1 research outputs found
Systematic Generation of Algorithms for Iterative Methods
The FLAME methodology makes it possible to derive provably correct algorithms
from a formal description of a linear algebra problem. So far, the methodology
has been successfully used to automate the derivation of direct algorithms such
as the Cholesky decomposition and the solution of Sylvester equations. In this
thesis, we present an extension of the FLAME methodology to tackle iterative
methods such as Conjugate Gradient. As a starting point, we use a formal
description of the iterative method in matrix form. The result is a family of
provably correct pseudocode algorithms. We argue that all the intermediate
steps are sufficiently systematic to be fully automated.Comment: Master's Thesi