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Paul E. Saylor

dblp:59/4710 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
High-performance computing
astrophysical simulation
0.011997
Scalable, Hydrodynamic and Radiation-Hydrodynamic Studies of Neutron Stars Mergers · SC 1997
Parallel and multicore computing
parallel computing
0.011997
Scalable, Hydrodynamic and Radiation-Hydrodynamic Studies of Neutron Stars Mergers · SC 1997
High-performance computing
scientific computing systems
0.011997
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
YearPublicationVenuePosition
1997 Scalable, Hydrodynamic and Radiation-Hydrodynamic Studies of Neutron Stars Mergers
abstract
We 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
SC1