A classification of scientific visualization algorithms for massive threading

Kenneth Moreland, Berk Geveci, Kwan-Liu Ma, Robert Maynard

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

3 Scopus citations

Abstract

As the number of cores in processors increase and accelerator architectures are becoming more common, an ever greater number of threads is required to achieve full processor utilization. Our current parallel scientific visualization codes rely on partitioning data to achieve parallel processing, but this approach will not scale as we approach massive threading in which work is distributed in such a fine level that each thread is responsible for a minute portion of data. In this paper we characterize the challenges of refactoring our current visualization algorithms by considering the finest portion of work each performs and examining the domain of input data, overlaps of output domains, and interdepen-dencies among work instances. We divide our visualization algorithms into eight categories, each containing algorithms with the same interdependencies. By focusing our research efforts to solving these categorial challenges rather than this legion of individual algorithms, we can make attainable advancement for extreme computing.

Original languageEnglish (US)
Title of host publicationProc. of UltraVis 2013
Subtitle of host publication8th Int. Workshop on Ultrascale Visualization - Held in Conjunction with SC 2013: The Int. Conference for High Performance Computing, Networking, Storage and Analysis
DOIs
StatePublished - Dec 1 2013
Event8th International Workshop on Ultrascale Visualization, UltraVis 2013 - Held in Conjunction with the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2013 - Denver, CO, United States
Duration: Nov 17 2013Nov 17 2013

Other

Other8th International Workshop on Ultrascale Visualization, UltraVis 2013 - Held in Conjunction with the International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2013
CountryUnited States
CityDenver, CO
Period11/17/1311/17/13

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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    Moreland, K., Geveci, B., Ma, K-L., & Maynard, R. (2013). A classification of scientific visualization algorithms for massive threading. In Proc. of UltraVis 2013: 8th Int. Workshop on Ultrascale Visualization - Held in Conjunction with SC 2013: The Int. Conference for High Performance Computing, Networking, Storage and Analysis [2] https://doi.org/10.1145/2535571.2535591