Python的性能可移植性框架

Nader Al Awar, Steven Zhu, G. Biros, Miloš Gligorić
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引用次数: 14

摘要

Kokkos是一个编程模型,用于为所有主要的高性能计算平台编写性能可移植的应用程序。它为数据管理和通用并行操作提供了抽象,允许开发人员编写可移植的高性能代码,而不需要了解特定于体系结构的细节。Kokkos是作为一个重度模板化的c++库实现的。然而,c++对于快速原型和快速算法探索来说并不理想。越来越多的开发人员使用Python进行科学计算、机器学习和数据分析。在本文中,我们提出了一个新的Python框架,称为PyKokkos,用于完全用Python编写性能可移植的应用程序。PyKokkos提供了类似kokkos的抽象,比c++接口更容易使用和更简洁。我们通过构建一个从Python子集到c++ Kokkos的转换器来实现PyKokkos,并通过自动生成的Python绑定桥接必要的函数调用。PyKokkos还兼容NumPy,一个广泛使用的高性能Python库。通过将几个现有的Kokkos应用程序移植到PyKokkos,包括ExaMiniMD(在c++中大约3k行代码),我们展示了后者可以以低性能开销实现高效执行。
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A performance portability framework for Python
Kokkos is a programming model for writing performance portable applications for all major high performance computing platforms. It provides abstractions for data management and common parallel operations, allowing developers to write portable high performance code with minimal knowledge of architecture-specific details. Kokkos is implemented as a heavily-templated C++ library. However, C++ is not ideal for rapid prototyping and quick algorithmic exploration. An increasing number of developers use Python for scientific computing, machine learning, and data analytics. In this paper, we present a new Python framework, dubbed PyKokkos, for writing performance portable applications entirely in Python. PyKokkos provides Kokkos-like abstractions that are easier to use and more concise than the C++ interface. We implemented PyKokkos by building a translator from a subset of Python to C++ Kokkos and bridging necessary function calls via automatically generated Python bindings. PyKokkos is also compatible with NumPy, a widely-used high performance Python library. By porting several existing Kokkos applications to PyKokkos, including ExaMiniMD (∼3k lines of code in C++), we show that the latter can achieve efficient execution with low performance overhead.
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