HSL_MA97 Sparse symmetric system using OpenMP. HSL_MA97 uses a direct method to solve large sparse symmetric linear systems of equations AX=B. This package optionally uses OpenMP and is designed to achieve bit-compatible results regardless of the number of threads used. ..
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References in zbMATH (referenced in 12 articles )
Showing results 1 to 12 of 12.
- Gould, Nicholas I.M.; Robinson, Daniel P.: A dual gradient-projection method for large-scale strictly convex quadratic problems (2017)
- Scott, Jennifer: On using Cholesky-based factorizations and regularization for solving rank-deficient sparse linear least-squares problems (2017)
- Wan, Wei; Biegler, Lorenz T.: Structured regularization for barrier NLP solvers (2017)
- Dunning, Peter D.; Ovtchinnikov, Evgueni; Scott, Jennifer; Kim, H.Alicia: Level-set topology optimization with many linear buckling constraints using an efficient and robust eigensolver (2016)
- Hogg, Jonathan D.; Ovtchinnikov, Evgueni; Scott, Jennifer A.: A sparse symmetric indefinite direct solver for GPU architectures (2016)
- Gill, Philip E.; Wong, Elizabeth: Methods for convex and general quadratic programming (2015)
- Hogg, Jonathan; Scott, Jennifer: On the use of suboptimal matchings for scaling and ordering sparse symmetric matrices. (2015)
- Arioli, M.; Scott, J.: Chebyshev acceleration of iterative refinement (2014)
- Hogg, J.D.; Scott, J.A.: Compressed threshold pivoting for sparse symmetric indefinite systems (2014)
- Scott, Jennifer; Tůma, Miroslav: On signed incomplete Cholesky factorization preconditioners for saddle-point systems (2014)
- Scott, Jennifer; Tůma, Miroslav: HSL_MI28: an efficient and robust limited-memory incomplete Cholesky factorization code (2014)
- Hogg, Jonathan D.; Scott, Jennifer A.: Pivoting strategies for tough sparse indefinite systems (2013)