caa a22 4500 46320297X CHVBK 20180405153117.0 cr unu---uuuuu 170326e20070501xx s 000 0 eng 10.1007/s00200-007-0037-x doi (NATIONALLICENCE)springer-10.1007/s00200-007-0037-x Gupta Anshul IBM T.J. Watson Research Center, 1101 Kitchawan Road, 10598, Yorktown Heights, NY, USA aut A Shared- and distributed-memory parallel general sparse direct solver [Elektronische Daten] [Anshul Gupta] An important recent development in the area of solution of general sparse systems of linear equations has been the introduction of new algorithms that allow complete decoupling of symbolic and numerical phases of sparse Gaussian elimination with partial pivoting. This enables efficient solution of a series of sparse systems with the same nonzero pattern but different coefficient values, which is a fairly common situation in practical applications. This paper reports on a shared- and distributed-memory parallel general sparse solver based on these new symbolic and unsymmetric-pattern multifrontal algorithms. Springer-Verlag, 2007 Sparse matrix factorization nationallicence Parallel sparse solvers nationallicence Multifrontal methods nationallicence Sparse LU decomposition nationallicence Applicable Algebra in Engineering, Communication and Computing Springer-Verlag 18/3(2007-05-01), 263-277 0938-1279 18:3<263 2007 18 200 https://doi.org/10.1007/s00200-007-0037-x text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00200-007-0037-x text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Gupta Anshul IBM T.J. Watson Research Center, 1101 Kitchawan Road, 10598, Yorktown Heights, NY, USA aut NATIONALLICENCE 773 0- Applicable Algebra in Engineering, Communication and Computing Springer-Verlag 18/3(2007-05-01), 263-277 0938-1279 18:3<263 2007 18 200 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer