Workload-Aware Power Optimization Strategy For Asymmetric Multiprocessors
DATE '16: Proceedings of the 2016 Conference on Design, Automation & Test in Europe(2016)
摘要
Asymmetric multi-core architectures, such as the ARM big. LITTLE, are emerging as successful solutions for the embedded and mobile markets due to their capabilities to trade-off performance and power consumption. However, both the Heterogeneous Multi-Processing (HMP) scheduler integrated in the commercial products and the previous research approaches are not able to fully exploit such potentiality. We propose a new runtime resource management policy for the big. LITTLE architecture integrated in Linux aimed at optimizing the power consumption while fulfilling performance requirements specified for the running applications. Experimental results show an improvement of the 11% on the performance and at the same time 8% in peak power consumption w.r.t. the current Linux HMP solution.
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关键词
asymmetric multiprocessors,workload-aware power optimization,asymmetric multicore architectures,heterogeneous multiprocessing scheduler,HMP scheduler,commercial products,runtime resource management policy,LITTLE architecture,power consumption,Linux HMP solution
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