Automatic Tuning of Master/Worker Applications

MORAJKO, ANNA; CÉSAR, EDUARDO; CAYMES SCUTARI, PAOLA; MARGALEF, TOMÀS; SORRIBES, JOAN; LUQUE, EMILIO

LECTURE NOTES IN COMPUTER SCIENCE

Springer Berlin / Heidelberg

Lugar: Berlín (Alemania); Año: 2005 vol. 3648 p. 95 - 103

0302-9743

The Master/Worker paradigm is one of the most commonly used by parallel/distributed application developers. This paradigm is easy to understand and is fairly close to the abstract concept of a wide range of applications. However, to obtain adequate performance indexes, such a paradigm must be managed in a very precise way. There are certain features, such as data distribution or the number of workers, that must be tuned properly in order to obtain such performance indexes, and in most cases they cannot be tuned statically since they depend on the particular conditions of each execution. In this context, dynamic tuning seems to be a highly promising approach since it provides the capability to change the parameters during the execution of the application to improve performance. In this paper, we demonstrate the usage of a dynamic tuning environment that allows for adaptation of the number of workers based on a theoretical model of Master/Worker behavior. The results show that such an approach significantly improves the execution time when the application modifies its behavior during execution.