similar to: Why is matrix product slower when matrix has very small values?

Hi Florian, just a guess, but couldn't it be that the multiplication of very small values leads to FP underflow exceptions which have to be handled by BLAS in a less efficient way than "normal" multiplications handled by SIMD instructions ? Best regards, Hilmar On 19/11/2019 15:09, Florian Gerber wrote: > Hi, > > I experience surprisingly large timing differences for

Hi, I was be half asleep in the heat ... 2016-08-04 0:04 GMT+09:00 Dirk Eddelbuettel <edd at debian.org>: > > On 3 August 2016 at 16:45, Gordon Ball wrote: > | On 02/08/16 03:10, Ei-ji Nakama wrote: > | > Hi, > | > > | > Create /etc/profile.d/openblas.sh. > | > Write the following during in this file. > | > OPENBLAS_NUM_THREADS = 1 > | > export

On 02/08/16 03:10, Ei-ji Nakama wrote: > Hi, > > Create /etc/profile.d/openblas.sh. > Write the following during in this file. > OPENBLAS_NUM_THREADS = 1 > export OPENBLAS_NUM_THREADS > > OPENBLAS_NUM_THREADS environment variable does not affect the OMP_NUM_THREADS. > Thanks for the response. This works fine for R run from the command line (as does setting the same

Hi Hilmar, weird. The memory problem seems be due to recursion (my R, version 3.3.3, says: Error: evaluation nested too deeply: infinite recursion / options(expressions=)?, just write traceback() to see how it happens), but why does it segfault with xlsx? Nb xlsx is the culprit: neither rJava nor xlsxjars cause the problem. On the other hand, quick googling for r+xlsx+segfault returns tons of

Hi, On 08/05/17 16:37, Ista Zahn wrote: > One of the key strengths of R is that packages are not akin to "fan > created mods". They are a central and necessary part of the R system. > I would tend to disagree here. R packages are in their majority not maintained by the core R developers. Concepts, features and lifetime depend mainly on the maintainers of the package (even

Dear Martin, On 11/09/2019 09:56, Martin Maechler wrote: > > > I wonder if data.frame(<some non-empty data>) == NULL should also return > > a value instead of an error. R help reads: > > > "At least one of |x| and |y| must be an atomic vector, but > > if the other is a list R attempts to coerce it to the > > type of the atomic

Hi, this is a problem that occurs in the presence of two libraries (limma, xlsx) and leads to a crash of R. The problematic code is the wrong application of sweep or the product ("*") function on an LIMMA MAList object. To my knowledge, limma does not define a "*" method for MAList objects. If only LIMMA is loaded but not package xlsx, the code does not crash but rather

What is the correct way to globally configure R to default to single (or at least, << NUM_CPUS) threaded operation? Using R 3.3.1 (both in debian unstable or using the CRAN repository for xenial) with OpenBLAS (0.2.18) defaults to using one thread per available CPU, which isn't ideal for machines more than a couple of CPUs. Setting the environment (OMP_NUM_THREADS or

Dear all, I just stumbled upon some behavior of the == operator which is at least somewhat inconsistent. R version 3.6.1 (2019-07-05) -- "Action of the Toes" Copyright (C) 2019 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 (64-bit) > list(a=1:3, b=LETTERS[1:3]) == NULL logical(0) > matrix(1:6, 2,3) == NULL logical(0) > data.frame(a=1:3,

Hi Tomas, Thanks for your answer. Indeed, I checked and my R-3.4.1 installed from the ubuntu repository use 'libopenblasp-r0.2.18.so' while my R-3.3.2 that I did compiled on my machine use 'libRblas.so' which explain the difference of behavior. I will use RhpcBLASctl to avoid issue when combining matrix product and other multi-threading package. Maybe this point regarding

Dear R Core Team, I wish to report what can be viewed as a bug or at least a strange behavior in R-3.4.1. I ask my question here (as recommended on https://www.r-project.org/bugs.html) since I am not member of the R's Bugzilla. When running 'R --vanilla' from the command line, the standard matrix product is by default based on BLAS and multi-threaded on all cores available on

Dear R experts, recently I started developing a Rcpp package "OpenMPTest". Within that package I want to use OpenMP, as in the following code example: // header file #include <omp.h> using namespace Rcpp ; RcppExport SEXP testOpenMP( SEXP nThreads ) ; // cpp file SEXP testOpenMP( SEXP nThreads ) { BEGIN_RCPP NumericVector numberThreads = NumericVector( nThreads );

Hi all, Assume I have a data frame with numerical and factor variables that I got through merging various other data frames and subsetting the resulting data frame afterwards. The number levels of the factors seem to be the same as in the original data frames, probably because subset() calls [.factor without drop = TRUE (that's what I gather from scanning the mailing lists). I wonder if

Dear all, I'm experiencing an unusual installation error for one package. Could anyone suggest how I can best investigate this from here please? I'm sorry this isn't very much to go on. Hopefully someone can point me in the right direction. The problem seems to be my library. It is large (3,418 packages) and I'd like to avoid rebuilding it, if possible. All packages are up to

Hi everybody, I'm trying to develop an R package with Fortran and OpenMP. I wrote a simple hello world but I'm not able to set the number of threads. I found this old email chain <http://r.789695.n4.nabble.com/Set-the-number-of-threads-using-openmp-with-C-td2284685.html> and I tried to set my compile instructions accordingly but i had no luck. *This is my makevars:*

Hi all, This occurred in R-2.11.0 (WinXP). The R-help page of .[ says that: "Character indices can in some circumstances be partially matched (see pmatch) to the names or dimnames of the object being subsetted (but never for subassignment). Unlike S (Becker et al p. 358)), R has never used partial matching when extracting by [, and as from R 2.7.0 partial matching is not by default used by

R 3.5.1 is installed under Linux Mint 19 from binaries r-base and r-base-dev from ubuntu bionic-cran35.? Mysteriously, packages using libRblas cannot be compiled.? I get: libRblas.so: cannot open shared object file: No such file or directory.? And indeed, I find no libRblas.so. Any ideas about how to fix this? Thanks, Steve

Dear all, I just found this issue: dd1 = c(rep(NaN,82), rep(-1, 144), rep(1, 74)) xx = runmed(dd1, 21) -> R crashes reproducibly in R 3.4.3, R3.4.4 (Ubuntu 14.04/Ubuntu 16.04) With GDB: Program received signal SIGSEGV, Segmentation fault. swap (l=53, r=86, window=window at entry=0xc59308, outlist=outlist at entry=0x12ea2e8, nrlist=nrlist at entry=0x114fdd8, print_level=print_level at

In the file MkRules.local.in, I see the line: USE_ATLAS = NO which I believe needs to be changed to YES. But how do I specify the BLAS file *libopenblas_haswell-r0.2.20.a *and its location? Regards, Indrajit On Tue, Feb 13, 2018 at 6:41 PM, Indrajit Sen Gupta <indrajitsg at gmail.com> wrote: > I was able to compile the R from the github by running build-r-devel.bat! > > Now need

I got this to work on Linux but it is not working on Windows. *My understanding is that this should also work on windows, is that correct?* If so, what should I do? differently? To get it to work on Linux, I modified my R script as follows: #' OpenMP Hello World #' #' @param nthreads The number of threads that you want to use #' @example #' hello(nthreads=2) #' @export