Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Sudhanshu Sane"'
Visualization and analysis of multivariate data and their uncertainty are top research challenges in data visualization. Constructing fiber surfaces is a popular technique for multivariate data visualization that generalizes the idea of level-set vis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da1b0d6772caabff7651ea9893d1b47a
http://arxiv.org/abs/2207.11318
http://arxiv.org/abs/2207.11318
Autor:
Sudhanshu Sane, Hank Childs
Publikováno v:
Mathematics and Visualization ISBN: 9783030816261
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b32d5d9aa0bba4869a8bdb3bcd14576
https://doi.org/10.1007/978-3-030-81627-8_5
https://doi.org/10.1007/978-3-030-81627-8_5
Publikováno v:
2021 IEEE Visualization Conference (VIS).
Marching squares (MS) and marching cubes (MC) are widely used algorithms for level-set visualization of scientific data. In this paper, we address the challenge of uncertainty visualization of the topology cases of the MS and MC algorithms for uncert
Autor:
Matthew Larsen, Cyrus Harrison, Terece L. Turton, Sudhanshu Sane, Stephanie Brink, Hank Childs
Publikováno v:
2021 IEEE 11th Symposium on Large Data Analysis and Visualization (LDAV).
Publikováno v:
e-Energy
The efficiency of solar panels depends on the operating temperature. As the panel temperature rises, efficiency drops. Thus, the solar energy community aims to understand the factors that influence the operating temperature, which include wind speed,
Publikováno v:
Journal of Computational Science. 61:101615
Publikováno v:
Computational Science – ICCS 2021 ISBN: 9783030779603
ICCS (1)
ICCS (1)
Although many types of computational simulations produce time-varying vector fields, subsequent analysis is often limited to single time slices due to excessive costs. Fortunately, a new approach using a Lagrangian representation can enable time-vary
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe050c54b2ea87462610eadc3df39b4f
https://doi.org/10.1007/978-3-030-77961-0_36
https://doi.org/10.1007/978-3-030-77961-0_36
Autor:
Aaron Knoll, Paul A. Navrátil, Steve Petruzza, Venkatram Vishwanath, Michel Rasquin, Silvio Rizzi, Jeremy S. Meredith, Thomas Fogal, Jay Lofstead, Bernd Hentschel, David Rogers, James Kress, Han-Wei Shen, Franz Sauer, Cyrus Harrison, Tom Peterka, David Pugmire, Sudhanshu Sane, Charles Hansen, Kenneth Moreland, Berk Geveci, Matthew Wolf, Kwan-Liu Ma, Janine C. Bennett, Rhonda Vickery, William F. Godoy, Sean B. Ziegeler, Ingo Wald, Eric Brugger, Christoph Garth, Steffen Frey, Joseph A. Insley, Jean M. Favre, Andrew Bauer, Soumya Dutta, Gunther H. Weber, Sean Ahern, Matthieu Dorier, Ruonan Wang, John Patchett, E. Wes Bethel, Chris R. Johnson, Valerio Pascucci, Patrick O'Leary, Preeti Malakar, Norbert Podhorszki, Hongfeng Yu, Brad Whitlock, Matthew Larsen, James Ahrens, Robert Sisneros, Joseph A. Cottam, Scott Klasky, Manish Parashar, Hank Childs, Peer-Timo Bremer, Will Usher
Publikováno v:
The International Journal of High Performance Computing Applications, vol 34, iss 6
International Journal of High Performance Computing Applications, vol 34, iss 6
International Journal of High Performance Computing Applications, vol 34, iss 6
The term “in situ processing” has evolved over the last decade to mean both a specific strategy for visualizing and analyzing data and an umbrella term for a processing paradigm. The resulting confusion makes it difficult for visualization and an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::070afd116d2dcb779f32cf9347bf71ee
https://escholarship.org/uc/item/20q1s49z
https://escholarship.org/uc/item/20q1s49z
Large scale parallel applications have evolved beyond the tipping point where there are compelling reasons to analyze, visualize and otherwise process output data from scientific simulations in situ rather than writing data to filesystems for post-pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::043326d8bb5694f0d21200ba6bcb93a3
https://doi.org/10.3233/apc200080
https://doi.org/10.3233/apc200080
Publikováno v:
IEEE Transactions on Computers. 65:353-366
To improve the reliability of on-chip network based systems, we design a deadlock-free routing technique that is more resilient to component failures and guarantees a higher degree of node connectivity. The routing methodology consists of three key s