Openblas and lme4
The bulk of the linear algebra calculations in lme4 are done using the Eigen C++ library which does not rely on the BLAS. Thus a multi-threaded BLAS will not affect lme4 speed to any great extent. I believe that Eigen has its own multi-thread capabilities but it has been a while since I checked. On Sat Nov 15 2014 at 8:05:00 AM Christian Brauner <
christianvanbrauner at gmail.com> wrote:
Hello,
For testing/research purposes I compiled R from source with blas as a
shared library. I then went on to compile openblas from source, tuned it
to Sandybridge and linked R against. The crucial step being:
cd /usr/local/lib/R/lib \
&& mv libRblas.so libRblas.so.old \
&& ln -s /usr/local/lib/libopenblas_sandybridgep-r0.2.12.so
libRblas.so
It worked perfectly and I see as output from /cat/pid/status:
Name: R
State: S (sleeping)
[?]
Threads: 4
[?]
Tests with the Matrix library confirm that threading works and the
increase in speed is significant for linear algebra operations such as
solve(), chol() etc.
I was wondering if lmer can make any use of this? I couldn't find a lot
on the internet. Just some posts from R-bloggers vaguely referencing
lme4 and some comments by Doug but I couldn't come to a conclusion
whether lme4 will see improvements in speed at least for larger models.
So far all my calls to lmer() on R with openblas run on a single core.
To pinpoint whether I did something wrong during compilation or if lme4
cannot reall profit from openblas I thought asking here might be a good
idea.
Best,
Christian
(For the sake of completeness: The exact compilation instructions I used
can also be found here
https://github.com/brauner/dockR/blob/master/r-patched-
ivy-openblas/Dockerfile.
Someone who runs an ivy- or sandybridge cpu and uses docker can also
pull a docker image with "docker pull brauner/rblas" and check for
himself if I did something wrong.)
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