A Fast and Low Power Hardware Accelerator for ANN Working at Near Threshold Voltage
Authors
Tianbao Chen, Shouyi Yin, Shaojun Wei
Corresponding Author
Tianbao Chen
Available Online April 2016.
- DOI
- 10.2991/ameii-16.2016.134How to use a DOI?
- Keywords
- ANN, Hardware accelerator, NTV
- Abstract
Arti cial neural network (ANN) are widely applied in machine learning and artificial intelligence. But ANN usually requires large data throughputs and induces high power consumptions. This paper proposes an accelerator design guideline for ANN with full consideration of the hardware scale, performance and power consumption. We apply multiple clocks in our design to get a high data throughput and introduce the near threshold voltage (NTV) to get a lower power consumption. We further optimize the multiplication operation in critical path obtaining a higher performance.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Tianbao Chen AU - Shouyi Yin AU - Shaojun Wei PY - 2016/04 DA - 2016/04 TI - A Fast and Low Power Hardware Accelerator for ANN Working at Near Threshold Voltage BT - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016) PB - Atlantis Press SP - 683 EP - 687 SN - 2352-5401 UR - https://doi.org/10.2991/ameii-16.2016.134 DO - 10.2991/ameii-16.2016.134 ID - Chen2016/04 ER -