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All phases of the computation, including sym bolic processing as well as numeric factorization and triangular solution, are performed in parallel. A parallel Cartesian-nested dissection algorithm is used to compute a fill- reducing ordering for the matrix and an appropriate partitioning of the problem across the processors. The separator tree resulting from nested dissection is used to identify and exploit large-grain parallelism in the remaining steps of the computation. The parallel performance of the solver is reported for a series of test problems on the Thinking Machines CM-5 and the Intel Touchstone Delta. The parallel efficiency, scalability, and absolute perfor mance of the solver, as well as the relative importance of the various phases of the computation, are investigated empirically<\/jats:p>","DOI":"10.1177\/109434209701100104","type":"journal-article","created":{"date-parts":[[2007,3,4]],"date-time":"2007-03-04T20:17:47Z","timestamp":1173039467000},"page":"49-64","source":"Crossref","is-referenced-by-count":6,"title":["Performance of a Fully Parallel Sparse Solver"],"prefix":"10.1177","volume":"11","author":[{"given":"Michael T.","family":"Heath","sequence":"first","affiliation":[{"name":"DEPARTMENT OF COMPUTER SCIENCE AND NCSA, UNIVERSITY\rOF ILLINOIS, URBANA, IL 61801"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Padma","family":"Raghavan","sequence":"additional","affiliation":[{"name":"DEPARTMENT OF COMPUTER SCIENCE, UNIVERSITY OF TENNESSEE,\rKNOXVILLE, TN 37996-1301"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[1997,3,1]]},"reference":[{"key":"atypb1","doi-asserted-by":"crossref","unstructured":"Amdahl, G.M. 1967. 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