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A Method to Construct Task Scheduling Algorithms for Heterogeneous Multi-Core Systems
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DOI：10.1109/ACCESS.2019.2944238.png)
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摘要
En 中文
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.
Keyword:
Task analysis
Program processors
Scheduling
Multicore processing
Scheduling algorithms
Real-time systems
Heuristic algorithms
Task scheduling
energy-aware scheduling
heterogeneous multi-core
real-time scheduling
dynamic voltage
frequency scaling
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3.6
论文数:
9.8W
被引数:
29.4W
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