Intel compilers

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Intel compilers (2019u4 / 2019 / 2014)

C&CZ has bought together with TCM and Theoretical Chemistry two licences for concurrent use of the Intel Parallel Studio XE for Linux. Different versions have been installed in /vol/opt/intelcompilers and is available on a.o. clusternodes en loginservers. To set the environment variables correctly, SH/BASH users must first run:

source /vol/opt/intelcompilers/intel-2019u4/composerxe/bin/compilervars.sh intel64

and CSH users must run:

setenv arch intel64
source /vol/opt/intelcompilers/intel-2019u4/composerxe/bin/compilervars.csh intel64

After that, icc -V returns the version number as output. For older versions, substitute "2019u4" with "2019" or "2014".
A very useful resource is intel-mkl-link-line-advisor which will advise you on compiler and linker options for using the MKL.

Documentation for the previous version (2011)

Compiling Fortran (/opt/intel/bin/ifort)

Math Kernel Library (mkl, linking blas, lapack)

Intel Cluster Studio 2011

How to create a standalone MKL version of BLAS and LAPACK shared libraries ?

This is described in detail in Building Custom Shared Objects

  • Create a new directory (e.g. ~/lib)
 mkdir ~/lib
 cd ~/lib
  • Copy these files:
 cp /opt/intel/composerxe/mkl/tools/builder/{makefile,blas_list,lapack_list} ~/lib
  • Set the MKLROOT variable (in bash):
 MKLROOT=/opt/intel/mkl
 export MKLROOT

In tcsh use:

 setenv MKLROOT /opt/intel/mkl
  • Make the shared libraries libblas_mkl.so and liblapack_mkl.so
 make libintel64 export=blas_list interface=lp64  threading=parallel name=libblas_mkl
 make libintel64 export=lapack_list interface=lp64  threading=parallel name=liblapack_mkl

The options are described here

The newly created libblas_mkl.so and liblapack_mkl.so require

 /opt/intel/lib/intel64/libiomp5.so
 

to work. On the cluster nodes this file is automatically linked when required.

Using the MKL BLAS and LAPACK shared libraries (with Scilab)

This should work for any executable that uses a dynamically linked blas or lapack. We use Scilab as an example.

  • Make sure we have an executable, not just a script that calls the executable:
 file scilab-bin

The output looks something like this:

 scilab-bin: ELF 64-bit LSB executable, x86-64, version 1 (SYSV), dynamically linked (uses shared libs), for GNU/Linux 2.6.15 ...
  • Determine the exact name that is used by the executable:
 ldd scilab-bin | grep blas

The output could be:

 libblas.so.3gf => ~/sciab-5.4.1/lib/thirdparty/libblas.so.3gf
  • Replace the library with a link to the MKL version
 cd ~/sciab-5.4.1/lib/thirdparty/
 rm libblas.so.3gf
 ln -s ~/lib/libblas_mkl.so libblas.so.3gf

Also follow this procedure for lapack.

  • To use more than one thread, i.e., for parallel computation, set:
 MKL_NUM_THREADS=4
 export MKL_NUM_THREADS

This example will use 4 cores.

  • To check the number of cores available, use:
 cat /proc/cpuinfo | grep processor | wc