Implementation and evaluation of self-organizing map algorithm on a graphic processor

Akihiro Shitara, Yuri Nishikawa, Masato Yoshimi, Hideharu Amano

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

In this paper, we introduce an implementation of algorithm for self-organizing maps(SOM) using GPUs and discuss its evaluation. We used CUDA provided by NVIDIA Corporation for parallel programming, profiling, and data flow optimization so as to exploit inherent data-level parallelism of the algorithm. By using three NVIDIA's graphic cards for evaluation, we investigated the relationships among the number of processor elements, amount of memory device and performance. As the result of performance evaluation with various parameter combinations, we found that implementation on GTX280 achieved 150 times higher performance of Intel Core 2 Quad 2.40 GHz when parameters of map size, dimension of vectors and learning size were 1372×1372, 128 and 128, respectively.

本文言語English
ホスト出版物のタイトルProceedings of the 21st IASTED International Conference on Parallel and Distributed Computing and Systems, PDCS 2009
ページ253-260
ページ数8
出版ステータスPublished - 2009 12 1
外部発表はい
イベント21st IASTED International Conference on Parallel and Distributed Computing and Systems, PDCS 2009 - Cambridge, MA, United States
継続期間: 2009 11 22009 11 4

出版物シリーズ

名前Proceedings of the IASTED International Conference on Parallel and Distributed Computing and Systems
ISSN(印刷版)1027-2658

Other

Other21st IASTED International Conference on Parallel and Distributed Computing and Systems, PDCS 2009
CountryUnited States
CityCambridge, MA
Period09/11/209/11/4

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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