Matches in SemOpenAlex for { <https://semopenalex.org/work/W3148229295> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W3148229295 endingPage "127" @default.
- W3148229295 startingPage "113" @default.
- W3148229295 abstract "Many applications rely on time-intensive matrix operations, such as factorization, which can be sped up significantly for large sparse matrices by interpreting the matrix as a sparse graph and computing a node ordering that minimizes the so-called fill-in. In this paper, we engineer new data reduction rules for the minimum fill-in problem, which significantly reduce the size of the graph while producing an equivalent (or near-equivalent) instance. By applying both new and existing data reduction rules exhaustively before nested dissection, we obtain improved quality and at the same time large improvements in running time on a variety of instances. Our overall algorithm outperforms the state-of-the-art significantly: it not only yields better elimination orders, but it does so significantly faster than previously possible. For example, on road networks, where nested dissection algorithms are typically used as a preprocessing step for shortest path computations, our algorithms are on average six times faster than Metis while computing orderings with less fill-in." @default.
- W3148229295 created "2021-04-13" @default.
- W3148229295 creator A5004139150 @default.
- W3148229295 creator A5059665527 @default.
- W3148229295 creator A5066225806 @default.
- W3148229295 date "2020-01-01" @default.
- W3148229295 modified "2023-09-23" @default.
- W3148229295 title "Engineering Data Reduction for Nested Dissection." @default.
- W3148229295 hasPublicationYear "2020" @default.
- W3148229295 type Work @default.
- W3148229295 sameAs 3148229295 @default.
- W3148229295 citedByCount "0" @default.
- W3148229295 crossrefType "proceedings-article" @default.
- W3148229295 hasAuthorship W3148229295A5004139150 @default.
- W3148229295 hasAuthorship W3148229295A5059665527 @default.
- W3148229295 hasAuthorship W3148229295A5066225806 @default.
- W3148229295 hasConcept C102192266 @default.
- W3148229295 hasConcept C111335779 @default.
- W3148229295 hasConcept C11413529 @default.
- W3148229295 hasConcept C121332964 @default.
- W3148229295 hasConcept C127413603 @default.
- W3148229295 hasConcept C13251829 @default.
- W3148229295 hasConcept C132525143 @default.
- W3148229295 hasConcept C154945302 @default.
- W3148229295 hasConcept C158693339 @default.
- W3148229295 hasConcept C163716315 @default.
- W3148229295 hasConcept C203776342 @default.
- W3148229295 hasConcept C22590252 @default.
- W3148229295 hasConcept C2524010 @default.
- W3148229295 hasConcept C33923547 @default.
- W3148229295 hasConcept C34736171 @default.
- W3148229295 hasConcept C41008148 @default.
- W3148229295 hasConcept C42355184 @default.
- W3148229295 hasConcept C45374587 @default.
- W3148229295 hasConcept C56372850 @default.
- W3148229295 hasConcept C62520636 @default.
- W3148229295 hasConcept C62611344 @default.
- W3148229295 hasConcept C66938386 @default.
- W3148229295 hasConcept C80444323 @default.
- W3148229295 hasConceptScore W3148229295C102192266 @default.
- W3148229295 hasConceptScore W3148229295C111335779 @default.
- W3148229295 hasConceptScore W3148229295C11413529 @default.
- W3148229295 hasConceptScore W3148229295C121332964 @default.
- W3148229295 hasConceptScore W3148229295C127413603 @default.
- W3148229295 hasConceptScore W3148229295C13251829 @default.
- W3148229295 hasConceptScore W3148229295C132525143 @default.
- W3148229295 hasConceptScore W3148229295C154945302 @default.
- W3148229295 hasConceptScore W3148229295C158693339 @default.
- W3148229295 hasConceptScore W3148229295C163716315 @default.
- W3148229295 hasConceptScore W3148229295C203776342 @default.
- W3148229295 hasConceptScore W3148229295C22590252 @default.
- W3148229295 hasConceptScore W3148229295C2524010 @default.
- W3148229295 hasConceptScore W3148229295C33923547 @default.
- W3148229295 hasConceptScore W3148229295C34736171 @default.
- W3148229295 hasConceptScore W3148229295C41008148 @default.
- W3148229295 hasConceptScore W3148229295C42355184 @default.
- W3148229295 hasConceptScore W3148229295C45374587 @default.
- W3148229295 hasConceptScore W3148229295C56372850 @default.
- W3148229295 hasConceptScore W3148229295C62520636 @default.
- W3148229295 hasConceptScore W3148229295C62611344 @default.
- W3148229295 hasConceptScore W3148229295C66938386 @default.
- W3148229295 hasConceptScore W3148229295C80444323 @default.
- W3148229295 hasLocation W31482292951 @default.
- W3148229295 hasOpenAccess W3148229295 @default.
- W3148229295 hasPrimaryLocation W31482292951 @default.
- W3148229295 hasRelatedWork W1495595721 @default.
- W3148229295 hasRelatedWork W1643654880 @default.
- W3148229295 hasRelatedWork W2090917733 @default.
- W3148229295 hasRelatedWork W2111712368 @default.
- W3148229295 hasRelatedWork W2115488732 @default.
- W3148229295 hasRelatedWork W2313903585 @default.
- W3148229295 hasRelatedWork W2612032746 @default.
- W3148229295 hasRelatedWork W2783463976 @default.
- W3148229295 hasRelatedWork W2891491149 @default.
- W3148229295 hasRelatedWork W2923101542 @default.
- W3148229295 hasRelatedWork W2963883200 @default.
- W3148229295 hasRelatedWork W2965758384 @default.
- W3148229295 hasRelatedWork W3001134538 @default.
- W3148229295 hasRelatedWork W3019931603 @default.
- W3148229295 hasRelatedWork W3090510908 @default.
- W3148229295 hasRelatedWork W3138153036 @default.
- W3148229295 hasRelatedWork W3173843690 @default.
- W3148229295 hasRelatedWork W3199665208 @default.
- W3148229295 hasRelatedWork W47249848 @default.
- W3148229295 hasRelatedWork W57373899 @default.
- W3148229295 isParatext "false" @default.
- W3148229295 isRetracted "false" @default.
- W3148229295 magId "3148229295" @default.
- W3148229295 workType "article" @default.