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Representing Linear Algebra Algorithms in Code: The FLAME Application Program Interfaces

机译:用代码表示线性代数算法:FLAME应用程序接口

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In this article, we present a number of Application Program Interfaces (APIs) for coding linear algebra algorithms. On the surface, these APIs for the MATLAB M-script and C programming languages appear to be simple, almost trivial, extensions of those languages. Yet with them, the task of programming and maintaining families of algorithms for a broad spectrum of linear algebra operations is greatly simplified. In combination with our Formal Linear Algebra Methods Environment (FLAME) approach to deriving such families of algorithms, dozens of algorithms for a single linear algebra operation can be derived, verified to be correct, implemented, and tested, often in a matter of minutes per algorithm. Since the algorithms are expressed in code much like they are explained in a classroom setting, these APIs become not just a tool for implementing libraries, but also a valuable tool for teaching the algorithms that are incorporated in the libraries. In combination with an extension of the Parallel Linear Algebra Package (PLAPACK) API, the approach presents a migratory path from algorithm to MATLAB implementation to high-performance sequential implementation to parallel implementation. Finally, the APIs are being used to create a repository of algorithms and implementations for linear algebra operations, the FLAME Interface REpository (FIRE), which already features hundreds of algorithms for dozens of commonly encountered linear algebra operations.
机译:在本文中,我们介绍了许多用于编码线性代数算法的应用程序接口(API)。从表面上看,这些用于MATLAB M脚本和C编程语言的API似乎是这些语言的简单,几乎琐碎的扩展。但是,有了它们,可以大大简化为广泛的线性代数运算编程和维护算法系列的任务。结合我们的形式线性代数方法环境(FLAME)方法来推导此类算法,可以为单个线性代数运算导出数十种算法,并验证其正确性,实现性和测试性,通常每分钟仅需几分钟算法。由于算法是在代码中表达的,就像在教室环境中解释的那样,因此这些API不仅成为实现库的工具,而且还成为了教学包含在库中的算法的有价值的工具。结合并行线性代数软件包(PLAPACK)API的扩展,该方法提供了一条从算法到MATLAB实现,从高性能顺序实现到并行实现的迁移路径。最后,API被用于创建线性代数运算的算法和实现的存储库,即FLAME接口存储库(FIRE),该库已经具有用于数十种常见线性代数运算的数百种算法。

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