Sustainable research on computational models of neuronal networks requires published
models to be understandable, reproducible, and extendable. Missing details or ambiguities …

Elucidating the intricate neural mechanisms underlying brain functions requires integrative
brain dynamics modeling. To facilitate this process, it is crucial to develop a general-purpose …

More than half of the Top 10 supercomputing sites worldwide use GPU accelerators and
they are becoming ubiquitous in workstations and edge computing devices. GeNN is a C++ …

Mature simulation systems for Spiking Neural Networks (SNNs) become more relevant than
ever for understanding the brain and supporting neuromorphic computing. The CARL-sim …

Simulating the brain-body-environment trinity in closed loop is an attractive proposal to
investigate how perception, motor activity and interactions with the environment shape brain …

Full scale simulations of neuronal network models of the brain are challenging due to the
high density of connections between neurons. This contribution reports run times shorter …

Spiking Neural Networks (SNNs) are currently the most widely used computing model for
neuroscience communities. There is also an increasing research interest in exploring the …

Spiking neural network models are increasingly establishing themselves as an effective tool
for simulating the dynamics of neuronal populations and for understanding the relationship …

Large-scale brain simulation allows us to understand the interaction of vast numbers of
neurons having nonlinear dynamics to help understand the information processing …

We propose and discuss a platform overarching benchmark suite for neuromorphic
hardware. This suite covers benchmarks from low-level characterization to high-level …