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  <title><![CDATA[CDA Distinguished Lecture: Dr. Yousef Saad]]></title>
  <body><![CDATA[<p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</p><p><strong>Speaker:</strong> Dr. Yousef Saad, College of Science &amp; Engineering Distinguished Professor in the Department of Computer Science &amp; Engineering at the University of Minnesota</p><p><strong>Title: </strong></p><p>Multilevel Algebraic Preconditioning Techniques with Applications</p><p>&nbsp;<strong>Abstract: </strong></p><p>Solving linear systems of equations with iterative methods is becoming more difficult due to a number of new challenges. Matrices of these systems are becoming larger, more ill-conditioned, and are often poorly structured, and indefinite. Multilevel methods have been advocated for handling some of these challenges. This talk will introduce a variety of multilevel preconditioners for solving linear systems of equations, with an emphasis on indefinite systems. We begin with the Algebraic Recursive Multilevel Solver (ARMS) and see how a class of "coarsening" schemes can be adapted to this framework.&nbsp;</p><p>ILU-type preconditioners have difficulties for some types of indefinite problems. We will show how they can be adapted for problems arising from Helmholtz equations. Then a new class of methods based on low-rank approximations which has some appealing features will be introduced. The methods handle indefiniteness quite well and are more amenable to SIMD computations, which makes them attractive for GPUs.&nbsp; We will then present an application in dynamic mean field theory (DMFT) where the problem is to compute the diagonal of the inverse of a matrix.</p><p>&nbsp;<strong>Bio:</strong></p><p>Yousef Saad is a College of Science &amp; Engineering Distinguished Professor in the Department of Computer Science &amp; Engineering at the University of Minnesota.&nbsp; He holds the William Norris Chair for Large-Scale Computing and is a fellow of SIAM and AAAS.&nbsp; He is known for his contributions to matrix computations, including iterative methods for solving large sparse linear algebraic systems, eigenvalue problems, and parallel computing.&nbsp; Dr. Saad is an ISI highly cited researcher in mathematics and is the author of the highly cited book, Iterative Methods for Sparse Linear Systems.&nbsp; For more information, please visit <a href="http://www-users.cs.umn.edu/~saad/">http://www-users.cs.umn.edu/~saad</a></p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p>]]></body>
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      <value><![CDATA[Multilevel Algebraic Preconditioning Techniques with Applications]]></value>
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      <value><![CDATA[2013-04-05T15:00:00-04:00]]></value>
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      <value><![CDATA[<p>Host: Edmond Chow; <a href="mailto:echow@cc.gatech.edu">echow@cc.gatech.edu</a></p>]]></value>
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