A Comparison Study of Static Mapping Heuristics for a Class of Meta-tasks on Heterogeneous Computing Systems

Heterogeneous computing (HC) environments are well suited tomeet the computational demands of large, diverse groups of tasks (i.e., a meta-task). The problem of mapping (de ned as matching and scheduling) these tasks onto the machines of an HC environment has been shown, in general, to be NP-complete, requiring the development of heuristic techniques. Selecting the best heuristic to use in a given environment, however, remains a di cult problem, because comparisons are often clouded by di erent underlying assumptions in the original studies of each heuristic. Therefore, a collection of eleven heuristics from the literature has been selected, implemented, and analyzed under one set of common assumptions. The eleven heuristics examine