Wei, Yi-HungYi-HungWeiYang, Chuan-YueChuan-YueYangKuo, Tei-WeiTei-WeiKuoHung, Shih-HaoShih-HaoHungTEI-WEI KUOSHIH-HAO HUNG2020-05-042020-05-042010https://scholars.lib.ntu.edu.tw/handle/123456789/489991In recent years, various multi-core architectures have become popular selections for the designs of mobile platforms. With the strong computing demands from many multimedia applications, how to energy-efficiently utilize the computing power of mobile platforms without violations of timing constraints has become a critical design problem. In this paper, a data-partitioning-based approach is proposed to explore the parallelism of multimedia workload processing over multiple cores. Dynamic voltage scaling and dynamic power management strategies are both considered in the dynamic scaling of the computing power of cores and the adjustment of the set of active cores, respectively. The practicability and the energy efficiency of the proposed algorithms were evaluated by a series of experiments and simulations, for which we have encouraging results. © 2010 ACM.[SDGs]SDG7Computing demands; Computing power; Critical design; Data partitioning; Dynamic power management; Dynamic scaling; Dynamic voltage scaling; Energy efficient; Energy-Efficient Scheduling; Mobile platform; Multi processor scheduling; Multi-core processor; Multicore architectures; Multimedia applications; Multimedia tasks; Multimedia workloads; Real time scheduling; Timing constraints; Algorithms; Electric power measurement; Energy management; Mobile phones; Multiprocessing systems; Timing circuits; Energy efficiencyconference paper10.1145/1774088.1774142https://doi.org/10.1145/1774088.1774142