EDBT 2026 Demo / reviewers in the wild / expert
Meta Sienkiewicz
dblp:351/3147
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1997
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1
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 · 67% Parallel and multicore computing · 33% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Environmental and earth informatics · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
High-performance computing › scientific computing
data assimilation |
0.0 | 1 | 1997 | Parallel Computing at the NASA Data Assimilation Office (DAO) · SC 1997 |
Parallel and multicore computing
parallel programming models |
0.0 | 1 | 1997 | Parallel Computing at the NASA Data Assimilation Office (DAO) · SC 1997 |
High-performance computing
scientific computing systems |
0.0 | 1 | 1997 | Parallel Computing at the NASA Data Assimilation Office (DAO) · SC 1997 |
Environmental and earth informatics
atmospheric modeling |
0.0 | 1 | 1997 | Parallel Computing at the NASA Data Assimilation Office (DAO) · SC 1997 |
Methods — techniques the papers use, named apart from their topics
multitasking · 0.0MPI · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1997 | Parallel Computing at the NASA Data Assimilation Office (DAO)abstractThis presentation discusses the NASA data assimilation project at the Data Assimilation Office at the NASA/Goddard Space Flight Center. The goal is to produce accurate gridded datasets of atmospheric fields by assimilating a range of observations along with physically consistent model forecasts. This work produces datasets that are used by the climate research community. The data come from conventional sources that are used for weather forecasts (e.g., radiosondes, earth-surface measurements, and satellite temperature retrievals), as well as new sources such as satellites that will be launched under the Mission To Planet Earth Enterprise. An end-to-end Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) currently supports stratospheric flight missions and reanalysis projects for NASA. The current Core of this system (Model, and Analysis) is a multitasking algorithm that runs on Cray J90 and C90 computers at Goddard and NASA Ames Research Center. Future Core computing will be carried out at Ames, with a new production system scheduled to be ready for the EOS AM-1 satellite launch in June of 1998. The DAO has acquired SGI Origin 2000 computers, with an aggregate of 160 processors in place at Ames, and more planned for the future. The DAO is currently updating the control scripts and programs, and implementing a modular Fortran 90 Core system. During 1998 the Core system will be migrated to distributed-memory software using the Message Passing Interface. Part of this work is being carried out under the NASA High Performance Computing and Communications Earth and Space Sciences program. The algorithmic and performance issues involved in Core system are the main subject of this presentation. M. P. Lyster, K. Ekers, M. Harber, D. Lamich, J. W. Larson, Robert Lucchesi, Richard B. Rood, S. Schubert, William B. Sawyer, Meta Sienkiewicz, Arlindo M. da Silva, J. Stobie, Lawrence Takacs, R. Todling, Jose Zero, Chris Ding, Robert D. Ferraro |
SC | 11 |