A. M. Baker

dblp:29/1079 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
0since 2021 · last 1994
—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 · 75% Performance modeling and evaluation · 25%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
High-performance computing › scientific computing systems
computational fluid dynamics
0.011994
A fixed time performance evaluation of parallel CFD applications · SC 1994
Performance modeling and evaluation
parallel performance evaluation
0.011994
A fixed time performance evaluation of parallel CFD applications · SC 1994
High-performance computing
performance optimization at scale
0.011994
A fixed time performance evaluation of parallel CFD applications · SC 1994
High-performance computing
scientific computing systems
0.011994
A fixed time performance evaluation of parallel CFD applications · SC 1994

Methods — techniques the papers use, named apart from their topics

fixed time measurement · 0.0
YearPublicationVenuePosition
1994 A fixed time performance evaluation of parallel CFD applications
abstract
The inviscid gas dynamics equations have been solved on the nCUBE 2s computer to better understand the challenges and opportunities that parallel processing presents. Two basic computational fluid dynamics (CFD) application problems representing different flow physics are used as test cases: supersonic internal flow and subsonic flow over an airfoil. Analysis of the parallel performance for these applications is presented following a fixed time measurement approach. Results from this study demonstrate that even though these flow simulation problems are communication-intensive, they are scalable. Parallel computing is shown to be an effective tool for future CFD challenges.>
A. M. Baker, S. X. Ying
SC1