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Content available remote Implementation of numerical integrationto high-order elements on the GPUs
EN
This article presents ways to implement a resource-consuming algorithm on hardware with a limited amount of memory, which is the GPU. Numerical integration for higher-order finite element approximation was chosen as an example algorithm. To perform compu- tational tests, we use a non-linear geometric element and solve the convection-diffusion- reaction problem. For calculations, a Tesla K20m graphics card based on Kepler archi- tecture and Radeon r9 280X based on Tahiti XT architecture were used. The results of computational experiments were compared with the theoretical performance of both GPUs, which allowed an assessment of actual performance. Our research gives sugges- tions for choosing the optimal design of algorithms as well as the right hardware for such a resource-demanding task.
EN
In this paper, we present a new approach based on Coifman wavelets to find approximate values of definite integrals. This approach overcomes both CAS and Haar wavelets and hybrid functions in terms of absolute errors. The algorithm based on Coifman wavelets can be easily extended to find numerical approximations for double and triple integrals. Illustrative examples implemented using Matlab show the efficiency and effectiveness of this new method.
EN
The traditional Boundary Element Method (BEM) is a numerical technique for solving some partial differential equations. The classical BEM produces fully populated coefficients matrix. With Galerkin Boundary Element Method (GBEM) is possible to produce the symmetric coefficients matrix. Generally the Galerkin boundary integral equations lead to the algebraic system where coefficients are defined by one or two dimensional integrals. The main problems are related to the integrals evaluation and treatment of the singularities. The article presents the general form of GBEM equations and problems associated with integration.
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