| Paper: | PS-1A.27 | ||
| Session: | Poster Session 1A | ||
| Location: | H Lichthof | ||
| Session Time: | Saturday, September 14, 16:30 - 19:30 | ||
| Presentation Time: | Saturday, September 14, 16:30 - 19:30 | ||
| Presentation: | Poster | ||
| Publication: | 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany | ||
| Paper Title: | Scalable simulation of rate-coded and spiking neural networks on shared memory systems | ||
| Manuscript: | Click here to view manuscript | ||
| License: |  This work is licensed under a Creative Commons Attribution 3.0 Unported License. |
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| DOI: | https://doi.org/10.32470/CCN.2019.1109-0 | ||
| Authors: | Helge Ülo Dinkelbach, Julien Vitay, Fred H. Hamker, Chemnitz University of Technology, Germany | ||
| Abstract: | The size and complexity of the neural networks investigated in computational neuroscience are increasing, leading to a need for efficient neural simulation tools to support their development. Several neuro-simulators have been developed over the years by the community, all with different scopes (rate-coded, spiking, mean-field), target platforms (CPU, GPU, clusters) or modeling principles (fixed model library, code generation). We compare here the current version of the neuro-simulator ANNarchy against other state-of-the-art simulators on rate-coded and spiking benchmarks with a focus on their parallel performance. | ||