Power-performance modeling on asymmetric multi-cores

Abstract

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.