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IBM Journal of Research and Development
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IBM Journal of Research and Development
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LAPACK Users' guide (third ed.)
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ACM Transactions on Mathematical Software (TOMS)
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IEEE Transactions on Parallel and Distributed Systems
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IBM Journal of Research and Development
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ACM Transactions on Mathematical Software (TOMS)
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IBM Journal of Research and Development
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IBM Journal of Research and Development
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ACM Transactions on Mathematical Software (TOMS)
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For about ten years now, Bo Kågström's Group in Umea, Sweden, Jerzy Wasniewski's Team at Danish Technical University in Lyngby, Denmark, and I at IBM Research in Yorktown Heights have been applying recursion and New Data Structures (NDS) to increase the performance of Dense Linear Algebra (DLA) factorization algorithms. Later, John Gunnels, and later still, Jim Sexton, both now at IBM Research also began working in this area. For about three years now almost all computer manufacturers have dramatically changed their computer architectures which they call Multi-Core, (MC). It turns out that these new designs give poor performance for the traditional designs of DLA libraries such as LAPACK and ScaLAPACK. Recent results of Jack Dongarra's group at the Innovative Computing Laboratory in Knoxville, Tennessee have shown how to obtain high performance for DLA factorization algorithms on the Cell architecture, an example of an MC processor, but only when they used NDS. In this talk we will give some reasons why this is so.