Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
The NEURON simulation environment
Neural Computation
Fast calculation of short-term depressing synaptic conductances
Neural Computation
The Book of Genesis: Exploring Realistic Neural Models with the General Neural Simulation System
The Book of Genesis: Exploring Realistic Neural Models with the General Neural Simulation System
Spiking Neuron Models: An Introduction
Spiking Neuron Models: An Introduction
Detailed Parallel Simulation of a Biological Neuronal Network
IEEE Computational Science & Engineering
Event-driven simulation of spiking neurons with stochastic dynamics
Neural Computation
µsik " A Micro-Kernel for Parallel/Distributed Simulation Systems
Proceedings of the 19th Workshop on Principles of Advanced and Distributed Simulation
Which model to use for cortical spiking neurons?
IEEE Transactions on Neural Networks
µsik " A Micro-Kernel for Parallel/Distributed Simulation Systems
Proceedings of the 19th Workshop on Principles of Advanced and Distributed Simulation
Scaling time warp-based discrete event execution to 104 processors on a Blue Gene supercomputer
Proceedings of the 4th international conference on Computing frontiers
Macro-Micro Economic System Simulation
Proceedings of the 21st International Workshop on Principles of Advanced and Distributed Simulation
Parallel discrete-event simulation of population dynamics
Proceedings of the 40th Conference on Winter Simulation
Accelerating event based simulation for multi-synapse spiking neural networks
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
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Neural systems are composed of a large number of highly-connected neurons and are widely simulated within the neurological community. In this paper, we examine the application of parallel discrete event simulation techniques to networks of a complex model called the Hodgkin-Huxley neuron[1]. We describe the conversion of this model into an event-driven simulation, a technique that offers the potential of much greater performance in parallel and distributed simulations compared to time-stepped techniques. We report results of an initial set of experiments conducted to determine the feasibility of this parallel event-driven Hodgkin-Huxley model and analyze its viability for large-scale neural simulations.