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conference paper
Computational memory-based inference and training of deep neural networks
January 1, 2019
2019 Symposium On Vlsi Circuits
In-memory computing is an emerging computing paradigm where certain computational tasks are performed in place in a computational memory unit by exploiting the physical attributes of the memory devices, Here, we present an overview of the application of in-memory computing in deep learning, a branch of machine learning that has significantly contributed to the recent explosive growth in artificial intelligence. The methodology for both inference and training of deep neural networks is presented along with experimental results using phase-change memory (PCM) devices.
Use this identifier to reference this record
Type
conference paper
Web of Science ID
WOS:000531736500118
Authors
Sebastian, A.
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Dazzi, M.
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Giannopoulos, I.
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Jonnalagadda, V.
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Joshi, V.
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Karunaratne, G.
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Kersting, B.
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Khaddam-Aljameh, R.
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Nandakumar, S. R.
Publication date
2019-01-01
Publisher
Published in
2019 Symposium On Vlsi Circuits
ISBN of the book
978-4-86348-718-5
Publisher place
New York
Start page
T168
End page
T169
Peer reviewed
REVIEWED
EPFL units
Event name | Event place | Event date |
Kyoto, JAPAN | Jun 09-14, 2019 | |
Available on Infoscience
May 28, 2020