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Users Matter: A Multi-agent Systems Model of High Performance Computing Cluster Users

  • Michael J. North
  • Cynthia S. Hood
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3415)

Abstract

High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex due to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.

Keywords

Unify Modeling Language High Performance Computing Cluster Performance Manual Trace User Matter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Michael J. North
    • 1
  • Cynthia S. Hood
    • 2
  1. 1.Argonne National LaboratoryArgonne
  2. 2.Illinois Institute of TechnologyChicagoUSA

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