Exploring the problem of GPU programming for data-intensive applications: A case study of multiple expectation maximization for motif elicitation

Yuki Kitsukawa, Manato Hirabayashi, Shinpei Kato, Masato Edahiro

研究成果: Conference contribution

抄録

Recently General-Purpose Computing on Graphics Processing Units (GPGPU) has been used to reduce the processing time of various applications, but the degree of acceleration by the Graphical Processing Unit (GPU) depends on the application. This study focuses on data analysis as an application example of GPGPU, specifically, the design and implementation of GPGPU computation libraries for data-intensive workloads. The effects of efficient memory allocation and high-speed read-only memories on the execution time are evaluated. In addition to employing a single GPU, the scalability using multiple GPUs is also evaluated. Compared to a Central Processing Unit (CPU) alone, the memory allocation method reduces the execution time for memory copies by approximately 60% when a GPU is used, while utilizing read-only memories results in an approximately 20% reduction in the overall program execution time. Moreover, expanding the number of GPUs from one to four reduces the execution time by approximately 10%.

本文言語English
ホスト出版物のタイトルProceedings of the 5th Symposium on Information and Communication Technology, SoICT 2014
出版社Association for Computing Machinery
ページ256-262
ページ数7
ISBN(電子版)9781450329309
DOI
出版ステータスPublished - 2014 12月 4
イベント5th Symposium on Information and Communication Technology, SoICT 2014 - Hanoi, Viet Nam
継続期間: 2014 12月 42014 12月 5

出版物シリーズ

名前ACM International Conference Proceeding Series
04-05-December-2014

Conference

Conference5th Symposium on Information and Communication Technology, SoICT 2014
国/地域Viet Nam
CityHanoi
Period14/12/414/12/5

ASJC Scopus subject areas

  • ソフトウェア
  • 人間とコンピュータの相互作用
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ ネットワークおよび通信

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