Predictive mapping framework in heterogeneous computing environment

Heterogeneity of computer environment allows execution of large diverse applications, but it also simultaneously aggravates mapping. We present a combined multicriterial mapping based on the MEVSP model. Model parameters originate from the level of application, platform, mapping and user. The most suitable prediction methods are long-term performance prediction, short-term prediction of threshold violations and short-term predictions of categorical data. Heterogeneity level can be expressed by single or stochastic values and by consistency level. The application of the MEVSP model and prediction procedures can improve the application execution, as shown in a simplified environment.

[1]  Ladislau Bölöni,et al.  A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems , 2001, J. Parallel Distributed Comput..

[2]  Howard Jay Siegel,et al.  Task execution time modeling for heterogeneous computing systems , 2000, Proceedings 9th Heterogeneous Computing Workshop (HCW 2000) (Cat. No.PR00556).

[3]  Joseph L. Hellerstein,et al.  Predictive algorithms in the management of computer systems , 2002, IBM Syst. J..

[4]  Jennifer M. Schopf,et al.  Predicting sporadic grid data transfers , 2002, Proceedings 11th IEEE International Symposium on High Performance Distributed Computing.

[5]  Ian T. Foster,et al.  The anatomy of the grid: enabling scalable virtual organizations , 2001, Proceedings First IEEE/ACM International Symposium on Cluster Computing and the Grid.