PEPS: predictive energy-efficient parallel scheduler for multi-core processors

In multi-core processors, energy efficiency and performance consideration are essential issues. Usually, energy-saving techniques result in performance loss and vice versa. Therefore, energy delay product (EDP) is used broadly in many applications as a trade-off between energy saving and performance improvement. This paper presents a technique to perform work-stealing scheduling in the operating system kernel without needing any modification to the user-space program. The proposed scheduling uses predictive models to determine the optimal active number of cores and clock frequency of the processor as an optimum configuration at runtime for any running program to achieve the minimum EDP value. Since EDP is considered as a long-term metric, at runtime, in each specific time frame, PEPS uses the instruction per watt (IPW) to determine the best configuration. By using performance and power predicting models, PEPS finds the optimal configuration in terms of energy efficiency for the next time interval. Because different workloads at runtime have different behaviors and programs with different degrees of parallelization acted variously, the proposed method uses performance counters as a factor for workload characterization. Compared to the Linux scheduler, the proposed algorithm has up to 25% improvement in energy saving at the cost of 7% performance loss. Moreover, while reducing the temperature by 24%, it results in 19% improvement in EDP.