The investigator studies iterative methods to solve linear algebraic systems of equations efficiently on both sequential and parallel computers. In a large class of iterative methods, each iteration consists of a solution of another system of equations. If that system is in turn solved by an iterative method, it is called a two-stage iterative method. Among the questions to be investigated are criteria to determine the optimal or near-optimal number of inner iterations to guarantee overall convergence of the two-stage method. When a matrix is appropriately partitioned by blocks, and its diagonal blocks are nonsingular, many of the classical iterative methods can be generalized to treat each submatrix as a component. On a MIMD parallel computer (a computer that executes multiple streams of instructions on multiple streams of data), each diagonal block can be solved by a different processor, using components of previous iterations as soon as they are available. These are chaotic or asynchronous parallel block iterative methods. Their convergence properties as well as implementation details will be studied. Iterative methods for the solution of the general eigenvalue problem will also be studied. Experiments with these methods will be performed on different parallel architectures. A large class of problems in science and enginering is described by linear systems of equations. These are equations in which the unknown quantities appear in a simple way. An example of a linear system is the description of the forces on a building structure. These forces need to be calculated to design the building materials. The quantities to be calculated, called the variables or unknowns, are the forces on particular points of the structure. To describe a big structure, such as a high-rise building or a bridge, many hundreds or thousands of equations are needed, but because the forces on each point come only from a few neighboring points, the equations are relatively simple. A simple iterative method to solve such equations, that is, to find the values of the unknowns, consists in giving an initial approximation for the values of some unknowns, and then computing the values of the resulting forces on the other points of the structure. Parallel computers are simply a collection of computers or processors that communicate with each other. In the method just described, different processors can compute the value of the forces on different points simultaneously, using the information already computed by the other processors. This is repeated until all values satisfy all equations. This situation, if attained, is called convergence. Not all iterative methods attain convergence. In this project, the iterative methods for which convergence can be guaranteed will be studied. Experiments will be carried out to test them.
