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The problem of scheduling tasks on a system of independent identical processors is discussed and the performance of a suboptimal method is evaluated. The computation is modeled by an acyclic directed graph G(T,<), where node set T represents the set of tasks to be completed and edge set < defines the precedence between tasks. The objective is to minimize the finishing time of the computation graph. Known theoretical results are reviewed and a general branch-and-bound algorithm for finding optimal solutions is presented. The schedules produced by a simple critical path priority method are shown to be near optimal for randomly generated computation graphs.