Automatic Generation of Loop-Invariants for Matrix Operations

Diego Fabregat-Traver, P. Bientinesi
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引用次数: 22

Abstract

In recent years it has been shown that for many linear algebra operations it is possible to create families of algorithms following a very systematic procedure. We do not refer to the fine tuning of a known algorithm, but to a methodology for the actual generation of both algorithms and routines to solve a given target matrix equation. Although systematic, the methodology relies on complex algebraic manipulations and non-obvious pattern matching, making the procedure challenging to be performed by hand, our goal is the development of a fully automated system that from the sole description of a target equation creates multiple algorithms and routines. We present CL1ck, a symbolic system written in Mathematica, that starts with an equation, decomposes it into multiple equations, and returns a set of loop-invariants for the algorithms -- yet to be generated -- that will solve the equation. In a successive step each loop-invariant is then mapped to its corresponding algorithm and routine. For a large class of equations, the methodology generates known algorithms as well as many previously unknown ones. Most interestingly, the methodology unifies algorithms traditionally developed in isolation. As an example, the five well known algorithms for the LU factorization are for the first time unified under a common root.
矩阵运算循环不变量的自动生成
近年来已经证明,对于许多线性代数运算,可以按照非常系统的程序创建算法族。我们不涉及已知算法的微调,而是涉及求解给定目标矩阵方程的算法和例程的实际生成的方法。虽然系统,方法依赖于复杂的代数操作和非明显的模式匹配,使过程具有挑战性的手工执行,我们的目标是开发一个完全自动化的系统,从目标方程的唯一描述创建多个算法和例程。我们介绍了CL1ck,一个用Mathematica编写的符号系统,它从一个方程开始,将其分解为多个方程,并返回一组循环不变量,用于求解该方程的算法(尚未生成)。在一个连续的步骤中,每个循环不变量被映射到它相应的算法和例程。对于一大类方程,该方法产生已知的算法以及许多以前未知的算法。最有趣的是,该方法将传统上孤立开发的算法统一起来。作为一个例子,五种众所周知的LU分解算法第一次统一在一个公共根下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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