Linear Programming Based Affinity Scheduling for Heterogeneous Computing Systems

Abstract Resource management systems (RMS) are an important component in heterogeneous computing (HC) systems. One of the jobs of an RMS is the mapping of arriving tasks onto the machines of the HC system. Many different mapping heuristics have been proposed in recent years. However, most of these heuristics suffer from several limitations. One of these limitations is the performance degradation that results from using outdated global information about the status of all machines in the HC system. This paper proposes a new heuristic which addresses this limitation by only requiring partial information in making the mapping decisions. Simulation results show that our heuristic performs very competitively while requiring dramatically less information