Compile r with mkl (With mulithreads support) - multithreading

Question

I compiled R by regarding these guides:
http://www.r-bloggers.com/compiling-64-bit-r-2-10-1-with-mkl-in-linux/
http://cran.r-project.org/doc/manuals/R-admin.html#MKL
But for matrix algebra R does not use all available CPUs.
I tried both:
MKL="-L${MKL_LIB_PATH} -lmkl_gf_lp64 -lmkl_gnu_thread \
-lmkl_core -fopenmp -lpthread"
and
MKL=" -L${MKL_LIB_PATH} \
-Wl,--start-group \
${MKL_LIB_PATH}/libmkl_gf_lp64.a \
${MKL_LIB_PATH}/libmkl_gnu_thread.a \
${MKL_LIB_PATH}/libmkl_core.a \
-Wl,--end-group \
-lgomp -lpthread"
Options.
How can I force R to use all available CPUs?
How can I check whether R use MKL or not?

Answer 1

I would like to add my procedure to compile R 3.0.1 with MKL libraries. I am using Debian 7.0 on a core i7 intel processor, 8G RAM. First i installed the MKL libraries, after i set MKL related environment variables (MKLROOT and LD_LIBRARY_PATH) with this command:
>source /opt/intel/mkl/bin/mklvars.sh intel64
So i used the following parameters to ./configure:
>./configure --enable-R-shlib --enable-threads=posix --with-lapack --with-blas="-fopenmp -m64 -I$MKLROOT/include -L$MKLROOT/lib/intel64 -lmkl_gf_lp64 -lmkl_gnu_thread -lmkl_core -lpthread -lm"
and finished the installation with make and make install.
As a benchmark, i did a product between two 5000 x 5000 matrix product without MKL and got:
user system elapsed
57.455 0.104 29.033
and after compiling:
user system elapsed
15.993 0.176 4.333
a real gain!

Answer 2

All this is now a lot easier -- a short blog post is here discussing the steps below in detail.
But in short, all you need is this:
## get archive key
cd /tmp
wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB
apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB
## add MKL to apt's repo list
sh -c 'echo deb https://apt.repos.intel.com/mkl all main > /etc/apt/sources.list.d/intel-mkl.list'
## update and install (500+ mb download, 1.9gb installed)
apt-get update
apt-get install intel-mkl-64bit-2018.2-046
## make it system default via update alternatives
update-alternatives --install /usr/lib/x86_64-linux-gnu/libblas.so libblas.so-x86_64-linux-gnu /opt/intel/mkl/lib/intel64/libmkl_rt.so 50
update-alternatives --install /usr/lib/x86_64-linux-gnu/libblas.so.3 libblas.so.3-x86_64-linux-gnu /opt/intel/mkl/lib/intel64/libmkl_rt.so 50
update-alternatives --install /usr/lib/x86_64-linux-gnu/liblapack.so liblapack.so-x86_64-linux-gnu /opt/intel/mkl/lib/intel64/libmkl_rt.so 50
update-alternatives --install /usr/lib/x86_64-linux-gnu/liblapack.so.3 liblapack.so.3-x86_64-linux-gnu /opt/intel/mkl/lib/intel64/libmkl_rt.so 50
## tell ldconfig
echo "/opt/intel/lib/intel64" > /etc/ld.so.conf.d/mkl.conf
echo "/opt/intel/mkl/lib/intel64" >> /etc/ld.so.conf.d/mkl.conf
ldconfig
That's it. Nothing else. Not recompiling or linking. And for example R now shows in sessionInfo() :
Matrix products: default
BLAS/LAPACK: /opt/intel/compilers_and_libraries_2018.2.199/linux/mkl/lib/intel64_lin/libmkl_rt.so

Answer 3

(not a real answer: I don't use MKL, I use OpenBlas as shared BLAS as described in the R-admin manual.)
As quick check whether the optimized BLAS is used I do a matrix multiplication. Even if only 1 core is used, this should be faster for the optimized BLAS than for the standard BLAS R comes with.
To check how many cores are in use, I look at top (or a CPU usage graph/monitor) during the matrix multiplication.
There has been trouble in the past with CPU affinity, so that a BLAS would start $n$ threads, but they were all running on the same core, see Parallel processing in R limited.
r-devel (3.0.0-to-be) has a function to set the CPU affinity.

Answer 4

A complete tutorial is available here:
https://software.intel.com/en-us/articles/build-r-301-with-intel-c-compiler-and-intel-mkl-on-linux
or simply using:
http://mran.revolutionanalytics.com/download/