Dynamic Load Balancing for Solution Adaptive FEA
on Heterogenious Clustures
Sponsored by: National Science
Foundation
Project period: 1996
Being able to use as much of the available compute cycles in a network
as possible is an area of active research at the present time. A suitable
load
balancing strategy is essential if efficient use of the compute servers
on a given network is to be assured. On heterogeneous networks of workstations,
widely differing processing capabilities coupled with unpredictable variations
in work load can pose a serious load balancing problem. In addition, adaptive
finite element analyses add further complexities by generating dynamically
varying amount of work load in different parts of the computational domain
as the solution evolves.
In distributed finite element analysis, the load balancing issues have
been addressed, typically using domain decomposition methods. However,
most of these strategies are static (or pseudo-static) and rely on knowledge
of system load and computational complexity of the numerical problem. In
case of solution adaptive finite element analysis on a heterogeneous network,
such assumptions are clearly violated leading to poor computational efficiency.
The current work addresses the above-mentioned issues by classifying
the imbalances using a severity measure and deals with each class
of imbalance separately. It uses concepts like buffer zones and
migration
to maintain the computation at a near-optimal load balanced state. The
strategies are adopted dynamically and are naturally suitable for networks
that may contain computers with widely varying capabilities and loads.
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Copyright 1994
Computational Mechanics Company Inc.