Demo Data from EDBT 2026 / reviewers in the wild / expert
Paul E. Saylor
dblp:59/4710
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1997
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 first-author
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 |
Computational science and engineering · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
High-performance computing
astrophysical simulation |
0.0 | 1 | 1997 | Scalable, Hydrodynamic and Radiation-Hydrodynamic Studies of Neutron Stars Mergers · SC 1997 |
Parallel and multicore computing
parallel computing |
0.0 | 1 | 1997 | Scalable, Hydrodynamic and Radiation-Hydrodynamic Studies of Neutron Stars Mergers · SC 1997 |
High-performance computing
scientific computing systems |
0.0 | 1 | 1997 | Scalable, Hydrodynamic and Radiation-Hydrodynamic Studies of Neutron Stars Mergers · SC 1997 |
Methods — techniques the papers use, named apart from their topics
radiation transport · 0.0hydrodynamic simulation · 0.0gravitational field equations · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1997 | Scalable, Hydrodynamic and Radiation-Hydrodynamic Studies of Neutron Stars MergersabstractWe discuss the high performance computing issues involved in the numerical simulation of binary neutron star mergers and supernovae. These phenomena, which are of great interest to astronomers and physicists, can only be described by modeling the gravitational field of the objects along with the flow of matter and radiation in a self consistent manner. In turn, such models require the solution of the gravitational field equations, Eulerian hydrodynamic equations, and radiation transport equations. This necessitates the use of scalable, high performance computing assets to conduct the simulations. We discuss some of the parallel computing aspects of this challenging task in this paper. Paul E. Saylor, F. Douglas Swesty |
SC | 1 |