HPC-ICTM: the interval categorizer tessellation-based model for high performance computing

Authors:
Marilton S. de Aguiar;Graçaliz P. Dimuro;Fábia A. Costa;Rafael K. S. Silva;César A. F. De Rose;Antônio C. R. Costa;Vladik Kreinovich
Affiliations:
Escola de Informática, Universidade Católica de Pelotas, Pelotas, Brazil;Escola de Informática, Universidade Católica de Pelotas, Pelotas, Brazil;Escola de Informática, Universidade Católica de Pelotas, Pelotas, Brazil;PPGCC, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil;PPGCC, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil;,Escola de Informática, Universidade Católica de Pelotas, Pelotas, Brazil;Department of Computer Science, University of Texas at El Paso, El Paso, TX
Venue:
PARA'04 Proceedings of the 7th international conference on Applied Parallel Computing: state of the Art in Scientific Computing
Year:
2004

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Abstract

This paper presents the Interval Categorizer Tessellation-based Model (ICTM) for the simultaneous categorization of geographic regions considering several characteristics (e.g., relief, vegetation, land use etc.). Interval techniques are used for the modelling of uncertain data and the control of discretization errors. HPC-ICTM is an implementation of the model for clusters. We analyze the performance of the HPC-ICTM and present results concerning its application to the relief/land-use categorization of the region surrounding the lagoon Lagoa Pequena (RS, Brazil), which is extremely important from an ecological point of view.