[R-sig-hpc] Choosing Intel MKL BLAS when compiling R

[Jonathan Greenberg]

Ok, so I did a new test and installed a local version of GotoBLAS
(OpenBLAS fork), used alternatives --install, and its working
perfectly.  According to your paper, I'm probably good to go (you got
the best results from GotoBLAS, right?)  However, just to see if I can
settle the issue (I have colleagues who would prefer to use Intel
MKL's BLAS), can you advise on how to properly link against the Intel
MKL libraries based on the previous error I reported?  What is the
specific file I should be pointing R towards?

***

Error in dyn.load(file, DLLpath = DLLpath, ...) :
 unable to load shared object
'/usr/apps/oa/lib64/R/library/stats/libs/stats.so':
 /usr/apps/oa/lib64/R/library/stats/libs/stats.so: undefined symbol: dswap_
During startup - Warning message:
package 'stats' in options("defaultPackages") was not found

***

--j


On Tue, Nov 1, 2011 at 4:09 PM, Dirk Eddelbuettel <edd at debian.org> wrote:
>
> On 1 November 2011 at 15:40, Jonathan Greenberg wrote:
> | Dirk:
> |
> | Thanks -- I was able to get this running on a Debian box previously
> | (http://lostingeospace.blogspot.com/2010/07/multithreaded-r-using-blas-in-debian_28.html)
> | but I'm having trouble figuring out specific steps I need to do to
> | choose the Intel MKL BLAS, particularly now that I don't have a
> | package manager to rely on -- is it an issue of using
> | update-alternatives?  How can I check to see what R is currently
> | using?
>
> By examining the Makefile(s) created after configure, as well as the
> configure logs.  "My" builds for Debian end the configure step in
>
> R is now configured for i486-pc-linux-gnu
>
>  Source directory:          .
>  Installation directory:    /usr
>
>  C compiler:                gcc -std=gnu99  -O3 -pipe  -g
>  Fortran 77 compiler:       gfortran  -O3 -pipe  -g
>
>  C++ compiler:              g++  -O3 -pipe  -g
>  Fortran 90/95 compiler:    gfortran -O3 -pipe  -g
>  Obj-C compiler:
>
>  Interfaces supported:      X11, tcltk
>  External libraries:        readline, BLAS(generic), LAPACK(generic), lzma
>  Additional capabilities:   PNG, JPEG, TIFF, NLS, cairo
>  Options enabled:           shared R library, R profiling, memory profiling, Java
>
>  Recommended packages:      no
>
>
> which shows you that external Blas and Lapack are used -- that's needed for
> the drop-in behaviour which you then deal with at the dynamoc linker stage
> (eg with LD_PRELOAD etc).
>
> Dirk
>
> --
> "Outside of a dog, a book is a man's best friend. Inside of a dog, it is too
> dark to read." -- Groucho Marx
>



-- 
Jonathan A. Greenberg, PhD
Assistant Professor
Department of Geography
University of Illinois at Urbana-Champaign
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