Publications

Moreland, Kenneth D.

Abstract not provided.

Moreland, Kenneth D.

Abstract not provided.

Moreland, Kenneth D.

Abstract not provided.

Moreland, Kenneth D.

Abstract not provided.

Moreland, Kenneth D.

Abstract not provided.

Moreland, Kenneth D.; Geveci, Berk G.; Pugmire, David P.; Rogers, David M.; Ma, Kwan-Liu M.; Childs, Hank C.

Abstract not provided.

Moreland, Kenneth D.; Geveci, Berk G.; Pugmire, David P.; Rogers, David M.; Ma, Kwan-Liu M.; Childs, Hank C.

Abstract not provided.

Moreland, Kenneth D.; Geveci, Berk G.; Meredith, Jeremy M.; Sewell, Chris S.; Ma, Kwan-Liu M.; Childs, Hank C.

Abstract not provided.

Moreland, Kenneth D.; Pugmire, David P.; Rogers, David M.; Childs, Hank C.; Ma, Kwan-Liu M.; Geveci, Berk G.

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

Moreland, Kenneth D.; Sewell, Christopher S.; Childs, Hank C.; Ma, Kwan-Liu M.; Geveci, Berk G.; Meredith, Jeremy M.

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

Moreland, Kenneth D.; Sewell, Christopher S.; Childs, Hank C.; Ma, Kwan-Liu M.; Geveci, Berk G.; Pugmire, David P.

Abstract not provided.

Moreland, Kenneth D.; Pugmire, David P.; Rogers, David M.; Childs, Hank C.; Ma, Kwan-Liu M.; Geveci, Berk G.

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.

Moreland, Kenneth D.; Sewell, Christopher S.; Childs, Hank C.; Ma, Kwan-Liu M.; Geveci, Berk G.; Meredith, Jeremy M.

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. This project provides the necessary research and infrastructure for scientific discovery in this new computational ecosystem by addressing four interlocking challenges: emerging processor technology, in situ integration, usability, and proxy analysis.