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DAMNED: A Distributed and Multithreaded Neural Event-Driven simulation framework
- Publication Year :
- 2006
- Publisher :
- HAL CCSD, 2006.
-
Abstract
- In a Spiking Neural Networks (SNN), spike emissions are sparsely and irregularly distributed both in time and in the network architecture. Since a current feature of SNNs is a low average activity, efficient implementations of SNNs are usually based on an Event-Driven Simulation (EDS). On the other hand, simulations of large scale neural networks can take advantage of distributing the neurons on a set of processors (either workstation cluster or parallel computer). This article presents DAMNED, a large scale SNN simulation framework able to gather the benefits of EDS and parallel computing. Two levels of parallelism are combined: Distributed mapping of the neural topology, at the network level, and local multithreaded allocation of resources for simultaneous processing of events, at the neuron level. Based on the causality of events, a distributed solution is proposed for solving the complex problem of scheduling without synchronization barrier.<br />Comment: 6 pages
- Subjects :
- FOS: Computer and information sciences
Quantitative Biology::Neurons and Cognition
Scheduling
Computer Science::Neural and Evolutionary Computation
Computer Science - Neural and Evolutionary Computing
[SCCO.COMP]Cognitive science/Computer science
[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]
Machine Learning (cs.LG)
Spiking Neural Networks
Computer Science - Learning
Multi-threading
Parallel Computing
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]
Event-Driven Simulations
Neural and Evolutionary Computing (cs.NE)
[INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....8c26ae47eb7d08a639360bfb0285a958