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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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%.

Original languageEnglish
Title of host publicationProceedings of the 5th Symposium on Information and Communication Technology, SoICT 2014
PublisherAssociation for Computing Machinery
Pages256-262
Number of pages7
ISBN (Electronic)9781450329309
DOIs
Publication statusPublished - 2014 Dec 4
Event5th Symposium on Information and Communication Technology, SoICT 2014 - Hanoi, Viet Nam
Duration: 2014 Dec 42014 Dec 5

Publication series

NameACM International Conference Proceeding Series
Volume04-05-December-2014

Conference

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

Keywords

  • GPGPU
  • GPU
  • Many-core
  • Parallelization

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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    Kitsukawa, Y., Hirabayashi, M., Kato, S., & Edahiro, M. (2014). Exploring the problem of GPU programming for data-intensive applications: A case study of multiple expectation maximization for motif elicitation. In Proceedings of the 5th Symposium on Information and Communication Technology, SoICT 2014 (pp. 256-262). (ACM International Conference Proceeding Series; Vol. 04-05-December-2014). Association for Computing Machinery. https://doi.org/10.1145/2676585.2676616