Gauss-Jordan inversion with pivoting on the Caltech Mark II hypercube

Abstract

The performance of a parallel Gauss-Jordan matrix inversion1,2 algorithm on the Mark II hypercube3 at Caltech is discussed. We will show that parallel Gauss-Jordan inversion is superior to parallel Gaussian elimination for inversion, and discuss the reasons for this. Empirical and theoretical efficiencies for parallel Gauss-Jordan inversion as a function of matrix dimension for different numbers and configurations of processors are presented. The theoretical efficiencies are in quantitative agreement with the empirical efficiencies.