Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.

Steven Docy

dblp:56/3394 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 1999
—ORCID · none

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
Performance modeling and evaluation · 100%

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

TopicWeightPapersLastEvidence papers
Performance modeling and evaluation › simulation › architectural simulation
execution-driven simulation
0.011999
Performance Prediction of Large Parallel Applications using Parallel Simulations · PPoPP 1999
Performance modeling and evaluation › simulation › parallel and distributed simulation
parallel simulation
0.011999
Performance Prediction of Large Parallel Applications using Parallel Simulations · PPoPP 1999
Performance modeling and evaluation
performance prediction
0.011999
Performance Prediction of Large Parallel Applications using Parallel Simulations · PPoPP 1999
Performance modeling and evaluation › simulation › discrete-event simulation
parallel discrete event simulation
0.011999
Performance Prediction of Large Parallel Applications using Parallel Simulations · PPoPP 1999

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

parallel discrete-event simulation · 0.0direct execution · 0.0
YearPublicationVenuePosition
1999 Performance Prediction of Large Parallel Applications using Parallel Simulations
abstract
Accurate simulation of large parallel applications can be facilitated with the use of direct execution and parallel discrete event simulation. This paper describes the use of COMPASS, a direct execution-driven, parallel simulator for performance prediction of programs that include both communication and I/O intensive applications. The simulator has been used to predict the performance of such applications on both distributed memory machines like the IBM SP and shared-memory machines like the SGI Origin 2000. The paper illustrates the usefulness of COMPASS as a versatile performance prediction tool. We use both real-world applications and synthetic benchmarks to study application scalability, sensitivity to communication latency, and the interplay between factors like communication pattern and parallel file system caching on application performance. We also show that the simulator is accurate in its predictions and that it is also efficient in its ability to use parallel simulation to reduce its own execution time which, in some cases, has yielded a nearlinear speedup.
Rajive L. Bagrodia, Ewa Deelman, Steven Docy, Thomas Phan
PPoPP3