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In this paper an inverse preconditioner for the numerical solution of anelliptic Laplace prob- lem of a global circulation ocean model is presented.The inverse preconditiong technique is adopted in order to efficiently computethe numerical solution of the elliptic kernel by using the Conjugate Gradient(CG) method. We show how the performance and the rate of conver- gence of thesolver are linked to the discretized grid resolution and to the Laplacecoefficients of the oceanic model. Finally, we describe an easy-to-implementversion of the solver on the Graphical Processing Units (GPUs) by means ofscientific computing libraries and we discuss its performance.

A PCG Implementation of an Elliptic Kernel in an Ocean Global Circulation Model Based on GPU Libraries