Type for the fpt header, stores all information needed to initialize the fpt method later on
Type | Visibility | Attributes | Name | Initial | |||
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type(ply_nodes_header_type), | private | :: | nodes_header | ||||
real(kind=rk), | private | :: | factor | = | 1.0_rk | In case of nonlinear equations, aliasing occurs if the projections of the nonlinear terms on the testfunctions are not calculated accurately enough. To avoid these errors it is possible to extend the transformation vectors of the FPT with zeros. This factor determines by how many zeros the modal vector is extended before transformation. This factor has to be chosen properly with respect of the type of nonlinearity of your equation. |
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integer, | private | :: | blocksize | = | ply_fpt_default_blocksize | The blockisze of the fast bases exchange algorithm from Legendre to Chebyshev polynomials. A negative number indicates to use the default blocksize of the algorithm. |
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integer, | private | :: | approx_terms | = | ply_fpt_default_approx_terms | The number of approximation terms to use for blocks apart from the diagonal. This defaults to 18, which is recommended for double precision. |
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integer, | private | :: | implementation | The implementation variant to use for the transformation computation. The computation can be done either by a |
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integer, | private | :: | striplen | = | vlen | The striplen, that should be used for vectorized simultaneous computations of the matrix operation. This defaults to the vlen from the TEM_compileconf_module, it might be set differently here, as we are dealing with a twodimensional problem here, and the optimal setting might be different from the code parts. |
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integer, | private | :: | subblockingWidth | = | ply_fpt_default_subblockingWidth | The width of the subblocks used during the unrolled base exchange to ensure a better cache usage. The default is a subblocking width of 8. |
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logical, | private | :: | adapt_factor_pow2 | = | .false. | Should the oversampling factor be adapted to ensure a power of 2 in the oversampled polynomial? If this is true, the factor will be increased to ensure an oversampled representation with a power of 2. Default is false. |