Clustering and reassignment-based mapping strategy for message-passing architectures

A fundamental issue affecting the performance of a parallel program is the assignment of tasks to processors in order to get the minimum completion time. We present a compilation-time two-stage mapping strategy (denoted as CREMA) used for mapping arbitrary programs (modeled as TIG graphs) onto message passing parallel systems with any architecture. In contrast to most of the other approaches found in the literature, CREMA is not tied to any particular architecture or any specific algorithm. The first stage is based on task clustering and task reassignment algorithms that contract the original task graph. The second stage takes the contracted graph and tries to successfully match the physical properties of the target system. It has been evaluated for a wide range of both regular and irregular graphs that correspond to some well-known real applications. The results show that CREMA provides a good trade-off between mapping quality and computational complexity