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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: Algebraic multigrid (AMG) is an iterative method often used to solve PDEs arising in various fields of science and engineering. The method is optimal, requiring only O(n) work to solve a system of n unknowns. Parallel implementations of AMG, however, lack scalability. As problem size increases, parallel AMG suffers from increasingly dense communication patterns, yielding network contention and reduced efficiency. The amount of communication can be reduced algorithmically with little change in convergence, through use of non-Galerkin coarse grids. The overall performance of parallel AMG can be further improved upon through the tradeoff of communication and convergence rates. Removing costly communication, such as that between two processors on opposite ends of the network, can improve the runtime of AMG if the cost saved from communication is greater than that added from decreasing convergence.
SUMMARY:Reducing Network Contention Associated with Parallel Algebraic Multigrid
PRIORITY:3
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