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. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Kressner, D., & Langou, J. (2007). Recent advances in dense linear algebra: Minisymposium abstract. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4699 LNCS, p. 116). Springer Verlag. https://doi.org/10.1007/978-3-540-75755-9_14
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