3 citations · 3 across the 6 of their papers we have counts for
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…
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…
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…