Abstract:

Today, simulation technology for spiking neuronal networks offers manifold possibilities to computational neuroscientists - from studying small networks on laptops in an interactive fashion to exploring the dynamics of brain-scale models on supercomputers. In the case of the NEST simulator, the development of simulation code that enables such a wide range of application goes hand in hand with the development of efficient methods that enable the systematic analysis of different simulator components with respect to memory usage and run time for different regimes of number of processes. The 90-minutes lecture will be mainly concerned with neuronal network simulation technology: What are the challenges of contemporary supercomputers and how can we efficiently adapt the simulation code in order to meet these challenges? Besides, I will give a general introduction to the NEST simulator. The 45-minutes tutorial will provide basic knowledge on how to control a simulation with NEST. The tutorial will also be useful for students that are interested in the topic of reproducibility of scientific results in computational neuroscience as I will analyze a popular simulation study that uses home brew code in order to try and reproduce some of the findings with NEST.

About lecturer:

Ms. Susanne Kunkel