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Task scheduling using a block dependency DAG for block-oriented sparse Cholesky factorization
2003
Parallel Computing
Block-oriented sparse Cholesky factorization decomposes a sparse matrix into rectangular subblocks; each block can then be handled as a computational unit in order to increase data reuse in a hierarchical memory system. Also, the factorization method increases the degree of concurrency and reduces the overall communication volume so that it performs more efficiently on a distributed-memory multiprocessor system than the customary column-oriented factorization method. But until now, mapping of
doi:10.1016/s0167-8191(02)00220-x
fatcat:joqgju7aabasfpdcqh3qbvwraq