A task graph centroid

When one is concerned with maximizing overall program throughput, task mapping in a heterogeneous computing environment presents the problem of which computing unit(s) is best suited to perform each task. This paper explores the concept that finding a “better” starting point for the static mapping process will provide a better opportunity for success. A starting point based on a computation task graph centroid, similar to that of masses in the gravity system, is derived such that the centroid of the task graph is the mapping starting point. Comparisons based on experimentation are then made using the HP Greedy mapping technique (Leangsuksun and Potter, 1994) while varying the starting point from beginning, centroid and end of the problem. Results show that the task centroid mapping technique does not increase the complexity of the mapping process but does result in an improved overall program throughput