可维护和可重用的科学软件改编:使科学软件改编民主化

Pilsung Kang, E. Tilevich, S. Varadarajan, Naren Ramakrishnan
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引用次数: 6

摘要

科学软件必须适应不同的执行环境、问题集和可用资源,以确保其效率和可靠性。尽管在最近的科学应用程序中可以找到相当大比例的适应模式,但传统的科学软件堆栈缺乏适当的适应抽象和工具。因此,科学的程序员手动实现难以维护和重用的临时解决方案。在本文中,我们提出了一种新的方法来适应用Fortran编写的科学软件。我们的方法利用了基于堆栈的命令式编程语言之间的二进制目标代码兼容性。这种兼容性使得将c++面向方面编程(AOP)扩展应用于Fortran程序成为可能。我们的方法将自适应功能表达为实现已知自适应模式的抽象方面,并且可以跨多个科学应用程序重用。特定于应用程序的代码通过继承系统地表示。由此产生的自适应功能可以由任何熟悉AOP的程序员维护,AOP已经成为现代软件开发的主要内容。我们通过重构一个现实世界计算流体动力学应用程序套件的手工编码自适应功能,验证了我们方法的表现力。重构后的代码通过消除重复和利用方面继承,平均减少了27%的ULOC来表达自适应功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Maintainable and reusable scientific software adaptation: democratizing scientific software adaptation
Scientific software must be adapted for different execution environments, problem sets, and available resources to ensure its efficiency and reliability. Although adaptation patterns can be found in a sizable percentage of recent scientific applications, the traditional scientific software stack lacks the adequate adaptation abstractions and tools. As a result, scientific programmers manually implement ad-hoc solutions that are hard to maintain and reuse. In this paper, we present a novel approach to adapting scientific software written in Fortran. Our approach leverages the binary object code compatibility between stack-based imperative programming languages. This compatibility makes it possible to apply a C++ Aspect-Oriented Programming (AOP) extension to Fortran programs. Our approach expresses the adaptive functionality as abstract aspects that implement known adaptation patterns and can be reused across multiple scientific applications. Application-specific code is systematically expressed through inheritance. The resulting adaptive functionality can be maintained by any programmer familiar with AOP, which has become a staple of modern software development. We validated the expressive power of our approach by refactoring the hand-coded adaptive functionality of a real-world computational fluid dynamics application suite. The refactored code expresses the adaptive functionality in 27% fewer ULOC on average by removing duplication and leveraging aspect inheritance.
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