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Abstract

Summary

The scalability of the Algebraic Multiscale Solver (AMS) ( ) for the heterogeneous pressure system that arises from incompressible flow in porous media is analyzed and experimentally demonstrated in parallel computing environments. The major steps of AMS are highly parallel, but the solver overall scalability is strongly tied to the choice of parameters and algorithms involved in each step. These choices additionally impact the convergence properties of the solver. The balance between computational scalability and convergence rate is carefully considered, to ensure high overall performance while maintaining robustness.

The basis-function kernel, which dominates the setup phase, and the local smoother, which dominates the solution phase, are studied in detail. In addition, the balance between convergence rate and scalability as a function of the coarsening ratio, Cr, is investigated.

Based on this analysis, the performance of a scalable AMS implementation is tested using highly heterogeneous problems derived from the SPE10 benchmark ( ) and geostatistically generated. The problems range in size from a few million to more than a 100 million cells. The solver robustness and scalability is demonstrated on modern multi-core systems and compared with the widely used parallel SAMG solver ( ).

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/content/papers/10.3997/2214-4609.20141772
2014-09-08
2024-04-24

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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.20141772
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Scalable Algebraic Multiscale Linear Solver for Large-scale Reservoir Simulation
Conference Proceedings 2014, 1 (2014); https://doi.org/10.3997/2214-4609.20141772
/content/papers/10.3997/2214-4609.20141772
/content/papers/10.3997/2214-4609.20141772
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