DUAL: Acceleration of Clustering Algorithms using Digital-based Processing In-Memory

Today's applications generate a large amount of data that need to be processed by learning algorithms. In practice, the majority of the data are not associated with any labels. Unsupervised learning, i.e., clustering methods, are the most commonly used algorithms for data analysis. However, run...

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Bibliographic Details

Published in:	2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO) pp. 356 - 371
Main Authors:	Imani, Mohsen, Pampana, Saikishan, Gupta, Saransh, Zhou, Minxuan, Kim, Yeseong, Rosing, Tajana
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.10.2020
Subjects:	Algorithm-hardware co-design Hyperdimensional computing Processing in-memory Unsupervised learning
Online Access:	Get full text
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