Scientific research and engineering computations are becoming dependent the modern high performance parallel computers increasingly. The algorithms for solving matrir eigen-problems is an important part in more computing projects. A brief review of the parallel algorithms for solving symmetric matrix eigenproblems is given here. A major emphasis is to collect bisection / multisection algorithm, divide and conquer algorithm,homotopy continuation method, Jacobi-like algorithm and iterative method.
A parallel block elimination algorithm for solving Hermitian matrir large eigen-value problems was provided in this paper. The algorithm prossess crude grain parallel properties. The high-quality black-bos for solving matrix eigenvalue problems, multi-processors and it’s local memory can be use effectively in this algorithm. It can be inplemented on high-performance distributed memory parallel computer.The convergencet error analysis of the algorithm, and parallel design are presented.A part of the numerical results are listed in this paper.
