Modular Supercomputing for Neuroscience

Abstract

The precise simulation of the human brain requires coupling different models in order to cover the different physiological and functional aspects of this extremely complex organ. Each of this brain models is implemented following specific mathematical and programming approaches, potentially leading to diverging computational behaviour and requirements. Such situation is the typical use case that can benefit from the Modular Supercomputing Architecture (MSA), which organizes heterogeneous computing resources at system level. This architecture and its corresponding software environment enable to run each part of an application or a workflow on the best suited hardware.This paper presents the MSA concept covering current hardware and software implementations, and describes how the neuroscientific workflow resulting of coupling the codes NEST and Arbor is being prepared to exploit the MSA.

Modular Supercomputing and its Role in Europe’s Exascale Computing Strategy

“…As part of the DEEP project series, several co-design applications were selected. Six of these applications have been ported to the DEEP-EST prototype system [19,25,26]. Most of the codes combine HPC computation with advanced data processing and analytics.…”