LINPACK is a collection of Fortran subroutines that analyze and solve linear equations and linear least-squares problems. The package solves linear systems whose matrices are general, banded, symmetric indefinite, symmetric positive definite, triangular, and tridiagonal square. In addition, the package computes the QR and singular value decompositions of rectangular matrices and applies them to least-squares problems. LINPACK uses column-oriented algorithms to increase efficiency by preserving locality of reference. LINPACK was designed for supercomputers in use in the 1970s and early 1980s. LINPACK has been largely superceded by LAPACK, which has been designed to run efficiently on shared-memory, vector supercomputers. (Source:

References in zbMATH (referenced in 390 articles , 1 standard article )

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  1. Xue, Dingyü; Chen, YangQuan: Scientific computing with MATLAB (2016)
  2. Blesgen, Thomas: On rotation deformation zones for finite-strain Cosserat plasticity (2015)
  3. Grewal, Mohinder S.; Andrews, Angus P.: Kalman filtering. Theory and practice with MATLAB (2015)
  4. Park, Sungwoo; O’Leary, Dianne P.: A polynomial time constraint-reduced algorithm for semidefinite optimization problems (2015)
  5. Scherer, C.S.: An analytical approach to the strong evaporation problem in rarefied gas dynamics (2015)
  6. Bosner, Nela: Balancing three matrices in control theory (2014)
  7. Capiez-Lernout, E.; Soize, C.; Mignolet, M.-P.: Post-buckling nonlinear static and dynamical analyses of uncertain cylindrical shells and experimental validation (2014)
  8. D’Azevedo, Eduardo; Hu, Zhiang; Su, Shi-Quan; Wong, Kwai: Solving a large scale radiosity problem on GPU-based parallel computers (2014)
  9. Quarteroni, Alfio; Sacco, Riccardo; Saleri, Fausto; Gervasio, Paola: Numerical mathematics (2014)
  10. Sewell, Granville: Computational methods of linear algebra (2014)
  11. Weihs, Claus; Mersmann, Olaf; Ligges, Uwe: Foundations of statistical algorithms. With references to R packages (2014)
  12. Gijsberts, Arjan; Metta, Giorgio: Real-time model learning using incremental sparse spectrum Gaussian process regression (2013)
  13. Pozrikidis, Constantine: XML in scientific computing. (2013)
  14. Schäfer, Christian; Chopin, Nicolas: Sequential Monte Carlo on large binary sampling spaces (2013)
  15. Villegas, Juan G.; Prins, Christian; Prodhon, Caroline; Medaglia, Andrés L.; Velasco, Nubia: A matheuristic for the truck and trailer routing problem (2013)
  16. Wu, Qiang; Yang, Canqun; Tang, Tao; Xiao, Liquan: Exploiting hierarchy parallelism for molecular dynamics on a petascale heterogeneous system (2013)
  17. Auger, Anne; Bader, Johannes; Brockhoff, Dimo; Zitzler, Eckart: Hypervolume-based multiobjective optimization: theoretical foundations and practical implications (2012)
  18. Bosilca, George; Bouteiller, Aurelien; Danalis, Anthony; Herault, Thomas; Lemarinier, Pierre; Dongarra, Jack: DAGuE: A generic distributed DAG engine for high performance computing (2012)
  19. Chen, Jeng-Tzong; Lee, Jia-Wei; Leu, Shyue-Yuh: Analytical and numerical investigation for true and spurious eigensolutions of an elliptical membrane using the real-part dual BIEM/BEM (2012)
  20. Gimel’farb, Georgy (ed.); Hancock, Edwin (ed.); Imiya, Atsushi (ed.); Kuijper, Arjan (ed.); Kudo, Mineichi (ed.); Omachi, Shinichiro (ed.); Windeatt, Terry (ed.); Yamada, Keiji (ed.): Structural, syntactic, and statistical pattern recognition. Joint IAPR international workshop, SSPR&SPR 2012, Hiroshima, Japan, November 7--9, 2012. Proceedings (2012)

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