Performance models for dynamic tuning of parallel applications on computational grids

Genaro Costa*, Josep Jorba, Anna Morajko, Tomas Margalef, Emilio Luque

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)


Performance is a main issue in parallel application development. Dynamic tuning is a technique that acts over application parameters to raise execution performance indexes. To perform that, it is necessary to collect measurements, analyze application behavior using a performance model and carry out tuning actions. Computational Grids present proclivity for dynamic changes on their features during application execution. Thus, dynamic tuning tools are indispensable to reach the expected performance indexes on those environments. A particular problem which provokes performance bottlenecks is the load distribution in master/worker applications. This paper addresses the performance modeling of such applications on Computational Grids for the perspective of dynamic tuning. It is inferred that grain size and number of workers are critical parameters to reduce execution time while raising the efficiency of resources usage. A heuristic to dynamically tune granularity and number of workers is proposed. The experimental simulated results of a matrix multiplication application in a heterogeneous Grid environment are shown.

Original languageEnglish
Pages (from-to)376-385
Number of pages10
JournalProceedings - IEEE International Conference on Cluster Computing, ICCC
Publication statusPublished - 2008


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