DOE OSTI · 3384944
Viskores: Integrating Parallel Scientific Visualization Research into Applications
Abstract
Viskores is a scientific visualization library that is the primary deployment of such algorithms to the parallel accelerated processors of modern DOE supercomputers. In this paper, we review the capabilities provided by Viskores and how these capabilities are leveraged by other software in the high-performance computing ecosystem. We discuss the Viskores data representation and pay particular attention to array management. Through this array management we describe how data is adapted between Viskores and other software along with strategies for converting dynamic, polymorphic objects to static representations better suited to GPU processing. We conclude with several examples of Viskores integrating with high-performance software that is used in production today.
Keep this discovery
Explore connections, maps & timelines
Moreland, Ken [ORNL] (ORCID:0000000270513288), Amstutz, Jefferson [NVIDIA] (ORCID:0000000160023739), Athawale, Tushar [ORNL] (ORCID:0000000331636274), Bolea, Vicente [Kitware] (ORCID:000000025382093X), Bolstad, Mark [Sandia National Laboratories (SNL)], Childs, Hank [University of Oregon], Geveci, Berk [Kitware], Harrison, Cyrus [Lawrence Livermore National Laboratory (LLNL)], Larsen, Matthew [Luminary Cloud], Lo, Li-Ta [Los Alamos National Laboratory (LANL)], Marsaglia, Nichole [Lawrence Livermore National Laboratory (LLNL)] (ORCID:0000000296304388), Mathai, Manish [ORNL], Pugmire, Dave [ORNL] (ORCID:0000000306472634), Rizzi, Silvio [Argonne National Laboratory (ANL)], Tsalikis, Spiros [Kitware] (ORCID:0000000151137195), Weber, Gunther [Lawrence Berkeley National Laboratory (LBNL)]. 2026-06-01. Viskores: Integrating Parallel Scientific Visualization Research into Applications. https://doi.org/10.2312/visgap.20261000
Cite the original work for its findings. Save a collection to share your selection of sources.