The use of heterogeneous multi-core architectures has increased because of their potential energy efficiency compared to the homogeneous multi-core architectures. The shift from homogeneous multi-core to heterogeneous multi-core architectures creates many challenges for scheduling applications on the heterogeneous multicore system. This paper studies the energy-efficient scheduling on Intel's QuickIA heterogeneous prototype platform [6] . A regression model is developed to estimate the energy consumption on the real heterogeneous multi-core platform. Our scheduling approach maps the program to the most appropriate core, based on program phases, through a combination of static analysis and runtime scheduling. We demonstrate the energy efficiency of our phase-based scheduling method by comparing it against the statical mapping approach proposed in [5] and the periodic sampling based approach proposed in [11] , The experimental results show that our scheduling scheme can achieve an average 10.20% reduction in the energy delay product compared to [5] and an average 19.81% reduction in energy delay product compared to [11] .
In REF , a global scheduling algorithm has been implemented on Intel's QuickIA uniform heterogeneous prototype platform and experimental studies showed that this approach is effective in improving the system energy efficiency.
Energy-efficient scheduling on heterogeneous multi-core architectures
ISLPED '12
Computer Science