TY - GEN
T1 - The SDAV Software frameworks for visualization and analysis on next-generation multi-core and many-core Architectures
AU - Sewell, Christopher
AU - Meredith, Jeremy
AU - Moreland, Kenneth
AU - Peterka, Tom
AU - Demarle, Dave
AU - Lo, Li Ta
AU - Ahrens, James
AU - Maynard, Robert
AU - Geveci, Berk
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - SDAV; data-parallel; in-situ; visualization; mult-core and many-core architectures; VTK-m
UR - http://www.scopus.com/inward/record.url?scp=84876585285&partnerID=8YFLogxK
U2 - 10.1109/SC.Companion.2012.36
DO - 10.1109/SC.Companion.2012.36
M3 - Conference contribution
AN - SCOPUS:84876585285
SN - 9780769549569
T3 - Proceedings - 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012
SP - 206
EP - 214
BT - Proceedings - 2012 SC Companion
T2 - 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012
Y2 - 10 November 2012 through 16 November 2012
ER -