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PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:2.0
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DTSTART:20151117T231500Z
DTEND:20151118T010000Z
LOCATION:Level 4 - Lobby
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: Automatic Differentiation (AD) is an algorithmic technique for augmenting computer programs to compute derivatives accurately and efficiently. AD has two major modes: forward and reverse. Previous work on parallel reverse mode AD algorithms mainly focus on first order. In those work, the communication is considered as a remote value assignment. Then  the communication is also reversed when evaluating derivatives.=0A=0AHere, we describe a new parallel Reverse mode algorithm to compute higher order derivative for an MPI program. The innovation is that in a parallel reverse mode AD algorithm, a Send/Recv pair should not be considered only as a remote value assignment, but as dummy independent/dependent variables. The innovation permits communication to be treated analogous to computation. Hence communication does not need to be reversed, but can be re-performed in a separate phase. So complications created by reversing the communications is avoided.
SUMMARY:High Order Automatic Differentiation with MPI
PRIORITY:3
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