Abstract
The performance of SPMD parallel programs is strongly affected by dynamic load imbalancing factors. The use of a suitable load balancing strategy is essential in overcoming the effects of these imbalancing factors. This chapter deals with concepts and experiments related to load balancing in SPMD applications. Initially, we discuss a set of classification criteria for load balancing algorithms designed for SPMD applications. In addition, we define a load imbalancing index in order to measure the load imbalance of a parallel application execution. In the experimental part of this chapter, we describe the development of an SPMD parallel application which computes the macroscopic thermal dispersion in porous media. Nine versions of this scientific application were developed, each one adopting a different load balancing strategy. We evaluate and compare the performance of these nine versions and show the importance of using an appropriate load balancing strategy for the characteristics of a specific SPMD parallel application.
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