Design and implementation of a novel dynamic load balancing library for cluster computing

This paper presents the design and implementation of a library based on an integrated approach to dynamic load balancing. This approach combines the advantages of optimizing data migration via novel dynamic loop scheduling strategies with the advances in resource management and task migration capabilities offered by a recently developed parallel runtime system. The performance improvements obtained by the use of this library have been investigated by its use in three scientific applications: the N-body simulations, the profiling of automatic quadrature routines, and the heat solver in an unstructured grid. The experimental results obtained underscore the significance of using such an integrated approach, as well as the benefits of using the library especially in applications characterized by irregular and unpredictable behavior.