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Highly scalable parallel algorithms for sparse matrix factorization
1997
IEEE Transactions on Parallel and Distributed Systems
In this paper, we describe a scalable parallel algorithm for sparse matrix factorization, analyze their performance and scalability, and present experimental results for up to 1024 processors on a Cray T3D parallel computer. Through our analysis and experimental results, we demonstrate that our algorithm substantially improves the state of the art in parallel direct solution of sparse linear systems-both in terms of scalability and overall performance. It is a well known fact that dense matrix
doi:10.1109/71.598277
fatcat:pwnnwungxbcavfi6imtrj7xv4q