Abstract
In this paper we present methods for developing high performance computational kernels and dense linear algebra routines. First, the microarchitecture of AMD Athlon processors is analyzed, with the goal to achieve peak computational rates. These processors are widely used for building inexpensive PC clusters. Then, different approaches for implementing matrix multiplication algorithms are analyzed for hierarchical memory computers, taking into account their architectural properties and limitations. Block versions of matrix multiplication and LU-decomposition algorithms are considered. Finally, the obtained performance results for AMD Athlon/Duron processors are discussed in comparison with other approaches.
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© 2003 Springer-Verlag Berlin Heidelberg
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Bessonov, O., Fougère, D., Roux, B. (2003). Analysis of Architecture and Design of Linear Algebra Kernels for Superscalar Processors. In: Malyshkin, V.E. (eds) Parallel Computing Technologies. PaCT 2003. Lecture Notes in Computer Science, vol 2763. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45145-7_33
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DOI: https://doi.org/10.1007/978-3-540-45145-7_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40673-0
Online ISBN: 978-3-540-45145-7
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