Easing Message-Passing Parallel Programming Through a Data Balancing Service

The message passing model is now widely used for parallel computing, but is still difficult to use with some applications. The explicit data distribution or the explicit dynamic creation of parallel tasks can require a complex algorithm. In this paper, in order to avoid explicit data distribution, we propose a programming approach based on a data load balancing service for MPI-C. Using a parallel version of the merge sort algorithm, we show how our service avoids explicit data distribution completely, easing parallel programming. Some performance results are presented which compare our approach to a version of merge sort with explicit data distribution.