High performance heterogeneous computing for collaborative visual analysis

Jianping Li, Jia Kai Chou, Kwan-Liu Ma

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

2 Scopus citations

Abstract

Visual analysis of large and complex data often requires multiple analysts with diverse expertise and different perspectives to collaborate in order to reveal hidden structures and gain insight in the data. While collaborative visualization allows multiple users to collectively work on the same analytic task, the user side computing devices can be used to share the computation workload for demanding data transformations and visualization calculations. In this paper, we present a heterogeneous computing framework for effective utilization of all the connected client devices to enhance the usability of online visualization applications.

Original languageEnglish (US)
Title of host publicationSIGGRAPH Asia 2015 Visualization in High Performance Computing, SA 2015
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450339292
DOIs
StatePublished - Nov 2 2015
EventSIGGRAPH Asia, SA 2015 - Kobe, Japan
Duration: Nov 2 2015Nov 6 2015

Other

OtherSIGGRAPH Asia, SA 2015
CountryJapan
CityKobe
Period11/2/1511/6/15

Keywords

  • Collaborative visualization
  • Heterogeneous computing
  • Information visualization
  • Parallel data transformation
  • Visual analytics

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

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  • Cite this

    Li, J., Chou, J. K., & Ma, K-L. (2015). High performance heterogeneous computing for collaborative visual analysis. In SIGGRAPH Asia 2015 Visualization in High Performance Computing, SA 2015 [12] Association for Computing Machinery, Inc. https://doi.org/10.1145/2818517.2818534