Abstract
Heterogeneous cluster-based multi/many-core systems (e.g., ARM big.LITTLE, supporting dynamic voltage and frequency scaling (DVFS) at cluster level and dynamic power management (DPM) at core level) have attracted much attention to optimize energy on modern embedded systems. For concurrently executing applications on such a platform, this paper aims to study how to appropriately apply the three system configurations (mapping, DVFS, and DPM) to reduce both dynamic and static energy. To this end, this paper first formulates the dependence of the three system configurations on heterogeneous cluster-based systems as a 0–1 integrated linear programming (ILP) model, taking into account run-time configuration overheads (e.g., costs of DPM mode switching and task migration). Then, with the 0–1 ILP model, different run-time strategies (e.g., considering the three configurations in fully separate, partially separate, and holistic manners) are compared based on a hierarchical management structure and design-time prepared data. Experimental case studies offer insights into the effectiveness of different management strategies on different platform sizes (e.g., #cluster × #core, 2 × 4, 2 × 8, 4 × 4, 4 × 8), in terms of application migration, energy efficiency, resource efficiency, and complexity.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
