New Intel compilers (Intel OneAPI Base and HPC Toolkits)

The newest versions of the Intel compilers, available under the name Intel OneAPI, do no longer require a license, they are freely available. The 2023.2 version has been installed on C&CZ managed Ubuntu systems. When they are available, the module command

module avail

will list among others “compiler/latest”, so e.g. the Intel C (icc) and Fortran (ifort) compilers can be used after typing

module add compiler/latest

Old Intel compilers (2019u5 / 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-2019u5/composerxe/bin/ intel64

and CSH users must run:

setenv arch intel64
source /vol/opt/intelcompilers/intel-2019u5/composerxe/bin/compilervars.csh intel64

After that, icc -V returns the version number as output. For older versions, substitute “2019u5” with “2019u4”, “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):

export MKLROOT

In tcsh use:

setenv MKLROOT /opt/intel/mkl

  • Make the shared libraries and

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 and require


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: => ~/sciab-5.4.1/lib/thirdparty/

  • Replace the library with a link to the MKL version

cd ~/sciab-5.4.1/lib/thirdparty/
ln -s ~/lib/

Also follow this procedure for lapack.

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


This example will use 4 cores.

  • To check the number of cores available, use:

cat /proc/cpuinfo | grep processor | wc