6 papers
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…
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…
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…
Scalable Construction of Spiking Neural Networks using up to thousands of GPUs
Bruno Golosio, Gianmarco Tiddia, José Villamar +10
Diverse scientific and engineering research areas deal with discrete, time-stamped changes in large systems of interacting delay differential equations. Simulating such complex sys…
Event-driven eligibility propagation in large sparse networks: efficiency shaped by biological realism
Agnes Korcsak-Gorzo, Jesús A. Espinoza Valverde, Jonas Stapmanns +5
Despite remarkable technological advances, AI systems may still benefit from biological principles, such as recurrent connectivity and energy-efficient mechanisms. Drawing inspirat…
Constructive community race: full-density spiking neural network model drives neuromorphic computing
Johanna Senk, Anno C. Kurth, Steve Furber +18
The local circuitry of the mammalian brain is a focus of the search for generic computational principles because it is largely conserved across species and modalities. In 2014 a mo…