Performance Prediction for Parallel Iterative Solvers

Authors:
V. Blanco;P. González;J. C. Cabaleiro;D. B. Heras;T. F. Pena;J. J. Pombo;F. F. Rivera
Affiliations:
Department of Statistics and Computer Science, LaLaguna University, 38071 Tenerife, Spain vicente.blanco@ull.es;Department of Electronics and Systems, A Coruña University, A Coruña, Spain patricia@dec.usc.es;Department of Electronics and Computer Science, Santiogo de Compostela University, 15706 Santiago, Spain caba@dec.usc.es;Department of Electronics and Computer Science, Santiogo de Compostela University, 15706 Santiago, Spain dora@dec.usc.es;Department of Electronics and Computer Science, Santiogo de Compostela University, 15706 Santiago, Spain tomas@dec.usc.es;Department of Electronics and Computer Science, Santiogo de Compostela University, 15706 Santiago, Spain juanjo@dec.usc.es;Department of Electronics and Computer Science, Santiogo de Compostela University, 15706 Santiago, Spain fran@dec.usc.es
Venue:
The Journal of Supercomputing
Year:
2004

Citing 9
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Abstract

In this paper, an exhaustive parallel library of sparse iterative methods and preconditioners in HPF and MPI was developed, and a model for predicting the performance of these codes is presented. This model can be used both by users and by library developers to optimize the efficiency of the codes, as well as to simplify their use. The information offered by this model combines theoretical features of the methods and preconditioners in addition to certain practical considerations and predictions about aspects of the performance of their execution in distributed memory multiprocessors.