A domain-specific architecture for deep neural networks-Reference-Cited by-同舟云学术

A domain-specific architecture for deep neural networks

Published:2018-08-22 Issue:9 Volume:61 Page:50-59
ISSN:0001-0782
Container-title:Communications of the ACM
language:en
Short-container-title:Commun. ACM

Author:

Jouppi Norman P.¹,Young Cliff¹,Patil Nishant¹,Patterson David²

Affiliation:

1. Google, Mountain View, CA

2. University of California at Berkeley, Berkeley, CA and Google, Mountain View, CA

Abstract

Tensor processing units improve performance per watt of neural networks in Google datacenters by roughly 50x.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Link

https://dl.acm.org/doi/pdf/10.1145/3154484

Reference38 articles.

1. Abadi M. et al. Tensorflow: Large-scale machine learning on heterogeneous distributed systems. arXiv preprint 2016; https://arxiv.org/abs/1603.04467 Abadi M. et al. Tensorflow: Large-scale machine learning on heterogeneous distributed systems. arXiv preprint 2016; https://arxiv.org/abs/1603.04467

2. Cnvlutin: Ineffectual-Neuron-Free Deep Neural Network Computing

3. The Case for Energy-Proportional Computing

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