By Topic

Extreme Scaling of Production Visualization Software on Diverse Architectures

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

8 Author(s)
Childs, H. ; Lawrence Berkeley National Laboratory, Berkeley ; Pugmire, D. ; Ahern, S. ; Whitlock, B.
more authors

We present the results of a series of experiments studying how visualization software scales to massive data sets. Although several paradigms exist for processing large data, we focus on pure parallelism,the dominant approach for production software. These experiments utilized multiple visualization algorithms and were run on multiple architectures. Two types of experiments were performed.For the first, we examined performance at massive scale:16,000 or more cores and one trillion or more cells. For the second, we studied weak scaling performance. These experiments were performed on the largest data set sizes published to date in visualization literature, and the findings on scaling characteristics and bottlenecks contribute to understanding of how pure parallelism will perform at high levels of concurrency and with very large data sets.

Published in:

Computer Graphics and Applications, IEEE  (Volume:PP ,  Issue: 99 )