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

Authors:
Elias N. Houstis;Vassilios S. Verykios;Ann C. Catlin;John R. Rice
Affiliations:
Dept. of Computer and Commun. Engr., Univ. of Thessaly, Volos, Greece and Dept. of Computer Sciences, Purdue University, West Lafayette, IN;Dept. of Computer and Commun. Engr., Univ. of Thessaly, Volos, Greece and Research and Academic Computer Technology Institute, Patras, Greece;Dept. of Computer Sciences, Purdue University, West Lafayette, IN;Dept. of Computer Sciences, Purdue University, West Lafayette, IN
Venue:
ICCS'03 Proceedings of the 2003 international conference on Computational science
Year:
2003

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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.