Asymptotically Optimal Algorithm for Laplace Task Graphs on Heterogeneous Platforms

摘要

In this paper, we focus on the scheduling of Laplace task graph on a general platform where both communication links and processing units are heterogeneous. In this context, it is known that deriving optimal algorithm, in the sense of makespan minimization, is NP-Complete, and several inapproximation results have been proved. Nevertheless, we provide an asymtotically optimal algorithm in this general context. Moreover, we expect that this methodolgy can be extended to more general task graphs, especially for nested loops where the innermost loop is parallel.