Jochen Martin Eppler
Affiliations: | Computational and Systems Neuroscience | Research Center Juelich, Jülich, Nordrhein-Westfalen, Germany |
Area:
Parallel and Distributed Computing, Neural SimulationsGoogle:
"Jochen Eppler"Mean distance: 16.6 (cluster 17) | S | N | B | C | P |
Parents
Sign in to add mentorMarkus Diesmann | grad student | 2006-2009 | University of Freiburg |
Marc-Oliver Gewaltig | grad student | 2006-2009 | Honda Research Institute Europe GmbH |
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Publications
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Feldotto B, Eppler JM, Jimenez-Romero C, et al. (2022) Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure. Frontiers in Neuroinformatics. 16: 884180 |
Blundell I, Brette R, Cleland TA, et al. (2018) Code Generation in Computational Neuroscience: A Review of Tools and Techniques. Frontiers in Neuroinformatics. 12: 68 |
Blundell I, Plotnikov D, Eppler JM, et al. (2018) Automatically Selecting a Suitable Integration Scheme for Systems of Differential Equations in Neuron Models. Frontiers in Neuroinformatics. 12: 50 |
Ippen T, Eppler JM, Plesser HE, et al. (2017) Constructing Neuronal Network Models in Massively Parallel Environments. Frontiers in Neuroinformatics. 11: 30 |
Kunkel S, Schmidt M, Eppler JM, et al. (2014) Spiking network simulation code for petascale computers. Frontiers in Neuroinformatics. 8: 78 |
Djurfeldt M, Davison AP, Eppler JM. (2014) Efficient generation of connectivity in neuronal networks from simulator-independent descriptions. Frontiers in Neuroinformatics. 8: 43 |
Davison AP, Djurfelt M, Eppler JM, et al. (2013) An integration layer for neural simulation: PyNN in the software forest F1000research. 4 |
Kunkel S, Schmidt M, Eppler JM, et al. (2013) From laptops to supercomputers: a single highly scalable code base for spiking neuronal network simulations Bmc Neuroscience. 14 |
Nowke C, Hentschel B, Kuhlen T, et al. (2013) Interactive visualization of brain-scale spiking activity Bmc Neuroscience. 14 |
Helias M, Kunkel S, Masumoto G, et al. (2012) Supercomputers ready for use as discovery machines for neuroscience. Frontiers in Neuroinformatics. 6: 26 |