|
From: Ralph S. <ori...@we...> - 2013-04-21 11:28:30
|
Hi Peter, yes, either you define QL_NO_UBLAS_SUPPORT or you implement toMatrixDecomp() as you described it. Providing toMatrixDecomp() has the advantage that it delivers the components for toMatrix() of FdmLinearOp and in this way you get a matrix representation of the P(I)DE as a SparseMatrix, such that you can e. g. directly invert it in order to solve it. This was e.g. used by Klaus Spanderen in his GPU example http://hpcquantlib.wordpress.com/2012/12/27/multi-dimensional-finite-difference-methods-on-a-gpu/ where the QuantLib fdm framework was brought on the GPU via the toMatrix() interface and the CUDA cuSPARSE library. Furthermore, you can use the matrix representation to precondition the finite difference solution. Best regards Ralph Am 20.04.2013 um 20:25 schrieb Peter Caspers: > Hi, > > when updating to the current trunk I notice that my operators do not > compile any more due to an extended interface of FdmLinearOpComposite. > Seems I have to implement > > virtual Disposable<std::vector<SparseMatrix> > toMatrixDecomp() const=0; > > and looking at other operators I think I should return a vector of > SparseMatrix'es corresponding to > > apply_direction(0,...) > apply_direction(1,...) > ... > apply_direction(n,...) > apply_mixed(...) > > , yes ? What is the improvement when using UBLAS ? Sorry in case I > overlooked any documentation on this. > > thank you > Peter > > > > > > ------------------------------------------------------------------------------ > Precog is a next-generation analytics platform capable of advanced > analytics on semi-structured data. The platform includes APIs for building > apps and a phenomenal toolset for data science. Developers can use > our toolset for easy data analysis & visualization. Get a free account! > http://www2.precog.com/precogplatform/slashdotnewsletter > _______________________________________________ > QuantLib-dev mailing list > Qua...@li... > https://lists.sourceforge.net/lists/listinfo/quantlib-dev |