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Priyamvada Sinvhal-Sharma

dblp:80/1559 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1990
—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
Embedded and real-time systems · 38% Performance modeling and evaluation · 38% Processor architecture and microarchitecture · 12%

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

TopicWeightPapersLastEvidence papers
Performance modeling and evaluation › performance monitoring
parallel program monitoring		 0.011990
Run-time monitoring of concurrent programs on the Cedar multiprocessor · SC 1990
Embedded and real-time systems
runtime monitoring		 0.011990
Run-time monitoring of concurrent programs on the Cedar multiprocessor · SC 1990
Processor architecture and microarchitecture
multicore design		 0.011990
Run-time monitoring of concurrent programs on the Cedar multiprocessor · SC 1990
Parallel and multicore computing
multiprocessor system		 0.011990
Run-time monitoring of concurrent programs on the Cedar multiprocessor · SC 1990

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

runtime tracing · 0.0distributed communication · 0.0
YearPublicationVenuePosition
1990 Run-time monitoring of concurrent programs on the Cedar multiprocessor
abstract
A prototype run-time performance monitoring environment for the Cedar multiprocessor has been developed. The authors describe how the Cedar performance monitoring infrastructure is designed to achieve run-time monitoring and distributed communication of parallel program execution data. The underlying tracing procedures used in Cedar to gather execution data are described, and the procedures by which traces are dynamically off-loaded from the Cedar system and sent to remote processes are explained. The application of these tools to capture and visualize matrix data from an application at run-time is discussed. Finally, results regarding the performance of the run-time monitoring system in in terms of execution data bandwidth and program perturbation are presented.>
Allen D. Malony, Michael W. Berry, Priyamvada Sinvhal-Sharma
 SC4