Optimized Simulation Framework for Spiking Neural Networks using GPU's

This paper presents a hardware accelerated model of a spiking neural network implemented in CUDA C. It does a short description of the mathematical model for the neural network and presents the implementation on the GPU. Additionally, it presents three methods of further accelerating the model by el...

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Bibliographic Details
Published in:Advances in electrical and computer engineering 2012-05, Vol.12 (2), p.61-68
Main Authors: MIRSU, R., MICUT, S., CALEANU, C., MIRSU, D. B.
Format: Article
Language:English
Subjects:
artificial intelligence
biological neural networks
GPU computing
parallel processing
spiking neural networks
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Summary:This paper presents a hardware accelerated model of a spiking neural network implemented in CUDA C. It does a short description of the mathematical model for the neural network and presents the implementation on the GPU. Additionally, it presents three methods of further accelerating the model by eliminating excess kernel launch overhead time, efficiently using shared memory and overlapping computation with data transfer. Finally, the implementation is benchmarked against an existing C++ equivalent model.
ISSN:1582-7445
1844-7600
DOI:10.4316/aece.2012.02011