PCM Enabled Low-Power Photonic Accelerator for Inference and Training on Edge Devices-Reference-Cited by-同舟云学术

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PCM Enabled Low-Power Photonic Accelerator for Inference and Training on Edge Devices

Published:2024-05-27 Issue: Volume:31 Page:600-607
ISSN:
Container-title:2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
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Author:

Curry Juliana¹,Louri Ahmed¹,Karanth Avinash²,Bunescu Razvan³

Affiliation:

1. The George Washington University,Dept. of Electrical and Computer Engineering,Washington,D.C.

2. School of Electrical Engineering and Computer Science, Ohio University,Athens,Ohio

3. University of North Carolina at Charlotte,Dept. of Computer Science,Charlotte,North Carolina

Funder

NSF

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10596331/10596332/10596448.pdf?arnumber=10596448

Reference37 articles.

1. Snowflakes at the Edge

2. Digital Electronics and Analog Photonics for Convolutional Neural Networks (DEAP-CNNs)

3. Design of CMOS Based D Flip-Flop with Different Low Power Techniques

4. Silicon microring resonators

5. Neuromorphic Photonic Memory Devices Using Ultrafast, Non‐Volatile Phase‐Change Materials

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