On red-black SOR smoothing in multigrid
SIAM Journal on Scientific Computing - Special issue on iterative methods in numerical linear algebra; selected papers from the Colorado conference
Handbook of mathematics (3rd ed.)
Handbook of mathematics (3rd ed.)
Isoefficiency: Measuring the Scalability of Parallel Algorithms and Architectures
IEEE Parallel & Distributed Technology: Systems & Technology
A New Block Parallel SOR Method and Its Analysis
SIAM Journal on Scientific Computing
1/25 degree Atlantic Ocean Simulation Using HYCOM
DOD_UGC '05 Proceedings of the 2005 Users Group Conference on 2005 Users Group Conference
Performance modeling and automatic ghost zone optimization for iterative stencil loops on GPUs
Proceedings of the 23rd international conference on Supercomputing
Parallel S.O.R. iterative methods
Parallel Computing
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The Successive Over Relaxation (SOR) is a variant of the iterative Gauss-Seidel method for solving a linear system of equations Ax=b. The SOR algorithm is used within the NEMO (Nucleus for European Modelling of the Ocean) ocean model for solving the elliptical equation for the barotropic stream function. The NEMO performance analysis shows that the SOR algorithm introduces a significant communication overhead. Its parallel implementation is based on the Red-Black method and foresees a communication step at each iteration. An enhanced parallel version of the algorithm has been developed by acting on the size of the overlap region to reduce the frequency of communications. The overlap size must be carefully tuned for reducing the communication overhead without increasing the computing time. This work describes an analytical performance model of the SOR algorithm that can be used for establishing the optimal size of the overlap region.