使用优化的AOCL-FFTW提高量子浓缩咖啡的性能

S. Raut
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引用次数: 0

摘要

Quantum Espresso (QE)是一个用于纳米级电子结构计算和材料建模的开源软件套件。QE依赖于多个库,包括用于FFT计算的内部或外部库。在QE中,迭代对角化过程和电荷密度的计算使用了正反三维fft,这占了整个应用程序运行时的很大一部分。AOCL- FFTW是推荐用于AMD CPU系统上QE的FFT库。QE目前以次优的方式使用FFTW库,因此没有达到最佳性能。本文提出了一套新的设计和实现策略,应用于AOCL-FFTW,以克服QE在使用FFTW时的主要限制,而不需要对QE进行任何代码更改。本文给出了在AOCL-FFTW中所提出的优化的性能优势的结果。加速是在单节点和多节点测试执行中实现的,这有助于加速QE应用程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance speedup of Quantum Espresso using optimized AOCL-FFTW
Quantum Espresso (QE) is an open-source software suite for electronic-structure calculations and materials modeling at the nanoscale. QE depends upon multiple libraries including an internal or external library for FFT computations. The iterative diagonalization process and the computation of charge density in QE use forward and inverse 3D FFTs that account for a large portion of the total application runtime. AOCL- FFTW is the FFT library recommended for QE on AMD CPU systems. QE currently uses the FFTW library in a sub-optimal manner thereby not achieving the best performance. This paper presents a new set of design and implementation strategies applied in AOCL-FFTW to overcome the major limitations of QE in its use of FFTW without requiring any code changes in QE. Results showcasing the performance benefits of the proposed optimizations in AOCL-FFTW are presented in this paper. Speed-ups are achieved in single-node and multi-node test executions that help to accelerate the QE application.
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