Abstract
Efficient data motion is critical for high performance computing on distributed memory architectures. The value of some techniques for efficient data motion is illustrated by identifying generic communication primitives. Further, the efficiency of these primitives is demonstrated on three different applications using the finite element method for unstructured grids and sparse solvers with different communication requirements. For the applications presented, the techniques advocated reduced the communication times by a factor of between 1.5 and 3.
Highlights
The nite element method is a popular technique for solving boundary and initial value problems
The results presented here are based on meshes which are composed of only one type of elements, the set of communication functions described here can be used for meshes comprising of di erent types of elements
This article introduces a set of communication primitives that are very useful for unstructured nite element simulations
Summary
The nite element method is a popular technique for solving boundary and initial value problems. This article identi es a common set of communication primitives in the data parallel programming model which express most of the communication needs for unstructured nite element simulations. The rst example application is a three{dimensional, fully dynamic nite element formulation that has been used to study the rate dependent three{dimensional deformation in the Charpy V{notch test Mathur et al, 1992a, Tvergaard and Needleman, 1986 and 1988] This is an explicit formulation in which the desired solution phase is spread out over several thousand time increments. The third application is from computational uid dynamics where the steady state Euler ow on a complete airplane is computed for a mesh involving almost a million degrees of freedom Johan et al, 1992] This is a fully implicit formulation based on a preconditioned matrix free restarted GMRES algorithm Saad and Schultz, 1986]
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