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Performance and power consumption analysis of Arm Scalable Vector Extension

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Abstract

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.

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Acknowledgements

This work is partially funded by MEXT’s program for the Development and Improvement for the Next Generation Ultra High-Speed Computer System, under its Subsidies for Operating the Specific Advanced Large Research Facilities.

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  1. RIKEN Center for Computational Science, Kobe, Japan

    Tetsuya Odajima, Yuetsu Kodama & Mitsuhisa Sato

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  1. Tetsuya Odajima
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  2. Yuetsu Kodama
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  3. Mitsuhisa Sato
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Correspondence to Tetsuya Odajima.

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Odajima, T., Kodama, Y. & Sato, M. Performance and power consumption analysis of Arm Scalable Vector Extension. J Supercomput 77, 5757–5778 (2021). https://doi.org/10.1007/s11227-020-03495-5

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