A knowledge discovery methodology for behavior analysis of large-scale applications on parallel architectures

dc.creator	Houstis, E. N.	en
dc.creator	Verkios, V. S.	en
dc.creator	Catlin, A. C.	en
dc.creator	Rice, J. R.	en
dc.date.accessioned	2015-11-23T10:30:11Z
dc.date.available	2015-11-23T10:30:11Z
dc.date.issued	2003
dc.identifier.isbn	3-540-40197-0
dc.identifier.issn	0302-9743
dc.identifier.uri	http://hdl.handle.net/11615/28513
dc.description.abstract	The focus of this paper is the application and extension of the knowledge discovery in databases process [5] developed in PYTHIA recommender system, to analyze the behavior of a DOE ASCI application/hardware pairs in the context of POEMS project[4]. The POEMS project has built a library of models for modeling scalable architectures like those in the ASCI program. Moreover, it supports detail simulation of a variety of state-of-the-art processors and memory hierarchies and incorporates parallel evaluation of discrete-event simulation. The driver application used is SWEEP3D.	en
dc.source	Computational Science - Iccs 2003, Pt Iv, Proceedings	en
dc.source.uri	<Go to ISI>://WOS:000184832100076
dc.subject	recommender system	en
dc.subject	data mining	en
dc.subject	knowledge discovery	en
dc.subject	scientific	en
dc.subject	computing	en
dc.subject	SYSTEM	en
dc.subject	PYTHIA	en
dc.subject	Computer Science, Interdisciplinary Applications	en
dc.subject	Computer Science,	en
dc.subject	Software Engineering	en
dc.subject	Computer Science, Theory & Methods	en
dc.title	A knowledge discovery methodology for behavior analysis of large-scale applications on parallel architectures	en
dc.type	bookChapter	en

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