VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures

Kenneth Moreland, Christopher Sewell, William Usher, Li Ta Lo, Jeremy Meredith, David Pugmire, James Kress, Hendrik Schroots, Kwan-Liu Ma, Hank Childs, Matthew Larsen, Chun Ming Chen, Robert Maynard, Berk Geveci

Research output: Contribution to journalArticle

43 Scopus citations

Abstract

One of the most critical challenges for high-performance computing (HPC) scientific visualization is execution on massively threaded processors. Of the many fundamental changes we are seeing in HPC systems, one of the most profound is a reliance on new processor types optimized for execution bandwidth over latency hiding. Our current production scientific visualization software is not designed for these new types of architectures. To address this issue, the VTK-m framework serves as a container for algorithms, provides flexible data representation, and simplifies the design of visualization algorithms on new and future computer architecture.

Original languageEnglish (US)
Article number7466740
Pages (from-to)48-58
Number of pages11
JournalIEEE Computer Graphics and Applications
Volume36
Issue number3
DOIs
StatePublished - May 1 2016

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Keywords

  • algorithmic structures
  • computer graphics
  • high-performance computing
  • massively threaded processors
  • parallel algorithms
  • visualization software
  • VTK-m framework

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

Cite this

Moreland, K., Sewell, C., Usher, W., Lo, L. T., Meredith, J., Pugmire, D., Kress, J., Schroots, H., Ma, K-L., Childs, H., Larsen, M., Chen, C. M., Maynard, R., & Geveci, B. (2016). VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures. IEEE Computer Graphics and Applications, 36(3), 48-58. [7466740]. https://doi.org/10.1109/MCG.2016.48