Abstract
The paper presents methods for developing high performance computational cores and dense linear algebra routines. Different ap- proaches for performing matrix multiplication algorithms are analysed for hierarchical memory computers, taking into account their architec- tural properties and limitations. Block versions of matrix multiplication and LU-decomposition algorithms are described. The performance re- sults of these new algorithms for several processors are compared with the results obtained for optimized LAPACK and BLAS libraries.
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© 1999 Springer-Verlag Berlin Heidelberg
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Bessonov, O., Fougère, D., Quoc, K.D., Roux, B. (1999). Methods for Achieving Peak Computational Rates for Linear Algebra Operations on Superscalar RISC Processors. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 1999. Lecture Notes in Computer Science, vol 1662. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48387-X_18
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DOI: https://doi.org/10.1007/3-540-48387-X_18
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