Parallel Global Optimization Using Interval Analysis On Ipsc 2


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Parallel Global Optimization Using Interval Analysis on IPSC/2


Parallel Global Optimization Using Interval Analysis on IPSC/2

Author: Jerry Eriksson

language: en

Publisher:

Release Date: 1990


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Parallel Computing in Optimization


Parallel Computing in Optimization

Author: A. Migdalas

language: en

Publisher: Springer Science & Business Media

Release Date: 2013-12-01


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During the last three decades, breakthroughs in computer technology have made a tremendous impact on optimization. In particular, parallel computing has made it possible to solve larger and computationally more difficult prob lems. This volume contains mainly lecture notes from a Nordic Summer School held at the Linkoping Institute of Technology, Sweden in August 1995. In order to make the book more complete, a few authors were invited to contribute chapters that were not part of the course on this first occasion. The purpose of this Nordic course in advanced studies was three-fold. One goal was to introduce the students to the new achievements in a new and very active field, bring them close to world leading researchers, and strengthen their competence in an area with internationally explosive rate of growth. A second goal was to strengthen the bonds between students from different Nordic countries, and to encourage collaboration and joint research ventures over the borders. In this respect, the course built further on the achievements of the "Nordic Network in Mathematical Programming" , which has been running during the last three years with the support ofthe Nordic Council for Advanced Studies (NorFA). The final goal was to produce literature on the particular subject, which would be available to both the participating students and to the students of the "next generation" .

Handbook of Parallel Computing and Statistics


Handbook of Parallel Computing and Statistics

Author: Erricos John Kontoghiorghes

language: en

Publisher: CRC Press

Release Date: 2005-12-21


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Technological improvements continue to push back the frontier of processor speed in modern computers. Unfortunately, the computational intensity demanded by modern research problems grows even faster. Parallel computing has emerged as the most successful bridge to this computational gap, and many popular solutions have emerged based on its concepts