A Study of Sparse Matrix Representations for Solving Linear Systems in a Functional Language

Abstract

Abstract This paper compares three different sparse matrix representations in Miranda for solving linear systems of equations: quadtrees, binary trees and run-length encoding. It compares the three data structures in each of two common linear system solvers, Conjugate Gradient and SOR. The test problems used in the paper arise from a simple reservoir model.