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PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:1.0
BEGIN:VEVENT
DTSTART:20141118T231500Z
DTEND:20141119T010000Z
LOCATION:New Orleans Theater Lobby
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: Jacobi-Davidson methods can efficiently compute a few eigenpairs of a large sparse matrix.=0ABlock variants of Jacobi-Davidson are known to be more robust than the standard algorithm, but they are usually avoided as the total number of floating point operations increases.=0AWe present the implementation of a block Jacobi-Davidson solver and show by detailed performance engineering and numerical experiments that the increase in operations is typically more than compensated by performance gains on modern architectures, giving a method that is both more efficient and robust than its single vector counterpart.
SUMMARY:Performance of Block Jacobi-Davidson Eigensolvers
PRIORITY:3
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