Performance of Communication Patterns for Extreme-Scale Analysis and Visualization

TitlePerformance of Communication Patterns for Extreme-Scale Analysis and Visualization
Publication TypeConference Paper
Year of Publication2010
AuthorsPeterka, T, Kendall, W, Goodell, D, Nouanesengsy, B, Shen, H-W, Huang, J, Moreland, K, Thakur, R, Ross, RB
Conference NameSciDAC 2010
Date Published07/2010
PublisherJournal of Physics: Conference Series
Conference LocationChattanooga, TN
Other NumbersANL/MCS-P1774-0610
Abstract

Efficient data movement is essential for extreme-scale parallel visualization and analysis algorithms. In this research, we benchmark and optimize the performance of collective and point-to-point communication patterns for data-parallel visualization of scalar and vector data. Two such communication patterns are global reduction and local nearest-neighbor communication. We implement scalable algorithms at tens of thousands of processes, in some cases to the full scale of leadership computing facilities, and benchmark performance using large-scale scientific data.

PDFhttp://www.mcs.anl.gov/papers/P1774.pdf