| Autor: |
Tarek M. Taha, Hua Chen, Bin Zhang, Yangjie Qi, Raqibul Hasan |
| Rok vydání: |
2014 |
| Předmět: |
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| Zdroj: |
NAECON 2014 - IEEE National Aerospace and Electronics Conference. |
| DOI: |
10.1109/naecon.2014.7045812 |
| Popis: |
The Interest in specialized neuromorphic computing architectures has been increasing recently, and several applications have been shown to be capable of being accelerated on such a platform. This paper describes the implementation of a multicore digital neuromorphic processing system on an Altera Quartus II FPGA. Static routing was used to allow communication between the cores on the FPGA. Two applications were mapped to the system: image edge detection and ECG. Compared to an Intel processor implementation of these applications, the FPGA based neural implementations provided about 3× and 127× speedup for the edge detection and ECG applications. Given that both applications were implemented with the same base Verilog code, with only a change in the synaptic weights and number of neurons utilized, the system has the capability to accelerate a broad range of applications. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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