Asymmetric multi-core architectures have recently emerged as a promising alternative in a power and thermal constrained environment. They typically integrate cores with different power and performance characteristics, which makes mapping of workloads to appropriate cores a challenging task. Limited number of performance counters and heterogeneous memory hierarchy increase the difficulty in predicting the performance and power consumption across cores in commercial asymmetric multi-core architectures. In this work, we propose a software-based modeling technique that can estimate performance and power consumption of workloads for different core types. We evaluate the accuracy of our technique on ARM big. LITTLE asymmetric multi-core platform.

Asymmetric multi-core architectures integrating cores with diverse power-performance characteristics is emerging as a promising alternative in the dark silicon era where only a fraction of the cores on chip can be powered on due to thermal limits. We introduce a hierarchical power management framework for asymmetric multi-cores that builds on control theory and coordinates multiple controllers in a synergistic manner to achieve optimal power-performance efficiency while respecting the thermal design power budget. We integrate our framework within Linux and implement/evaluate it on real ARM big.LITTLE asymmetric multi-core platform.