DocumentCode
1913534
Title
The SDAV Software Frameworks for Visualization and Analysis on Next-Generation Multi-Core and Many-Core Architectures
Author
Sewell, Christopher ; Meredith, Jeremy ; Moreland, Kenneth ; Peterka, Tom ; DeMarle, Dave ; Li-Ta Lo ; Ahrens, James ; Maynard, Robert ; Geveci, B.
Author_Institution
Los Alamos Nat. Lab., Los Alamos, NM, USA
fYear
2012
fDate
10-16 Nov. 2012
Firstpage
206
Lastpage
214
Abstract
This paper surveys the four software frameworks being developed as part of the visualization pillar of the SDAV (Scalable Data Management, Analysis, and Visualization) Institute, one of the SciDAC (Scientific Discovery through Advanced Computing) Institutes established by the ASCR (Advanced Scientific Computing Research) Program of the U.S. Department of Energy. These frameworks include EAVL (Extreme-scale Analysis and Visualization Library), DAX (Data Analysis at Extreme), DIY (Do It Yourself), and PISTON. The objective of these frameworks is to facilitate the adaptation of visualization and analysis algorithms to take advantage of the available parallelism in emerging multi-core and many-core hardware architectures, in anticipation of the need for such algorithms to be run in-situ with LCF (leadership-class facilities) simulation codes on supercomputers.
Keywords
computer architecture; data visualisation; multiprocessing systems; DAX; DIY; EAVL; SDAV software frameworks; SciDAC; advanced scientific computing research; data analysis at extreme; do it yourself; extreme scale analysis and visualization library; next generation manycore architectures; next generation multicore architectures; scalable data management analysis and visualization; scientific discovery through advanced computing; visualization pillar; SDAV; data-parallel; in-situ; visualization; mult-core and many-core architectures; VTK-m;
fLanguage
English
Publisher
ieee
Conference_Titel
High Performance Computing, Networking, Storage and Analysis (SCC), 2012 SC Companion:
Conference_Location
Salt Lake City, UT
Print_ISBN
978-1-4673-6218-4
Type
conf
DOI
10.1109/SC.Companion.2012.36
Filename
6495818
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