DLASCL' gave error code -4 ----- Erroneous Matrix: ftp://usys-ftp.ethz.ch/ITES/STEP/nussbaum/R/matrix-lapack-error4.RData /.csv Operating System: Debian 8

Hello R-users, during one of my analyses that involve a SVD, I get the following error message: Error in La.svd(x, nu, nv, method) : error code 1 from Lapack routine dgesdd With a search on the R web site, I only found references to error codes 17 and 3 for this particular routine. I also found the Lapack web site, but could not find a list of the possible error messages. If somebody knows what

Greetings, compiling R 1.7.0 with gcc 3.1.1 on Debain Linux (woody stable) with the configure option --with-lapack works but make check fails in test base-R with the message [...] > kappa(x1 <- cbind(1,1:10))# 15.71 [1] 15.70590 > kappa(x1, exact = TRUE) # 13.68 [1] 13.67903 > kappa(x2 <- cbind(x1,2:11))# high! [x2 is singular!] [1] 8.351867e+16 > > hilbert

Hello. I know almost nothing about Linux, so I apologize if the answer to this is obvious. I am trying to compile R with ATLAS (successfully compiled 3.9.24 on Ubuntu 10.04 64 bit). I configured with: ./configure --enable-R-shlib --enable-BLAS-shlib --with-blas="-L/usr/local/atlas/lib -lf77blas -latlas" --with-lapack="-L/usr/local/atlaslib -llapack -lcblas" --with-x and I

Hello. I know almost nothing about Linux, so I apologize if the answer to this is obvious. I am trying to compile R with ATLAS (successfully compiled 3.9.24 on Ubuntu 10.04 64 bit). I configured with: ./configure --enable-R-shlib --enable-BLAS-shlib --with-blas="-L/usr/local/atlas/lib -lf77blas -latlas" --with-lapack="-L/usr/local/atlaslib -llapack -lcblas" --with-x and I

Hi, I'm just wondering if it is planned to include the Lapack routine DGESDD (and friends) in R-1.4.0? This is faster (supposedly by a factor of ~6 for large matrices) than DGESVD which is currently (R-1.3.1) called by La.svd. And if it is not in the plans yet, is there a chance it could be? I've added it to my local version of R-1.3.1 and so far see a factor of 4 improvement over

Dear R helpers, I am working with R 2.4.1 GUI 1.18 (4038) for MacOSX. I have a matrix of 10 000 genes and try to run the following commands: > model.mix<-makeModel (data=data, formula=~Dye+Array+Sample+Time, random=~Array+Sample) > anova.mix<-fitmaanova (data, model.mix) > test.mix<-matest (data, model=model.mix, term="Time", n.perm=100, test.method=c(1,0,1,1))

Error in La.svd(x, nu, nv) : error code 1 from Lapack routine ‘dgesdd’ what resources are there to track down errors like this [[alternative HTML version deleted]]

[mailed jointly to maintainers@octave.org, r-devel@stat.math.ethz.ch to reach users with relevant experience. watch where your replies go. what would make using LAPACK and ScaLAPACK easier for Octave and R developers? -- ejr, not subscribed] We plan to update the LAPACK and ScaLAPACK libraries and would like to have feedback from users on what functionalities they think are missing and would

Lately I'm getting this error quite a bit: Error in La.svd(x, nu, nv) : error code 1 from Lapack routine 'dgesdd' I'm running R 2.5.0 on a 64 bit Intel machine running Fedora (8 I think). Maybe the 64 bit platform is more fragile about declaring convergence. I'm seeing way more of these errors than I ever have before. From R-Help I see that this issue comes up from time to

Dear all I have a big matrix of standardized values (dimensions 285x5829) and R fails to calculate the principal components using prcomp() with the following error message: pc <- prcomp(my.matrix) Error in La.svd(x, nu, nv, method) : error code 1 from Lapack routine dgesdd Is the matrix too big? I'm using R-1.8.1 under Unix (Solaris8) and Linux(Suse 8.2). I tried to perform a principal

I am a relative newcomer to both the R and C/C++ software worlds -- I'm taking a C Programming class currently. I noticed the other day that the C:\Program Files\R1_8_1\src\include\R_ext directory on my WinXP box has the header files BLAS.h Lapack.h Linpack.h RLapack.h I am interested in (perhaps) using one or more of these header files in a straight C program I'm working on in Visual

OS X 10.2 and higher comes standard with highly optimized versions of BLAS and Lapack in /Systems/Library/Frameworks/vecLib.framework. It seems that even for double precision they do much better. See http://sthmac.magnet.fsu.edu/benchmarks/ I am not sure how these numbers would look on G3 Macs, but obviously for double precision there is not much reliance on Altivec. So I tried to configure

Hello, This simple SVD calculation (commands are copied immediately below) crashes on my Ubuntu machine (R 2.13.0). However it worked fine with R.12 and Ubuntu 10.04, and it also works fine on my Windows 7 machine with R 2.13, so I suspect there's a problem with (my?) Ubuntu and / or R. I'm using the R distribution that is accessible with Ubuntu's repositories manager, I am not