Abstract
We discuss the architecture, implementation and testing of a neuromorphic Cellular Neural Network (CNN) processor for intelligent IoT devices. The processor is based on a simplicial piecewise linear CNN architecture that allows implementation of linear and nolinear CNNs. A linear array of 64 processing element (PE) with column-shared computation resources, tightly coupled to two data memory caches was synthesized and fabricated in a 55nm CMOS technology using custom layout libraries. The fabricated chip achieves an overall performance of 2.95 TOPS/W with dynamic energy dissipation efficiency of 86.4fJ per OP at V=500mV. The processor can implement different types of processing on 2D data arrays, such as gray-scale morphology, gradient flow, median filters, and approximate Gaussian filters, among others.
Originalsprache | Englisch |
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Titel | 2018 IEEE International Symposium on Circuits and Systems (ISCAS) |
Herausgeber (Verlag) | IEEE Computer Society |
Seiten | 1-4 |
Seitenumfang | 4 |
ISBN (Print) | 978-1-5386-4882-7 |
DOIs | |
Publikationsstatus | Veröffentlicht - 30 Mai 2018 |
Extern publiziert | Ja |
Veranstaltung | 2018 IEEE International Symposium on Circuits and Systems (ISCAS) - Florence, Italy Dauer: 27 Mai 2018 → 30 Mai 2018 |
Konferenz
Konferenz | 2018 IEEE International Symposium on Circuits and Systems (ISCAS) |
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Zeitraum | 27/05/18 → 30/05/18 |