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VTK-m Users' Guide (Version 0.0)

Moreland, Kenneth D.

VTK-m is written in C++ and makes extensive use of templates. The toolkit is implemented as a header library, meaning that all the code is implemented in header files (with extension .h) and completely included in any code that uses it. This is typically necessary of template libraries, which need to be compiled with template parameters that are not known until they are used. This also provides the convenience of allowing the compiler to inline user code for better performance.

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TYPE Other Report YEAR 2015
DOIOSTI

XVis: Visualization for the Extreme-Scale Scientific-Computation Ecosystem (Mid-year report FY15 Q2)

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

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.

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TYPE Other Report YEAR 2015
DOIOSTI

Formal metrics for large-scale parallel performance

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Moreland, Kenneth D.; Oldfield, Ron

Performance measurement of parallel algorithms is well studied and well understood. However, a flaw in traditional performance metrics is that they rely on comparisons to serial performance with the same input. This comparison is convenient for theoretical complexity analysis but impossible to perform in large-scale empirical studies with data sizes far too large to run on a single serial computer. Consequently, scaling studies currently rely on ad hoc methods that, although effective, have no grounded mathematical models. In this position paper we advocate using a rate-based model that has a concrete meaning relative to speedup and efficiency and that can be used to unify strong and weak scaling studies.

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TYPE Conference Poster YEAR 2015
OSTIScopus
Results 126–150 of 329
Results 126–150 of 329