In this paper, a method via sparse-sparse iteration for computing a sparse incomplete factorization of the inverse of a symmetric positive definite matrix is proposed. The resulting factorized sparse approximate inverse is used as a preconditioner for ...
In this paper, we describe scalable parallel algorithms for symmetric sparse matrix factorization, analyze their performance and scalability, and present experimental results for up to 1,024 processors on a Cray T3D parallel computer. Through our ...
The matrix-vector multiplication operation is the kernel of most numerical algorithms.Typically, matrix-vector multiplication algorithms exploit the sparsity of a matrix, either to reduce the time taken or the memory used. In the case of parallel ...
IEEE Computer Society
United States
