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

机译:通过结合处理器内核关闭和动态电压缩放功能,在异构系统中并行程序的能量优化

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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.
机译:降低功耗和提高效率是将超级计算机发展为大规模系统的重要方面。结果,异构系统已经成为高性能计算中的重要发展趋势。从异构系统的角度出发,本研究建立了并行程序能量优化(EOPP)模型,并提出了使用它的方法。通过考虑由重新同步,电压切换和关键部分的操作引起的能量开销,该模型有效地结合了处理器内核关闭和动态电压缩放技术,可将其应用于异构系统中以指导优化过程。结果表明,该模型可以有效降低并行程序的能耗。此外,增加关键部分中的操作比例可提高处理器的最佳频率,同时降低关键部分中发生冲突的可能性。因此,它可以提供用于减少处理器频率的优化空间,从而最终减少系统的能量开销。

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