26 citations · 61 across the 7 of their papers we have counts for
9 papers
Fast and Flexible Spiking Network Simulations on Massively Distributed On-Chip Memory Accelerators
Catherine Mia Schöfmann, Jan Finkbeiner, Jan Vogelsang +1
Studying brain function and dysfunction in spiking networks with realistic synaptic densities pushes simulation technology beyond its current limits. It requires simulations substa…
Rewiring of adult neural networks - learning from structural plasticity across multiple scales
Michael Fauth, Han Lu, Jannik Luboeinski +36
Synaptic connections are continuously formed and eliminated even in adult neuronal networks. This process - called structural plasticity - allows networks to change their topology…
NUMA balancing hampering performance of spiking network simulations
Melissa Lober, Alp Inangu, Gorka Peraza Coppola +9
Computing centers today mostly operate conventional CPU- and GPU-based systems, where the direct way of decreasing energy consumption is a reduction in the applications' runtime. N…
Continuous benchmarking: Keeping pace with an evolving ecosystem of models and technologies
Jan Vogelsang, Melissa Lober, Catherine Mia Schöfmann +7
Drawing on ideas from continuous integration, we present concepts of an automated benchmarking pipeline for high performance applications. Customization and collaboration have been…
Exploiting network topology in brain-scale simulations of spiking neural networks
Melissa Lober, Markus Diesmann, Susanne Kunkel
Simulation code for conventional supercomputers serves as a reference for neuromorphic computing systems. The present bottleneck of distributed large-scale spiking neuronal network…
Phenomenological modeling of diverse and heterogeneous synaptic dynamics at natural density
Agnes Korcsak-Gorzo, Charl Linssen, Jasper Albers +9
This chapter sheds light on the synaptic organization of the brain from the perspective of computational neuroscience. It provides an introductory overview on how to account for em…
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…
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…