Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications

Parallelization of Adaboost Algorithm on Intel MIC Architecture

Authors
Haibiao Luo, Haojie Yuan, Shendong Cheng, Ying Li, Feng Yuan, Mingzhu Wei
Corresponding Author
Haibiao Luo
Available Online January 2016.
DOI
10.2991/icaita-16.2016.61How to use a DOI?
Keywords
Intel MIC; adaboost; parallel computation
Abstract

The Adaboost algorithm plays important role in many machine learning applications. But the computation cost is real expensive when the candidate features are in large amount. In this paper, we introduce a parallel strategy of the Adaboost algorithm on Intel CPU+MIC system, where Intel MIC works as a coprocessor. Open MP directive was used to parallelize the program in both CPU and MIC. The paper achieved a speedup of 5.2 on CPU+MIC with respect to CPU alone.

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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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
Series
Advances in Intelligent Systems Research
Publication Date
January 2016
ISBN
10.2991/icaita-16.2016.61
ISSN
1951-6851
DOI
10.2991/icaita-16.2016.61How to use a DOI?
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  - Haibiao Luo
AU  - Haojie Yuan
AU  - Shendong Cheng
AU  - Ying Li
AU  - Feng Yuan
AU  - Mingzhu Wei
PY  - 2016/01
DA  - 2016/01
TI  - Parallelization of Adaboost Algorithm on Intel MIC Architecture
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
PB  - Atlantis Press
SP  - 248
EP  - 250
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-16.2016.61
DO  - 10.2991/icaita-16.2016.61
ID  - Luo2016/01
ER  -