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A generic reconfigurable neural network architecture as a network on chip

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5 Author(s)

Neural networks are widely used in pattern recognition, security applications and data manipulation. We propose a hardware architecture for a generic neural network, using network on chip (NoC) interconnect. The proposed architecture allows for expandability, mapping of more than one logical unit onto a single physical unit, and dynamic reconfiguration based on application-specific demands. Simulation results show that this architecture has significant performance benefits over existing architectures.

Published in:

SOC Conference, 2004. Proceedings. IEEE International

Date of Conference:

12-15 Sept. 2004