Mapping heterogeneous task graphs onto heterogeneous system graphs

In this paper, a generic technique for mapping heterogeneous task graphs onto heterogeneous system graphs is presented. The task and system graphs studied in this paper have nonuniform computation and communication weights associated with the nodes and the edges. Two clustering algorithms have been proposed which can be used to obtain a multilayer clustered graph called a Spec graph from a given task graph and a multilayer clustered graph called a Rep graph from a given system graph. We present a mapping algorithm which produces a suboptimal matching of a given Spec graph containing M task modules, onto a Rep graph of N processors, in O(MP) fame, where P=max(M,N). Our experimental results indicate that our mapping algorithm is the fastest one and generates results which are better than, or similar to, those of other leading techniques which work only for restricted task or system graphs.