Neuroscience research has become increasingly interdisciplinary in recent years. New imaging technologies deliver ultra-high resolution images, and new simulator technology enables scientists to simulate larger and more detailed neural networks. Such data can no longer be analysed and such simulations can no longer be run solely on a user’s computer in the office: clusters, supercomputers and good data management strategies have become indispensable. This HBP Education Workshop will set the grounds for the students to get started with high-performance computing (HPC)-based research and thus lays the foundation for them to advance the state of the art in their fields.
The workshop will teach the basics of supercomputing needed for starting to use HPC systems for (neuroscience) research. This includes on the one hand introductory lectures with hands-on sessions about scientific computing in Python and an introduction to the usage of HPC systems and (big) data management. On the other hand, the students will get hands-on training for tools and applications that can both be used on a supercomputer as well as on the user’s local computer, for instance the simulators NEST (for point-neuron models) and Arbor (for morphologically detailed neuron models), and visualisation tools that can handle large imaging or simulation data as generated on a supercomputer. The tools and applications presented are developed in the HBP High Performance Analytics and Computing (HPAC) Platform. The introductory lectures also enable the students to make efficient use of the other HBP Platforms, in particular the Neuroinformatics, the Brain Simulation and the Neurorobotics Platforms that use the HPAC Platform as a back-end.
A prior experience with at least one programming language (e.g. Python, C or C++) is highly recommended.
Application deadline: 3 June 2019