批处理离散傅里叶变换的DaCe可移植性与性能研究

Måns I. Andersson, S. Markidis
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引用次数: 2

摘要

随着新计算机体系结构的出现,可移植性和性能可移植性成为开发高性能计算应用程序的重要关注点。这项工作报告了我们使用DaCe在不同的单节点计算机系统上创建和优化批量离散傅里叶变换(DFT)计算的经验和教训。批处理DFT计算是FFT算法的重要组成部分,在计算机科学、数值分析和信号处理等领域有着广泛的应用。我们用三种复杂值数组数据布局实现了批处理DFT,并与原生复杂类型实现进行了比较。我们使用DaCe,它依赖于有状态数据流多图(SDFG)作为中间表示(IR),可以通过转换进行优化,然后为不同的体系结构生成代码。我们展示了几个性能结果,展示了DaCe在不同计算机系统上表达HPC应用程序的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Case Study on DaCe Portability & Performance for Batched Discrete Fourier Transforms
With the emergence of new computer architectures, portability and performance-portability become significant concerns for developing HPC applications. This work reports our experience and lessons learned using DaCe to create and optimize batched Discrete Fourier Transform (DFT) calculations on different single node computer systems. The batched DFT calculation is an essential component in FFT algorithms and is widely used in computer science, numerical analysis, and signal processing. We implement the batched DFT with three complex-value array data layouts and compare them with the native complex type implementation. We use DaCe, which relies on Stateful DataFlow multiGraphs (SDFG) as an intermediate representation (IR) which can be optimized through transforms and then generates code for different architectures. We present several performance results showcasing the potential of DaCe for expressing HPC applications on different computer systems.
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