Leibniz hardware

The Leibniz cluster is the default UAntwerp cluster. Besides regular compute nodes, it contains 2 NVIDIA GPU compute nodes, and a visualization node.

For larger jobs, consider using the newer Vaughan. For smaller jobs, longer jobs or batches of single core jobs, consider using the Breniac nodes.

Compute nodes

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).

CPU compute nodes

The maximum execution wall time for jobs is 3 days (72 hours).

Slurm partition	nodes	processors per node	memory	local disk	network
broadwell	144	2x 14-core Xeon E5-2680v4 @2.4 GHz	128 GB	120 GB SSD	EDR-IB
broadwell_256	8	2x 14-core Xeon E5-2680v4 @2.4 GHz	256 GB	120 GB SSD	EDR-IB

GPU compute nodes

The maximum execution wall time for jobs is 1 day (24 hours).

Slurm partition	nodes	GPUs per node	GPU memory	processors per node	memory	local disk	network
pascal_gpu	2	2x NVIDIA Tesla P100 (Pascal)	16 GB HBM2	2x 14-core Xeon E5-2680v4 @2.4 GHz	128 GB	120 GB	EDR-IB

See also

See Requesting GPUs for more information on using the GPU nodes.

Login infrastructure

You can log in to the Leibniz cluster using SSH via login-leibniz.hpc.uantwerpen.be.

Alternatively, you can also log in directly to the login nodes or the visualization node using one of the following hostnames. From inside the VSC network (e.g., when connecting from another VSC cluster), use the internal interface names.

Login node	External interface	Internal interface
generic name	login-leibniz.hpc.uantwerpen.be	login.leibniz.antwerpen.vsc
per node	login1-leibniz.hpc.uantwerpen.be login2-leibniz.hpc.uantwerpen.be	login1.leibniz.antwerpen.vsc login2.leibniz.antwerpen.vsc
visualization node	viz1-leibniz.hpc.uantwerpen.be	viz1.leibniz.antwerpen.vsc

Note

Direct login is possible to all login nodes and to the visualization node from within Belgium only. From outside of Belgium, a VPN connection to the UAntwerp network is required.

• 2 login nodes

  • 2x 14-core Xeon E5-2680v4 CPUs@2.4 GHz (Broadwell)

  • 256 GB RAM

  • 2x 1 TB HDD local disk (raid 1)

• 1 visualization node

  • 2x 14-core Xeon E5-2680v4 CPUs@2.4 GHz (Broadwell)

  • 1 NVIDIA Quadro P5000

  • 256 GB RAM

  • 2x 1 TB HDD local disk (raid 1)

  • Instructions for using the visualization node

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).

See also

For general information about the compiler toolchains, please see the shared Intel toolchain and FOSS toolchain documentation.

Optimization options for the Intel compilers

To optimize for Leibniz, compile on the Leibniz login or compute nodes. Use either -xHost or Broadwell architecture specific options, and combine this 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).

Warning If you forget these options, the default for the Intel compilers is to generate code using optimization level -O2 for architecture -march=pentium4. While -O2 gives pretty good results, compiling for the Pentium 4 architecture uses none of the new instructions nor the vector instructions introduced since 2005.

Optimization options for the GNU compilers

To optimize for Leibniz, compile on the Leibniz login or compute nodes. Sse the -march=native or -march=broadwell architecture options, and combine this 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.

Warning If you forget to specify 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.

History

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 an EDR InfiniBand network, 144 of these nodes having 128 GB RAM and the other 8 nodes having 256 GB RAM. Leibniz also contains a node for visualization and 2 GPU nodes with two NVIDIA Tesla P100 GPU compute cards. All nodes are connected using an InfiniBand EDR network.

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.