This really is the wrong list (R-devel or R-SIG-HPC?): see the posting
guide. But there are two issues.
- How your BLAS controls its core usage (which is in its documentation).
- How your third-party package interacts with a BLAS which uses multiple
cores, and for that you need to ask the package maintainers.
On 24/11/2013 09:03, Safiye Celik wrote:
Hi,
I am trying to use GotoBLAS2 on R 3.0 on Unix. I downloaded GotoBLAS2
source code from TACC web site, compiled it, and replaced libRblas.so with
libgoto2.so, following the instructions at the link
http://www.rochester.edu/college/gradstudents/jolmsted/files/computing/BLAS.pdf.
Much better to use the definitive R documentation at
http://cran.r-project.org/doc/manuals/r-release/R-admin.html#Shared-BLAS .
The simple matrix operations in R like "determinant" are 20 times faster
than before (I am using huge matrices), which is good. However, I cannot
use many cores in parallel now.
For example, below code runs forever. But if I use commented out "for"
instead of "foreach", it takes just a second. When I was using R's default
BLAS library, I could run below code (using many cores) (but it took more
time since BLAS was not optimized, of course)..
library("foreach")
library("doParallel")
registerDoParallel(cores=2)set.seed(100)
foreach (i = 1:2) %dopar% {# for (i in 1:2) {
a = replicate(1000, rnorm(1000))
d = determinant(a)
So, is it possible to use many cores at the same time with GotoBLAS2, do
you have any ideas?
Thanks a lot in advance.
--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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