GPCG: A Case Study in the Performance and Scalability of Optimization Algorithms

Details GPCG: A Case Study in the Performance and Scalability of Optimization Algorithms GPCG: A Case Study in the Performance and Scalability of Optimization Algorithms

2001-01-19

arxiv.org/abs/cs/0101018v1

Computer Science

Mathematical Software

title + 16 pages

Scientific paper

GPCG is an algorithm within the Toolkit for Advanced Optimization (TAO) for solving bound constrained, convex quadratic problems. Originally developed by More' and Toraldo, this algorithm was designed for large-scale problems but had been implemented only for a single processor. The TAO implementation is available for a wide range of high-performance architecture, and has been tested on up to 64 processors to solve problems with over 2.5 million variables.

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