Vectorization of a Multiprocessor Multifrontal Code

We describe design changes that enhance the vectoriza tion of a multiprocessor version of a multifrontal code for the direct solution of large sparse sets of linear equations. These changes employ techniques used with success in full Gaussian elimination and are based on the use of matrix-vector and matrix-matrix kernels as implemented in the Level 2 and Level 3 BLAS. We illus trate the performance of the improved code by runs on the IBM 3090/VF, the ETA-10P, and the CRAY-2. Al though our experiments are principally on a single pro cessor of these machines, we briefly consider the influ ence of multiprocessing. Speedup factors of more than 11 are obtained, and the modified code performs at over 200 MFLOPS on standard structures problems on one processor of the CRAY-2.