2.1.2. Leibniz hardware#

The Leibniz cluster was installed in the spring of 2017. It is a NEC system consisting of 152 compute nodes with dual 14-core Intel E5-2680v4 Broadwell generation CPUs connected through a EDR InfiniBand network. 144 of these nodes have 128 GB RAM, the other 8 have 256 GB RAM. The nodes do not have a sizeable local disk.

Leibniz also contains a node for visualisation and 3 node types for experimenting with accelerators: 2 nodes for GPU computing with two NVIDIA Tesla P100 GPU compute cards, 1 node with dual NEC SX-Aurora TSUBASA vector processors and 1 node with an Intel Xeon Phi expansion board.

Access restrictions#

Access is available for faculty, students (master’s projects under faculty supervision), and researchers of the AUHA. The cluster is integrated in the VSC network and runs the standard VSC software setup. It is also available to all VSC users, though we appreciate that you contact the UAntwerp support team so that we know why you want to use the cluster.

Jobs can have a maximal execution wall time of 3 days (72 hours). On the accelerator nodes, a shorter wall time of 1 day applies. For big parallel jobs, consider using the newer cluster Vaughan, which has nodes with 64 cores.

Hardware details#

All nodes are connected using an InfiniBand EDR network. The regular compute nodes are logically organised in 5 islands with 24 nodes, 1 island with 22 nodes and 1 island with 10 nodes (including the 8 nodes with 256 GB RAM). Storage is provided through the central UAntwerp storage system.

Login infrastructure#

Direct login is possible to both login nodes and to the visualization node.

  • From outside the VSC network: use the external interface names. Note that from outside of Belgium, a VPN connection to the UAntwerp network is required.

  • From inside the VSC network (e.g., another VSC cluster): use the internal interface names.


External interface

Internal interface

Login node (generic name)



Login node (per node)





Visualisation node



Available resources#

Characteristics of the compute nodes#

Leibniz is running the Slurm Workload Manager as its resource manager and scheduler. We do not support the PBS compatibility layer but encourage users to develop proper Slurm job scripts as one can then fully exploit the Slurm features and enjoy the power of the srun command when starting processes.

Make sure to read the following pages which give a lot of information on Slurm and how to convert your Torque scripts:

To remain compatible with the typical VSC setup, a number of features can be used in job scripts (e.g. with Slurm’s --constraint option). However, only the following features are really useful in the current setup of Leibniz to select regular compute nodes based on the amount of available memory.




Use nodes with 128 GB RAM (roughly 112 GB available). This is the majority of the regular compute nodes on Leibniz. Requesting this as a feature ensures that you only get nodes with 128 GB of memory and keep the nodes with more memory available for other users who really need that feature.


Use nodes with 256 GB RAM (roughly 240 GB available). This property is useful if you submit a batch of jobs that require more than 4 GB of memory per processor but do not use all cores and you do not want to use a tool such as Worker to bundle jobs yourself, as it helps the scheduler to put those jobs on nodes that can be further filled with your jobs.

Available partitions#

When submitting a job with sbatch or using srun, you can choose to specify the partition your job is submitted to. When the option is omitted, your job is submitted to the default partition (broadwell).

The following partitions are available:




Default. Maximum wall time of 3 days.


Submit to the Pascal GPU nodes.

Compiling for Leibniz#

To compile code for Leibniz, all intel, foss and GCC modules can be used (the latter being equivalent to foss but without MPI and the math libraries).

Optimization options for the Intel compilers#

To optimize specifically for Leibniz, compile on the Leibniz login or compute nodes and combine the option -xHost with either optimization level -O2 or -O3. For some codes, the additional optimizations at level -O3 actually produce slower code (often the case if the code contains many short loops).

Note that if you forget these options, the default for the Intel compilers is to generate code using optimization level -O2 (which is pretty good) but for the Pentium 4 (-march=pentium4) which uses none of the new instructions and hence also none of the vector instructions introduced since 2005, which is pretty bad. Hence always specify -xHost (or any of the equivalent architecture options specifically for Broadwell for specialists) when compiling code.

Optimization options for the GNU compilers#

Never use the default GNU compilers installed on the system, but always load one of the foss or GCC modules.

To optimize for Leibniz, compile on the Leibniz login or compute nodes and combine either the option -march=native or -march=broadwell with either optimization level -O2 or -O3. In most cases, and especially for floating point intensive code, -O3 will be the preferred optimization level with the GNU compilers as it only activates vectorization at this level whereas the Intel compilers already offer vectorization at level -O2.

Note that if you forget these options, the default for the GNU compilers is to generate unoptimized (level -O0) code for a very generic CPU (-march=x86-64) which doesn’t exploit the performance potential of the Leibniz CPUs at all. Hence one should always specify an appropriate architecture (the -march flag) and appropriate optimization level (the -O flag) as explained in the previous paragraph.

Further documentation:#

Origin of the name#

Leibniz is named after Gottfried Wilhelm Leibniz, a German multi-disciplinary scientist living in the late 17th and early 18th century. Leibniz may be best known as a developer of differential and integral calculus, independently of the work of Isaac Newton. But his contributions to science do not stop there. Leibniz also refined the binary number system, the foundation of nearly all modern computers. He also designed mechanical calculators on which one could do the four basic operations (add, subtract, multiply and divide). In all, Leibniz made contributions to philosophy, mathematics, physics and technology, and several other fields.