A Scheduling Strategy of Naive Bayesian image classification on HSA Platform
Authors
Nan Xiao
Corresponding Author
Nan Xiao
Available Online May 2017.
- DOI
- 10.2991/icmeit-17.2017.122How to use a DOI?
- Keywords
- Heterogeneous computing; HSA; Naive Bayesian image classification; Scheduling Strategy
- Abstract
As the heterogeneous system based on CPU-GPU architecture has a strong performance advantages, so that it has been widely used in many fields especially image recognition, in order to enhance the transmission efficiency on HSA (Heterogeneous System Architecture) Platform. In this paper, we design a naive Bayesian image classification algorithm on the APU, which supports the HSA standard, and design a set of resource dynamic scheduling strategy for the eigenvalue extraction of the algorithm. The experimental results show that this strategy can save 29.56% execution time on average.
- Copyright
- © 2017, 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 - Nan Xiao PY - 2017/05 DA - 2017/05 TI - A Scheduling Strategy of Naive Bayesian image classification on HSA Platform BT - Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017) PB - Atlantis Press SP - 670 EP - 675 SN - 2352-538X UR - https://doi.org/10.2991/icmeit-17.2017.122 DO - 10.2991/icmeit-17.2017.122 ID - Xiao2017/05 ER -