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Proceedings Paper

On-chip phase-change photonic memory and computing
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Paper Abstract

The use of photonics in computing is a hot topic of interest, driven by the need for ever-increasing speed along with reduced power consumption. In existing computing architectures, photonic data storage would dramatically improve the performance by reducing latencies associated with electrical memories. At the same time, the rise of ‘big data’ and ‘deep learning’ is driving the quest for non-von Neumann and brain-inspired computing paradigms. To succeed in both aspects, we have demonstrated non-volatile multi-level photonic memory avoiding the von Neumann bottleneck in the existing computing paradigm and a photonic synapse resembling the biological synapses for brain-inspired computing using phase-change materials (Ge2Sb2Te5).

Paper Details

Date Published: 24 August 2017
PDF: 7 pages
Proc. SPIE 10345, Active Photonic Platforms IX, 1034519 (24 August 2017); doi: 10.1117/12.2272127
Show Author Affiliations
Zengguang Cheng, Univ. of Oxford (United Kingdom)
Carlos Ríos, Univ. of Oxford (United Kingdom)
Nathan Youngblood, Univ. of Oxford (United Kingdom)
C. David Wright, Univ. of Exeter (United Kingdom)
Wolfram H. P. Pernice, Univ. of Munster (Germany)
Harish Bhaskaran, Univ. of Oxford (United Kingdom)

Published in SPIE Proceedings Vol. 10345:
Active Photonic Platforms IX
Ganapathi S. Subramania; Stavroula Foteinopoulou, Editor(s)

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