This title appears in the Scientific Report :
2014
Please use the identifier:
http://dx.doi.org/10.3389/fninf.2014.00043 in citations.
Please use the identifier: http://hdl.handle.net/2128/7904 in citations.
Efficient generation of connectivity in neuronal networks from simulator-independent descriptions
Efficient generation of connectivity in neuronal networks from simulator-independent descriptions
Simulator-independent descriptions of connectivity in neuronal networks promise greater ease of model sharing, improved reproducibility of simulation results, and reduced programming effort for computational neuroscientists. However, until now, enabling the use of such descriptions in a given simula...
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Personal Name(s): | Djurfeldt, Mikael (Corresponding Author) |
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Davison, Andrew P. / Eppler, Jochen M. | |
Contributing Institute: |
Computational and Systems Neuroscience; IAS-6 Computational and Systems Neuroscience; INM-6 |
Published in: | Frontiers in neuroinformatics, 8 (2014) S. 43 |
Imprint: |
Lausanne
Frontiers Research Foundation
2014
|
DOI: |
10.3389/fninf.2014.00043 |
PubMed ID: |
24795620 |
Document Type: |
Journal Article |
Research Program: |
Brain-Scale Simulations Helmholtz Alliance on Systems Biology Supercomputing and Modelling for the Human Brain Theory, modelling and simulation Signalling Pathways and Mechanisms in the Nervous System Brain-inspired multiscale computation in neuromorphic hybrid systems |
Link: |
Get full text OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://hdl.handle.net/2128/7904 in citations.
Simulator-independent descriptions of connectivity in neuronal networks promise greater ease of model sharing, improved reproducibility of simulation results, and reduced programming effort for computational neuroscientists. However, until now, enabling the use of such descriptions in a given simulator in a computationally efficient way has entailed considerable work for simulator developers, which must be repeated for each new connectivity-generating library that is developed. We have developed a generic connection generator interface that provides a standard way to connect a connectivity-generating library to a simulator, such that one library can easily be replaced by another, according to the modeler's needs. We have used the connection generator interface to connect C++ and Python implementations of the previously described connection-set algebra to the NEST simulator. We also demonstrate how the simulator-independent modeling framework PyNN can transparently take advantage of this, passing a connection description through to the simulator layer for rapid processing in C++ where a simulator supports the connection generator interface and falling-back to slower iteration in Python otherwise. A set of benchmarks demonstrates the good performance of the interface. |