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Matrix Algebra and Applicative Programming
 Functional Programming Languages and Computer Architecture (Proceedings
, 1987
"... General Term: Algorithms. The broad problem of matrix algebra is taken up from the perspective of functional programming. Akey question is how arrays should be represented in order to admit good implementations of wellknown e cient algorithms, and whether functional architecture sheds any new ligh ..."
Abstract

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General Term: Algorithms. The broad problem of matrix algebra is taken up from the perspective of functional programming. Akey question is how arrays should be represented in order to admit good implementations of wellknown e cient algorithms, and whether functional architecture sheds any new light on these or other solutions. It relates directly to disarming the \aggregate update " problem. The major thesis is that 2 dary trees should be used to represent ddimensional arrays � examples are matrix operations (d = 2), and a particularly interesting vector (d = 1) algorithm. Sparse and dense matrices are represented homogeneously, but at some overhead that appears tolerable � encouraging results are reviewed and extended. A Pivot Step algorithm is described which o ers optimal stability at no extra cost for searching. The new results include proposed sparseness measures for matrices, improved performance of stable matrix inversion through repeated pivoting while deep within a matrixtree (extendible to solving linear systems), and a clean matrix derivation of the vector algorithm for the fast Fourier transform. Running code is o ered in the appendices.