Technical Program

Paper Detail

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: Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
DOI: https://doi.org/10.32470/CCN.2019.1109-0
Authors: Helge √úlo 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.