Oltikar, Mohana, authorBriceño, Luis D., authorMaciejewski, Anthony A., authorSiegel, Howard Jay, author2007-01-032007-01-032006http://hdl.handle.net/10217/89368Heterogeneous computing (HC) is the coordinated use of different types of machines, networks, and interfaces to maximize the combined performance and/or cost effectiveness. Heuristics for allocating resources in an HC system have different optimization criteria. A common optimization criterion is to minimize the completion time of the last to finish machine (makespan). In some environments, it is useful to minimize the finishing times of the other machines in the system, i.e., those machines that are not the last to finish. Consider a production environment where a set of known tasks are to be mapped to resources off-line before execution begins. In this study, we present an "iterative" approach for decreasing the finishing time of each machine in a given resource allocation, by repeatedly running a mapping heuristic to minimize makespan on all machines and then the non-makespan machines; i.e., ignoring the current makespan machine and the tasks assigned to it. This work identifies heuristics that can offer improvements in the completion time of non-makespan machines using this "iterative" approach.born digitalStudent workspostersengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.computingallocationheterogeneousiterativeText