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Future Generation Computer Systems
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Future Generation Computer Systems
Article . 2019 . Peer-reviewed
License: Elsevier TDM
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Energy optimization of parallel programs in a heterogeneous system by combining processor core-shutdown and dynamic voltage scaling

Authors: Wang, Zhuowei; Wang, Hao; Zhao, Wuqing; Cheng, Lianglun;

Energy optimization of parallel programs in a heterogeneous system by combining processor core-shutdown and dynamic voltage scaling

Abstract

Abstract Reducing power consumption and improving efficiency are important aspects of the development of supercomputers into large-scale systems. As a result, heterogeneous systems have become an important development trend in high-performance computing. From the perspective of heterogeneous systems, this study establishes a model for energy optimization of parallel programs (EOPP) and puts forward a method of using it. By considering the energy overheads caused by re-synchronization, voltage switching, and operations in critical sections, the model effectively combines processor core-shutdown and dynamic voltage scaling technologies, which can be applied in a heterogeneous system to guide the optimization process. The results show that the proposed model can effectively reduce the energy consumption of parallel programs. Moreover, increasing the proportion of operations in the critical section enhances the optimal frequency of a processor while decreasing the probability of conflicts in the critical section. It can thus provide optimization space for reducing the frequency of a processor which ultimately reduces the energy overhead of the system.

Keywords

Energy optimization; Parallel program; Heterogeneous system; Processor core-shutdown; Dynamic voltage scaling

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Average
Green
hybrid