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Part of book or chapter of book . 2001
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Simulating distributed systems

descriptionPublicationkeyboard_double_arrow_right Article , Part of book or chapter of book 01 Jan 2001 United States Publisher:AIPJournal:AIP Conference Proceedings, volume 583, pages 164-166 (issn: 0094-243X, Copyright policy )
Authors: Newman, Harvey B.; Legrand, Iosif C.;

doi: 10.1063/1.1405293

Simulating distributed systems

Abstract

The simulation framework developed within the "Models of Networked Analysis at Regional Centers" (MONARC) project as a design and optimization tool for large scale distributed systems is presented. The goals are to provide a realistic simulation of distributed computing systems, customized for specific physics data processing tasks and to offer a flexible and dynamic environment to evaluate the performance of a range of possible distributed computing architectures. A detailed simulation of a large system, the CMS High Level Trigger (HLT) production farm, is also presented.

© 2001 American Institute of Physics. Issue Date: 20 August 2001. This work has been performed in collaboration with the MONARC project at CERN. We would like to thank David Stickland and Tony Wildish for the help in understanding the CMS production farm configuration and set-up.

<p>Published - <a href="/records/st3gk-wrt44/files/NEWaipcp01a.pdf?download=1">NEWaipcp01a.pdf</a></p>

Country
United States
Related Organizations
Keywords

large-scale systems, software architecture, software performance evaluation, discrete event simulation, distributed processing, multi-threading, 530

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green