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Performance and power consumption analysis of Arm Scalable Vector Extension

机译:ARM可伸缩矢量扩展的性能和功耗分析

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摘要

Modern CPUs not only have multiple cores but also support wide single instruction multiple data (SIMD). This trend is expected to grow in the future. In this paper, we examine the effect of the vector length and the number of out-of-order resources on the performance and the power consumption of programs having multiple vector lengths using the Arm Scalable Vector Extension. Based on the performed evaluation, we conclude that using a longer vector length with multicycle vector units leads to up to approximately 30% improvement in performance and 21% decrease in power consumption than when using a shorter vector length.
机译:现代CPU不仅具有多个核心,还支持宽单指令多数据(SIMD)。 这一趋势预计将来会增长。 在本文中,我们研究了使用ARM可伸缩矢量扩展的具有多个矢量长度的程序的性能和程序的功耗和功耗的效果。 基于执行的评估,我们得出结论,使用具有多网载体单元的较长载体长度导致性能提高至多约30%,功耗降低了21%,而不是使用较短的向量长度。

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