螺旋的A64可伸缩矢量扩展自适应调谐

2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) Pub Date : 2021-06-01 DOI:10.1109/IPDPSW52791.2021.00117

Naruya Kitai, D. Takahashi, F. Franchetti, T. Katagiri, S. Ohshima, Toru Nagai

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引用次数: 0

摘要

在本文中，我们提出了一种自动调谐(AT)系统，该系统采用A64可伸缩向量扩展来生成离散傅里叶变换(DFT)实现。使用名古屋大学的超级计算机“Flow”对我们的方法进行了性能评估。A64可扩展向量扩展应用DFT码比标量DFT码快1.98倍，SIMD指令速率高3.63倍。此外，采用所提出的AT系统进行环展开，得到最大加速系数为2.32。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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An Auto-tuning with Adaptation of A64 Scalable Vector Extension for SPIRAL

In this paper, we propose an auto-tuning (AT) system by adapting the A64 Scalable Vector Extension for SPIRAL to generate discrete Fourier transform (DFT) implementations. The performance of our method is evaluated using the Supercomputer "Flow" at Nagoya University. The A64 scalable vector extension applied DFT codes are up to 1.98 times faster than scalar DFT codes and up to 3.63 times higher in terms of the SIMD instruction rate. In addition, we obtain a factor of maximum speedup 2.32 by adapting proposed AT system for loop unrolling.

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2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

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