Dept. of Computer Science and Engineering
Oregon Graduate Center
This paper deals with the problem of solving a system of sparse nonsymmetric matrices on a distributed memory multiprocessor computer, the Intel iPSC (hypercube). The processors have substantial local memory but no global shared memory. They communicate among themselves and with a host processor through message passing. The primary interest is to design an algorithm which exploits parallelism, and which performs elimination and solution of large sparse matrices. Elimination is performed by LU- decomposition. The storage scheme is based on linked list data-structure defined for a given generated matrix. The matrix is distributed by columns in a "wrapped" fashion so that elimination in the natural order will be balanced, if the sparsity structure is equally distributed across the columns. Numerical results from experiments running on the hypercube are included along with performance analysis.
Nader, Babak, "Parallel solution of sparse linear systems" (1987). Scholar Archive. 235.