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A parallel algorithm for sparse symbolic LU factorization without pivoting on out—of—core matrices

Finding the nonzero structures of the lower and upper triangular factors of an unsymmetric sparse matrix A is an important problem in the field of sparse matrix computations. Complementing previous research on sequential algorithms, we develop a parallel algorithm by appropriately intertwining a fully concurrent algorithm with an experimentally proved efficient algorithm (both algorithms are previous art). The resulting algorithm, intended to use with out-of-core matrices, leads to sensitive improvements in memory usage.
The algorithm is described in terms of its theoretical complexity, its experimental implementation with the MPI communication library the Origin 2000 multiprocessor, as well as its performance on large size real world matrices.