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Sparse matrices can be useful for computing large-scale applications that dense matrices cannot handle. One such application involves solving partial differential equations by using the finite element method.
The finite element method is one method of solving partial differential equations (PDEs). Compared with another numeric method, the finite difference method, the finite element method can handle geometrically complicated domains straightforwardly. The finite element method also has the flexibility to deal with problems that vary rapidly. Using the finite element method to solve PDEs involves the following steps.
The coefficient matrix is mostly sparse. Also, the size of the coefficient matrix is large in order to get an accurate approximation to the solution of PDEs. Therefore, practical finite element method applications always rely on sparse matrices and sparse matrix operations.
Complete the following steps to use the Multicore Analysis and Sparse Matrix VIs to solve the PDE by the finite element method.
Refer to the Solve PDE by FEM VI in the labview\examples\Multicore Analysis and Sparse Matrix\Sparse Matrix\Solve PDE by FEM directory for an example that uses the LabVIEW Multicore Analysis and Sparse Matrix Toolkit to solve a Poisson equation by the finite element method.