A Method to Construct Task Scheduling Algorithms for Heterogeneous Multi-Core Systems

Sung Il Kim,Jong-Kook Kim

doi:10.1109/access.2019.2944238

Sung Il Kim, Jong-Kook Kim

Open Access

https://doi.org/10.1109/access.2019.2944238

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Abstract

The use of heterogeneous multicore processors (HMP) is spreading rapidly from data centers to large-scale deployment in smartphones because they give greater flexibility to adapt to power constraints and performance needs. In this study, we show that an intelligent task scheduler is critical for improving the performance and energy efficiency in an HMP environment. We assume that the tasks are independent in the environment, with hard real-time constraints and multicore systems, where the processors can be manipulated to change the clock cycle speed and power levels. Tasks are assumed to arrive aperiodically where the tasks are applications from the SPEC CPU 2006 benchmark suite. In the evaluation, we used a real system comprising of two multicore processors, which supported on-the-fly dynamic voltage/frequency scaling. We extracted several important components from previously proposed algorithms and combined them to construct algorithms with better performance. Our results showed that some of the best combinations reduced the energy consumption and achieved a better completion rate in the environment. In addition, a method is proposed for calculating the upper-bound of the task completion rate and energy consumption so that there is a guide as to how near the results are to the optimal performance.

Highlights

Constructing a processor using multiple simple cores rather than a single complex core is a mainstream practice because processors with multiple cores have a higher throughput and better power efficiency
The heterogeneous multicore processor (HMP) system considered in this study provides per processor on-the-fly dynamic voltage/frequency scaling (DVFS) such that frequency scaling and task scheduling can be performed dynamically
The step option had a 56.1% higher task completion rate with 23.13% more energy consumption compared with the no DVFS method

Summary

Introduction

Constructing a processor using multiple simple cores rather than a single complex core is a mainstream practice because processors with multiple cores have a higher throughput and better power efficiency. Wenjing and Lisheng [14] designed a task scheduling algorithm that considers both the execution time for tasks and energy consumption in an ILP model. Average of tasks in the queue: If the execution times of all tasks are not known in advance, the classification method must determine the threshold dynamically from information given through the runtime environment.

Results

Conclusion