Optimization Online


GPCG: A case study in the performance and scalability of optimization algorithms

Steve Benson (benson***at***mcs.anl.gov)
Lois McInnes (curfman***at***mcs.anl.gov)
Jorge More' (more***at***mcs.anl.gov)

Abstract: 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.

Keywords: large-scale optimization, high-performance architectures, object-oriented design

Category 1: Optimization Software and Modeling Systems (Optimization Software Design Principles )

Category 2: Optimization Software and Modeling Systems (Parallel Algorithms )

Category 3: Optimization Software and Modeling Systems (Problem Solving Environments )

Citation: Preprint ANL/MCS-P768-0799 Mathematics and Computer Science Division Argonne National Laboratory September 2000

Download: [Compressed Postscript]

Entry Submitted: 11/17/2000
Entry Accepted: 11/20/2000
Entry Last Modified: 11/17/2000

Modify/Update this entry

  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository


Coordinator's Board
Classification Scheme
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Programming Society