An Adaptive Algorithm of K-means on HSA Platform

DOI

10.2991/cset-16.2016.33How to use a DOI?

Keywords

Heterogeneous computing, HSA, K-means, workload division

Abstract

With the growing demand for high performance computing, heterogeneous system, based on CPU-GPU architecture, were widely applied because of its higher processing capacity. To reduce the communication latency between CPUs and GPUs or other agents, HSA (Heterogeneous System Architecture) Foundation proposed a kind of an open industry standards body. In this paper, we designed the K-means algorithm on Kaveri APU, which complied with HSA standard, and optimized it into an adaptive one to obtain high utilization effect of both CPU and GPU. Experimental results show that our adaptive algorithm gets a 45.2% average decrease in overall execution time.

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/).

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TY  - CONF
AU  - Zhenshan Bao
AU  - Qi Luo
AU  - Wenbo Zhang
PY  - 2016/08
DA  - 2016/08
TI  - An Adaptive Algorithm of K-means on HSA Platform
BT  - Proceedings of the 2016 International Conference on Computer Science and Electronic Technology
PB  - Atlantis Press
SP  - 136
EP  - 139
SN  - 2352-538X
UR  - https://doi.org/10.2991/cset-16.2016.33
DO  - 10.2991/cset-16.2016.33
ID  - Bao2016/08
ER  -