Abstract
A framework for the vectorization and multitasking of optimization software is developed. It is then applied on the primal truncated Newton algorithm for nonlinear generalized network problems. The vectorization and multitasking of the algorithm is discussed and illustrated with computational experiments with the software system NLPNETG on the CRAY series of vector multiprocessors.
Original language | English (US) |
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Pages (from-to) | 449-470 |
Number of pages | 22 |
Journal | Mathematical Programming, Series B |
Volume | 42 |
Issue number | 2 |
State | Published - Nov 1 1988 |
All Science Journal Classification (ASJC) codes
- Software
- General Mathematics