Evaluating Performance, Power and Energy of Deep Neural Networks on CPUs and GPUs-Reference-Cited by-同舟云学术

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Evaluating Performance, Power and Energy of Deep Neural Networks on CPUs and GPUs

Published:2021 Issue: Volume: Page:196-221
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
Short-container-title:

Author:

Sun Yuyang,Ou Zhixin,Chen Juan,Qi Xinxin,Guo Yifei,Cai Shunzhe,Yan Xiaoming

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-7443-3_12

Reference30 articles.

1. Convnet. https://github.com/soumith/convnet-benchmarks

2. cxxnet. https://github.com/dmlc/cxxnet

3. Imagenet large-scale visual recognition challenge. http://image-net.org/challenges/LSVRC

4. Nvidia system management interface. https://developer.nvidia.com/nvidia-system-management-interface

5. Abadi, M., et al.: TensorFlow: large-scale machine learning on heterogeneous distributed systems. ArXiv abs/1603.04467 (2016)

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