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L. Ruby Leung

dblp:60/6077 · also Lai-yung Ruby Leung · DBLP profile ↗
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3ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-3221-9467ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 2Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Environmental and earth informatics · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
High-performance computing › scientific computing systems
climate modeling
0.712023
The Simple Cloud-Resolving E3SM Atmosphere Model Running on the Frontier Exascale System · SC 2023
High-performance computing › supercomputing
exascale computing
0.712023
The Simple Cloud-Resolving E3SM Atmosphere Model Running on the Frontier Exascale System · SC 2023
Environmental and earth informatics
atmospheric modeling
0.212023
The Simple Cloud-Resolving E3SM Atmosphere Model Running on the Frontier Exascale System · SC 2023
YearPublicationVenuePosition
2023 The Simple Cloud-Resolving E3SM Atmosphere Model Running on the Frontier Exascale System
Peter M. Caldwell, Luca Bertagna, Conrad Clevenger, Aaron Donahue, James G. Foucar, Oksana Guba, Benjamin R. Hillman, Noel Keen, Jayesh Krishna, Matthew R. Norman, Sarat Sreepathi, Christopher Terai, James B. White III, Andrew G. Salinger, Renata B. McCoy, L. Ruby Leung, David C. Bader, Danqing Wu
SC17
2002 New paradigms in problem solving environments for scientific computing
abstract
Computer and computational scientists at Pacific Northwest National Laboratory (PNNL) are studying and designing collaborative problem solving environments (CPSEs) for scientific computing in various domains. Where most scientific computing efforts focus at the level of the scientific codes, file systems, data archives, and networked computers, our analysis and design efforts are aimed at developing enabling technologies that are directly meaningful and relevant to domain scientist at the level of the practice and the science. We seek to characterize the nature of scientific problem solving and look for innovative ways to improve it. Moreover, we aim to glimpse beyond current systems and technical limitations to derive a design that expresses the scientist's own perspective on research activities, processes, and resources. The product of our analysis and design work is a conceptual scientific CPSE prototype that specifies a complete simulation and modeling user environment and a suite of high-level problem solving tools.
George Chin, L. Ruby Leung, Karen Schuchardt, Deborah K. Gracio
IUI2
2000 Vector fields simplification - a case study of visualizing climate modeling and simulation data sets
Pak Chung Wong, Harlan Foote, L. Ruby Leung, Elizabeth Jurrus, Dan Adams, James J. Thomas
IEEE Visualization3