TNPACK
| Author | Tamar Schlick
Courant Institute of Mathematical Sciences 251 Mercer Street New York, NY 10012 Phone: (212) 998-3116 E-mail: schlick@cims.nyu.edu Aaron Fogelson
University of Utah,Department of Mathematics, Salt Lake City, Utah, 84112 |

Language | Fortran 77 | |

Algorithm | Truncated Newton Method using the preconditioned conjugate gradient algorithm | |

Input Format | ||

Modeling Languages link | ||

Commercial Status | free | |

Platform | Any machine with a reasonable amount of memory and a Fortran compiler | |

Remarks | TNPACK uses a preconditioned conjugate gradient method to solve the Newton equations approximately at every step.
Modifications are incorporated to handle indefiniteness of both the Hessian and the preconditioner. The preconditioning matrix (usually a sparse approximation to the Hessian) is provided by the user. It is factored by a sparse modified Cholesky factorization based on the Yale Sparse Matrix Package. TNPACK is intended to solve complex problems that arise in practical applications, such as computational chemistry and biology, where a natural separability or hierarchy in complexity exists among the different functional components. The user can adapt details of the algorithm to suit the problem at hand (for example, by preconditioning and variable reordering). | |

References |