An Efficient Stochastic Local Search for Heterogeneous Computing Scheduling

This work presents a stochastic local search method for efficiently solve the scheduling problem in heterogeneous computing environments. The research community has been searching for accurate schedulers for heterogeneous computing systems, able to perform in reduced times. The stochastic search proposed in this work is based on simple operators in order to keep the computational complexity as low as possible, thus allowing to efficiently tackle large scheduling instances. The experimental analysis demonstrates that the new stochastic local search method is able to compute accurate suboptimal schedules in significantly shorter execution times than state-of-the-art schedulers.