Exploiting idle cycles to execute data mining applications on clusters of PCs

  • Authors:
  • Hermes Senger;Eduardo R. Hruschka;Fabrício A. B. Silva;Liria M. Sato;Calebe P. Bianchini;Bruno F. Jerosch

  • Affiliations:
  • Universidade Católica de Santos (UniSantos), R. Dr. Carvalho de Mendonça 144, 11070-906 Santos, SP, Brazil;Universidade Católica de Santos (UniSantos), R. Dr. Carvalho de Mendonça 144, 11070-906 Santos, SP, Brazil;Universidade Católica de Santos (UniSantos), R. Dr. Carvalho de Mendonça 144, 11070-906 Santos, SP, Brazil;Escola Politécnica, Universidade de São Paulo Av. Prof. Luciano Gualberto, trav. 3, n. 180, 05508-900 São Paulo, SP, Brazil;Escola Politécnica, Universidade de São Paulo Av. Prof. Luciano Gualberto, trav. 3, n. 180, 05508-900 São Paulo, SP, Brazil;Universidade Católica de Santos (UniSantos), R. Dr. Carvalho de Mendonça 144, 11070-906 Santos, SP, Brazil

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2007

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Abstract

In this paper we present and evaluate Inhambu, a distributed object-oriented system that supports the execution of data mining applications on clusters of PCs and workstations. This system provides a resource management layer, built on the top of Java/RMI, that supports the execution of the data mining tool called Weka. We evaluate the performance of Inhambu by means of several experiments in homogeneous, heterogeneous and non-dedicated clusters. The obtained results are compared with those achieved by a similar system named Weka-Parallel. Inhambu outperforms its counterpart for coarse grain applications, mainly for heterogeneous and non-dedicated clusters. Also, our system provides additional advantages such as application checkpointing, support for dynamic aggregation of hosts to the cluster, automatic restarting of failed tasks, and a more effective usage of the cluster. Therefore, Inhambu is a promising tool for efficiently executing real-world data mining applications. The software is delivered at the project's web site available at http://incubadora.fapesp.br/projects/inhambu/.