Multifrontal parallel distributed symmetric and unsymmetric solvers ?
We consider the solution of both symmetric and unsymmetric systems of sparse linear equations. A new parallel distributed memory multifrontal approach is described. To handle numerical pivoting efficiently, a parallel asynchronous algorithm with dynamic scheduling of the computing tasks has been developed. We discuss some of the main algorithmic choices and compare both implementation issues and the performance of the LDLT and LU factorizations. Performance analysis on an IBM SP2 shows the efficiency and the potential of the method. The test problems used are from the RutherfordBoeing collection and from the PARASOL end users.
mpi distributed memory architecture sparse matrices multifrontal direct methods