Implementing a Timing Error-Resilient and Energy-Efficient Near-Threshold Hardware Accelerator for Deep Neural Network Inference

Implementing a Timing Error-Resilient and Energy-Efficient Near-Threshold Hardware Accelerator for Deep Neural Network Inference

Increasing processing requirements in the Artificial Intelligence (AI) realm has led to the emergence of domain-specific architectures for Deep Neural Network (DNN) applications. Tensor Processing Unit (TPU), a DNN accelerator by Google, has emerged as a front runner outclassing its contemporaries,...

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Bibliographic Details
Main Authors: Noel Daniel Gundi, Pramesh Pandey, Sanghamitra Roy, Koushik Chakraborty
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Journal of Low Power Electronics and Applications
Subjects:
near-threshold computing
NTC
deep neural network
DNN
accelerators
timing error
Online Access:https://www.mdpi.com/2079-9268/12/2/32

Internet

https://www.mdpi.com/2079-9268/12/2/32

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