Litcius/Paper detail

Fairness-Aware Energy Efficient Scheduling on Heterogeneous Multi-Core Processors

Bagher Salami, Hamid Noori, Mahmoud Naghibzadeh

2020IEEE Transactions on Computers47 citationsDOI

Abstract

Heterogeneous multi-core processors (HMP) with the same instruction set architecture (ISA) integrate complex high performance big cores with power efficient small cores on the same chip. In comparison with homogeneous architectures, HMPs have been shown to significantly increase energy efficiency. However, current techniques to exploit the energy efficiency of HMPs do not consider fair usage of resources that leads to reduced performance predictability, a longer makespan, starvation, and QoS degradation. The effect of different cluster voltage and frequency levels on fairness is another issue neglected by previous task scheduling algorithms. The present study investigates both the fairness problem and energy efficiency in HMPs. This article proposes a heterogeneous fairness-aware energy efficient framework (HFEE) that employs DVFS to meet fairness constraints and provide energy efficient scheduling. The proposed framework is implemented and evaluated on a real heterogeneous multi-core processor. The experimental results indicate that the introduced technique can significantly improve energy efficiency and fairness when compared to Linux standard scheduler and two energy efficient and fairness-aware schedulers.

Topics & Concepts

Computer scienceEfficient energy useScheduling (production processes)Multi-core processorExploitDistributed computingPredictabilityFairness measureParallel computingQuality of serviceComputer networkMathematical optimizationOperating systemWirelessEngineeringElectrical engineeringPhysicsMathematicsThroughputComputer securityQuantum mechanicsParallel Computing and Optimization TechniquesCloud Computing and Resource ManagementDistributed and Parallel Computing Systems
Fairness-Aware Energy Efficient Scheduling on Heterogeneous Multi-Core Processors | Litcius