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- sponsors
- University of Minnesota Supercomputing Institute
for Digital Simulation and Advanced Computation
University of Waterloo
Lawrence Livermore National Laboratory
Center for Applied Scientific Computing
- in cooperation with
- SIAM Linear Algebra Group
- conference chair
- Yousef Saad, University of Minnesota
- program co-chairs
- Daniel Pierce, The Boeing Company
Wei-Pai Tang, University of Waterloo
The goal of this conference is to address the complex issues related to the solution
of general sparse linear systems of equations in real applications, or specifically
in an industrial setting. It is often observed that the issues that are of interest
to industrial users of linear systems solution software are fairly different from
those on which the academic community is focussed. For example, in an industrial
context, improving robustness is far more important than finding a method that would
gain speed. Memory usage is also an important consideration -- which is seldom accounted
for in academic research on sparse solvers. As a last example, linear systems solved
in applications are almost always part of some nonlinear iteration (e.g. Newton)
or optimization loop, and it is important to consider the coupling between the linear
and nonlinear parts, instead of focussing on the linear system alone.
The speakers of this conference will discuss some of the latest developments in the
field of preconditioning methods for sparse linear systems. The conference will allow
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.
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