FPGA design of a multicore neuromorphic processing system

Author

Bin Zhang, University of Dayton

Date of Award

2016

Degree Name

M.S. in Electrical Engineering

Department

Department of Electrical and Computer Engineering

Advisor/Chair

Advisor: Tarek Taha

Abstract

Neuromorphic computing architecture has developed rapidly during recent years. Neuronmorphic network processor FPGA implementation is 3x and 127x faster than Intel E8400 processor with edge detection applications and ECG applications respectively. Considering resource utilization and system stability, a hardware-controlled communication routing network is a better choice than a time-delay based routing network. The separation of data lines prevents the hardware-controlled communication routing network from turning into a large network.

Keywords

Neuromorphics, Neural networks (Computer science), Adaptive routing (Computer network management), Field programmable gate arrays, Electrical Engineering, Neuronmorphic Network, micro-processor, FPGA, ultra-low power processor

Rights Statement

Copyright © 2016, author

Recommended Citation

Zhang, Bin, "FPGA design of a multicore neuromorphic processing system" (2016). Graduate Theses and Dissertations. 1160.
https://ecommons.udayton.edu/graduate_theses/1160