HSL
HSL (formerly the Harwell Subroutine Library) is a collection of state-of-the-art packages for large-scale scientific computation written and developed by the Numerical Analysis Group at the STFC Rutherford Appleton Laboratory and other experts. HSL offers users a high standard of reliability and has an international reputation as a source of robust and efficient numerical software. Among its best known packages are those for the solution of sparse linear systems of equations and sparse eigenvalue problems. MATLAB interfaces are offered for selected packages. The Library was started in 1963 and was originally used at the Harwell Laboratory on IBM mainframes running under OS and MVS. Over the years, the Library has evolved and has been extensively used on a wide range of computers, from supercomputers to modern PCs. Recent additions include optimised support for multicore processors. If you are interested in our optimization or nonlinear equation solving packages, our work in this area is released in the GALAHAD library.
This software is also referenced in ORMS.
This software is also referenced in ORMS.
Keywords for this software
References in zbMATH (referenced in 275 articles , 2 standard articles )
Showing results 1 to 20 of 275.
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- Birgin, E. G.; Martínez, J. M.: Complexity and performance of an augmented Lagrangian algorithm (2020)
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- Cerdán, J.; Guerrero, D.; Marín, J.; Mas, J.: Preconditioners for rank deficient least squares problems (2020)
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- Orban, Dominique; Siqueira, Abel Soares: A regularization method for constrained nonlinear least squares (2020)
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- Alrehaili, A. H.; Walkley, M. A.; Jimack, P. K.; Hubbard, Matthew E.: An efficient numerical algorithm for a multiphase tumour model (2019)
- Andersson, Joel A. E.; Gillis, Joris; Horn, Greg; Rawlings, James B.; Diehl, Moritz: CasADi: a software framework for nonlinear optimization and optimal control (2019)
- Andreani, Roberto; Ramirez, Viviana A.; Santos, Sandra A.; Secchin, Leonardo D.: Bilevel optimization with a multiobjective problem in the lower level (2019)