CHaNAS: coordinated search for network architecture and scheduling policy-Reference-Cited by-同舟云学术

CHaNAS: coordinated search for network architecture and scheduling policy

Published:2021-06-22 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 22nd ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems
language:
Short-container-title:

Author:

Chen Weiwei¹,Wang Ying²,Lin Gangliang³,Gao Chengsi¹,Liu Cheng²,Zhang Lei²

Affiliation:

1. Institute of Computing Technology at Chinese Academy of Sciences, China / University of Chinese Academy of Sciences, China

2. Institute of Computing Technology at Chinese Academy of Sciences, China

3. University of Chinese Academy of Sciences, China

Funder

National Natural Science Foundation of China

2025 Key Technology Innovation Program of Ningbo City

Strategic Priority Research Program of Chinese Academy of Science,

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3461648.3463846

Reference51 articles.

1. 2020. Google(R) XLA. https://www.tensorflow.org/xla 2020. Google(R) XLA. https://www.tensorflow.org/xla

2. 2020. Inter(R) MKL-DNN. https://github.com/intel/mkl-dnn 2020. Inter(R) MKL-DNN. https://github.com/intel/mkl-dnn

3. 2020. NVIDIA(R) CUBLAS Library. https://www.nvidia.com/ 2020. NVIDIA(R) CUBLAS Library. https://www.nvidia.com/

4. Martín Abadi Paul Barham Jianmin Chen Zhifeng Chen Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Geoffrey Irving and Michael Isard. 2017. Tensorflow: A system for large-scale machine learning. In 12th $USENIX$ Symposium on Operating Systems Design and Implementation ($OSDI$ 17). 265–283. https://www.usenix.org/conference/osdi16/technical-sessions/presentation/abadi Martín Abadi Paul Barham Jianmin Chen Zhifeng Chen Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Geoffrey Irving and Michael Isard. 2017. Tensorflow: A system for large-scale machine learning. In 12th $USENIX$ Symposium on Operating Systems Design and Implementation ($OSDI$ 17). 265–283. https://www.usenix.org/conference/osdi16/technical-sessions/presentation/abadi

5. Best of Both Worlds: AutoML Codesign of a CNN and its Hardware Accelerator