Abstract
These last past years have seen a tremendous amount of new results in computational dense linear algebra. New algorithms have been developed to increase the speed of convergence of eigensolvers, to improve the final accuracy of solvers, to improve the parallel efficiency of applications, and to harness even better the capability of our computing platforms. Of particular interest for this minisymposium are new algorithms that outperform the algorithms used in Sca/LAPACK’s current routines or match expected new functionality of the library.
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© 2007 Springer-Verlag Berlin Heidelberg
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Kressner, D., Langou, J. (2007). Recent Advances in Dense Linear Algebra: Minisymposium Abstract. In: Kågström, B., Elmroth, E., Dongarra, J., Waśniewski, J. (eds) Applied Parallel Computing. State of the Art in Scientific Computing. PARA 2006. Lecture Notes in Computer Science, vol 4699. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75755-9_14
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DOI: https://doi.org/10.1007/978-3-540-75755-9_14
Publisher Name: Springer, Berlin, Heidelberg
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