Matches in SemOpenAlex for { <https://semopenalex.org/work/W4226223878> ?p ?o ?g. }
- W4226223878 endingPage "29" @default.
- W4226223878 startingPage "1" @default.
- W4226223878 abstract "The standard LU factorization-based solution process for linear systems can be enhanced in speed or accuracy by employing mixed-precision iterative refinement. Most recent work has focused on dense systems. We investigate the potential of mixed-precision iterative refinement to enhance methods for sparse systems based on approximate sparse factorizations. In doing so, we first develop a new error analysis for LU- and GMRES-based iterative refinement under a general model of LU factorization that accounts for the approximation methods typically used by modern sparse solvers, such as low-rank approximations or relaxed pivoting strategies. We then provide a detailed performance analysis of both the execution time and memory consumption of different algorithms, based on a selected set of iterative refinement variants and approximate sparse factorizations. Our performance study uses the multifrontal solver MUMPS, which can exploit block low-rank factorization and static pivoting. We evaluate the performance of the algorithms on large, sparse problems coming from a variety of real-life and industrial applications showing that mixed-precision iterative refinement combined with approximate sparse factorization can lead to considerable reductions of both the time and memory consumption." @default.
- W4226223878 created "2022-05-05" @default.
- W4226223878 creator A5017738496 @default.
- W4226223878 creator A5022604100 @default.
- W4226223878 creator A5052601679 @default.
- W4226223878 creator A5060535239 @default.
- W4226223878 creator A5065253192 @default.
- W4226223878 creator A5082594621 @default.
- W4226223878 date "2023-03-21" @default.
- W4226223878 modified "2023-10-01" @default.
- W4226223878 title "Combining Sparse Approximate Factorizations with Mixed-precision Iterative Refinement" @default.
- W4226223878 cites W1540842995 @default.
- W4226223878 cites W1559275088 @default.
- W4226223878 cites W1975332401 @default.
- W4226223878 cites W1975818677 @default.
- W4226223878 cites W1977146902 @default.
- W4226223878 cites W1988201922 @default.
- W4226223878 cites W2014423375 @default.
- W4226223878 cites W2018136118 @default.
- W4226223878 cites W2020804487 @default.
- W4226223878 cites W2022484711 @default.
- W4226223878 cites W2035080386 @default.
- W4226223878 cites W2038205735 @default.
- W4226223878 cites W2053489736 @default.
- W4226223878 cites W2063675347 @default.
- W4226223878 cites W2069849438 @default.
- W4226223878 cites W2070299075 @default.
- W4226223878 cites W2077590638 @default.
- W4226223878 cites W2078126355 @default.
- W4226223878 cites W2111593426 @default.
- W4226223878 cites W2119623923 @default.
- W4226223878 cites W2129256515 @default.
- W4226223878 cites W2137541800 @default.
- W4226223878 cites W2226936188 @default.
- W4226223878 cites W2315019111 @default.
- W4226223878 cites W2317841906 @default.
- W4226223878 cites W23203733 @default.
- W4226223878 cites W2517659069 @default.
- W4226223878 cites W2599973081 @default.
- W4226223878 cites W2605947118 @default.
- W4226223878 cites W2607498875 @default.
- W4226223878 cites W2731353277 @default.
- W4226223878 cites W2752879223 @default.
- W4226223878 cites W2786704328 @default.
- W4226223878 cites W2808102735 @default.
- W4226223878 cites W2895305554 @default.
- W4226223878 cites W2903589674 @default.
- W4226223878 cites W2986784331 @default.
- W4226223878 cites W3000958723 @default.
- W4226223878 cites W3023393331 @default.
- W4226223878 cites W3108141724 @default.
- W4226223878 cites W3150959508 @default.
- W4226223878 cites W3203140351 @default.
- W4226223878 cites W4246470261 @default.
- W4226223878 cites W4281657881 @default.
- W4226223878 cites W4289772929 @default.
- W4226223878 cites W4292565208 @default.
- W4226223878 doi "https://doi.org/10.1145/3582493" @default.
- W4226223878 hasPublicationYear "2023" @default.
- W4226223878 type Work @default.
- W4226223878 citedByCount "3" @default.
- W4226223878 countsByYear W42262238782022 @default.
- W4226223878 countsByYear W42262238782023 @default.
- W4226223878 crossrefType "journal-article" @default.
- W4226223878 hasAuthorship W4226223878A5017738496 @default.
- W4226223878 hasAuthorship W4226223878A5022604100 @default.
- W4226223878 hasAuthorship W4226223878A5052601679 @default.
- W4226223878 hasAuthorship W4226223878A5060535239 @default.
- W4226223878 hasAuthorship W4226223878A5065253192 @default.
- W4226223878 hasAuthorship W4226223878A5082594621 @default.
- W4226223878 hasBestOaLocation W42262238781 @default.
- W4226223878 hasConcept C11413529 @default.
- W4226223878 hasConcept C121332964 @default.
- W4226223878 hasConcept C134978465 @default.
- W4226223878 hasConcept C155332342 @default.
- W4226223878 hasConcept C158693339 @default.
- W4226223878 hasConcept C159694833 @default.
- W4226223878 hasConcept C163716315 @default.
- W4226223878 hasConcept C173608175 @default.
- W4226223878 hasConcept C187834632 @default.
- W4226223878 hasConcept C199360897 @default.
- W4226223878 hasConcept C2524010 @default.
- W4226223878 hasConcept C2777210771 @default.
- W4226223878 hasConcept C2778770139 @default.
- W4226223878 hasConcept C2779982483 @default.
- W4226223878 hasConcept C33923547 @default.
- W4226223878 hasConcept C41008148 @default.
- W4226223878 hasConcept C42355184 @default.
- W4226223878 hasConcept C56372850 @default.
- W4226223878 hasConcept C62520636 @default.
- W4226223878 hasConceptScore W4226223878C11413529 @default.
- W4226223878 hasConceptScore W4226223878C121332964 @default.
- W4226223878 hasConceptScore W4226223878C134978465 @default.
- W4226223878 hasConceptScore W4226223878C155332342 @default.
- W4226223878 hasConceptScore W4226223878C158693339 @default.
- W4226223878 hasConceptScore W4226223878C159694833 @default.
- W4226223878 hasConceptScore W4226223878C163716315 @default.
- W4226223878 hasConceptScore W4226223878C173608175 @default.