Efficient support for skeletons on workstation clusters

M. Danelutto

Abstract Beowulf class clusters are gaining more and more interest as low cost parallel architectures. They deliver reasonable performance at a very reasonable cost, compared to classical MPP machines. Parallel applications are usually developed on clusters using MPI/PVM message passing or HPF programming environments. Here we discuss new implementation strategies to support structured parallel programming environments for clusters based on skeletons. The adoption of structured parallel programming models greatly reduces the time spent in developing new parallel applications on clusters. The adoption of our implementation techniques based on macro data flow allows very efficient parallel applications to be developed on clusters. We discuss experiments that demonstrate the full feasibility of the approach.