International Conference On Preconditioning Techniques For Scientific And Industrial Applications

May 16-18, 2011
Bordeaux, France

Universite Bordeaux 1


Conseil Régional d'Aquitaine


la CUB

Conference Chairs

Pascal Hénon,  TOTAL   /  INRIA,   France
Esmond G. Ng, Lawrence Berkeley National Laboratory, USA
Yousef Saad, The University of Minnesota, USA
Wei-Pai Tang, The Boeing Company, USA

Local Organization (INRIA Bordeaux Sud-Ouest, ENSEIRB, University of Bordeaux 1)

Emmanuel Agullo,  Luc Giraud, Abdou Guermouche, François Pellegrini,  Pierre Ramet, Jean Roman
Josy Baron, Laetitia Grimaldi


Click here for the program.

Open repository (HAL)  containing abstracts and authors information  is  also here .
The International Conference on Preconditioning Techniques for Scientific and Industrial Applications, Preconditioning 2011, is the seventh in a series of conferences that focus on preconditioning techniques in sparse matrix computation.  Past Preconditioning Conferences were
  • Preconditioning 1999, The University of Minnesota, Minneapolis, June 10-12 1999.
  • Preconditioning 2001, The Granlibakken Conference Center, Tahoe City, April 29 - May 1, 2001.
  • Preconditioning 2003, Embassy Suites Napa Valley, Napa, October 27-29, 2003.
  • Preconditioning 2005, Emory University, Atlanta, May 19-21, 2005.
  • Preconditioning 2007, Météopole, Toulouse, France, July 9-12, 2007.
  • Preconditioning 2009, Hong-Kong Baptist University, Hong-Kong, August 24-26, 2009.

The goal of this series of conferences is to address the complex issues related to the solution of general sparse matrix problems in large-scale real applications and in industrial settings.  The issues related to sparse matrix software that are of interest to application scientists and industrial users are often fairly different from those on which the academic community is focused.  For example, for an application scientist or an industrial user, improving robustness may be far more important than finding a method that would gain speed.  Memory usage is also an important consideration, but is seldom accounted for in academic research on sparse matrix solvers.  As a last example, linear systems solved in applications are almost always part of some nonlinear iteration (e.g., Newton) or optimization loop.  It is important to consider the coupling between the linear and nonlinear parts, instead of focusing on the linear systems alone.

The speakers of this conference will discuss some of the latest developments in the field of preconditioning techniques for sparse matrix problems.  The conference will allow participants to exchange findings in this area and to explore possible new directions in light of emerging paradigms, such as parallel processing and object-oriented programming.


  May 16-18, 2011.