Parallel algorithms for unconstrained optimization

In this paper, parallel algorithms are proposed for locating the minimum point of a strictly convex quadratic function. The proposed algorithms are based on a new idea of group conjugacy and they can be considered parallel extensions of conjugate direction methods.