Extreme scaling of production visualization software on diverse architectures

Hank Childs; David Pugmire; Sean Ahern; Brad Whitlock; Mark Howison; Gunther H Weber; E Wes Bethel

doi:10.1109/MCG.2010.51

Extreme scaling of production visualization software on diverse architectures

IEEE Comput Graph Appl. 2010 May-Jun;30(3):22-31. doi: 10.1109/MCG.2010.51.

Authors

Hank Childs¹, David Pugmire, Sean Ahern, Brad Whitlock, Mark Howison, Gunther H Weber, E Wes Bethel

Affiliation

¹ Lawrence Berkeley National Laboratory, and University of California at Davis, CA, USA. hchilds@lbl.gov

PMID: 20650715
DOI: 10.1109/MCG.2010.51

Abstract

This article presents the results of experiments studying how the pure-parallelism paradigm scales to massive data sets, including 16,000 or more cores on trillion-cell meshes, the largest data sets published to date in the visualization literature. The findings on scaling characteristics and bottlenecks contribute to understanding how pure parallelism will perform in the future.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.