214 citations · 2.3k across the 48 of their papers we have counts for
7 papers · 1 filter
A Modular Workflow for Performance Benchmarking of Neuronal Network Simulations
Jasper Albers, Jari Pronold, Anno Christopher Kurth +9
Modern computational neuroscience strives to develop complex network models to explain dynamics and function of brains in health and disease. This process goes hand in hand with ad…
Sub-realtime simulation of a neuronal network of natural density
Anno C. Kurth, Johanna Senk, Dennis Terhorst +2
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 t…
Sequence learning, prediction, and replay in networks of spiking neurons
Younes Bouhadjar, Dirk J. Wouters, Markus Diesmann +1
Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm re…
Connectivity Concepts in Neuronal Network Modeling
Johanna Senk, Birgit Kriener, Mikael Djurfeldt +7
Sustainable research on computational models of neuronal networks requires published models to be understandable, reproducible, and extendable. Missing details or ambiguities about…
Routing brain traffic through the von Neumann bottleneck: Efficient cache usage in spiking neural network simulation code on general purpose computers
Jari Pronold, Jakob Jordan, Brian J. N. Wylie +3
Simulation is a third pillar next to experiment and theory in the study of complex dynamic systems such as biological neural networks. Contemporary brain-scale networks correspond…
Routing brain traffic through the von Neumann bottleneck: Parallel sorting and refactoring
Jari Pronold, Jakob Jordan, Brian J. N. Wylie +3
Generic simulation code for spiking neuronal networks spends the major part of time in the phase where spikes have arrived at a compute node and need to be delivered to their targe…