PARALLEL PRECONDITIONING USING SPARSE APPROXIMATE INVERSES

		      Michele Benzi
       Computer Research and Applications (CIC-3)
             Los Alamos National Laboratory
	         Los Alamos, New Mexico

ABSTRACT. I will give an overview of some of my work on parallel
preconditioning for large sparse linear systems arising from a
variety of LANL applications. The emphasis will be on sparse
approximate inverse techniques, but some results with a parallel
Algebraic Multigrid (AMG) code will also be included. 

As a typical application, I will briefly discuss an approach
to solving radiation transport problems using discontinuous
discretization schemes. This approach is currently being developed
in collaboration with the Transport Methods Group at LANL.


BIO: Michele Benzi received a PhD in Mathematics from North
     Carolina State University in 1993. He has since held
     positions at the University of Bologna in Italy, and at
     CERFACS in Toulouse, France. He is currently a Technical
     Staff member in the Computer Research and Applications
     Group at Los Alamos National Laboratory, where he has been
     since 1997.

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