SCHEDULE: NOV 10-16, 2012
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Scalable Direct Eigenvalue Solver ELPA for Symmetric Matrices
SESSION: Research Poster Reception
EVENT TYPE: Posters and Electronic Posters
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Torsten Hoefler
AUTHOR(S):Hermann Lederer, Andreas Marek
ROOM:East Entrance
ABSTRACT:
ELPA is a new efficient distributed parallel direct eigenvalue solver for symmetric matrices. It contains both an improved one-step ScaLAPACK type solver (ELPA1) and the two-step solver ELPA2 [1,2]. ELPA has demonstrated good scalability for large matrices up to 294.000 cores of a BlueGene/P system [3].
ELPA is especially beneficial when a significant part, but not all eigenvectors are needed. For a quantification of this statement, matrix sizes of 10,000, 20,000, and 50,000 have been solved with ELPA1, ELPA2 and ScaLAPACK routines from Intel MKL 10.3 for real and complex matrices with eigenvector fractions of 10%, 25%, 50% and 100% on 1024 cores of an Intel Sandy Bridge based Linux cluster with FDR10 Infiniband interconnect.
Results are presented and discussed.
[1] T. Auckenthaler et al, Parallel Computing, Vol. 27, Issue 12, p. 783-794 (2011)
[2] http://elpa.rzg.mpg.de
[3] R. Johanni et al, in: Technical Report FZJ-JSC-IB-2011-02, p. 27-30, April 2011
Chair/Author Details:
Torsten Hoefler (Chair) - ETH Zurich
Hermann Lederer - Max Planck Society
Andreas Marek - Max Planck Society
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Scalable Direct Eigenvalue Solver ELPA for Symmetric Matrices
SESSION: Research Poster Reception
EVENT TYPE:
TIME: 5:15PM - 7:00PM
SESSION CHAIR: Torsten Hoefler
AUTHOR(S):Hermann Lederer, Andreas Marek
ROOM:East Entrance
ABSTRACT:
ELPA is a new efficient distributed parallel direct eigenvalue solver for symmetric matrices. It contains both an improved one-step ScaLAPACK type solver (ELPA1) and the two-step solver ELPA2 [1,2]. ELPA has demonstrated good scalability for large matrices up to 294.000 cores of a BlueGene/P system [3].
ELPA is especially beneficial when a significant part, but not all eigenvectors are needed. For a quantification of this statement, matrix sizes of 10,000, 20,000, and 50,000 have been solved with ELPA1, ELPA2 and ScaLAPACK routines from Intel MKL 10.3 for real and complex matrices with eigenvector fractions of 10%, 25%, 50% and 100% on 1024 cores of an Intel Sandy Bridge based Linux cluster with FDR10 Infiniband interconnect.
Results are presented and discussed.
[1] T. Auckenthaler et al, Parallel Computing, Vol. 27, Issue 12, p. 783-794 (2011)
[2] http://elpa.rzg.mpg.de
[3] R. Johanni et al, in: Technical Report FZJ-JSC-IB-2011-02, p. 27-30, April 2011
Chair/Author Details:
Torsten Hoefler (Chair) - ETH Zurich
Hermann Lederer - Max Planck Society
Andreas Marek - Max Planck Society
Click here to download .ics calendar file