Massively parallel sparse LU factorization

Abstract

The multifrontal algorithm for sparse LU factorization has been expressed as a data parallel program that is suitable for massively parallel computers. A new way of mapping data and computations to processors is used, and good processor utilization is obtained even for unstructured sparse matrices. The sparse problem is decomposed into many smaller, dense subproblems, with low overhead for communications and memory access. Performance results are provided for factorization of regular and irregular finite-element grid matrices on the MasPar MP-1.<>