Approximate Computing and the Efficient Machine Learning Expedition

Approximate computing (AxC) has been long accepted as a design alternative for efficient system implementation at the cost of relaxed accuracy requirements. Despite the AxC research activities in various application domains, AxC thrived the past decade when it was applied in Machine Learning (ML). T...

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Bibliographic Details

Published in:	2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD) pp. 1 - 9
Main Authors:	Henkel, Jorg, Li, Hai, Raghunathan, Anand, Tahoori, Mehdi B., Venkataramani, Swagath, Yang, Xiaoxuan, Zervakis, Georgios
Format:	Conference Proceeding
Language:	English
Published:	ACM 29.10.2022
Subjects:	Approximate computing Computational modeling Costs Design automation In-memory Machine learning Precision Scaling Printed Electronics Prototypes Pruning Quantization Taxonomy Transformers
ISSN:	1558-2434
Online Access:	Get full text
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