I am not using Strassen for (Dyadic) Dense matrices. However, if the matrix dimensions are not dyadic, then Strassen cannot be natively used. What folks suggest is to zero pad the data and then employ Strassen's algorithm. The second link that I shared, described an optimal way to using the Zero padded data. What this would mean for regular matrices is that some of the sub-matrices would become Dense matrix matrix products while others may become sparse matrix/dense matrix products. Thanks and Regards Sumit From: Karl Rupp <r...@iue.tuwien.ac.at> To: Sumit Kumar <dost_4_e...@yahoo.com> Cc: "viennacl-devel@lists.sourceforge.net" <viennacl-devel@lists.sourceforge.net> Sent: Wednesday, July 29, 2015 2:44 PM Subject: Re: [ViennaCL-devel] ViennaCL reductions Hi Sumit,
> ViennaCL: Sparse Matrix-Matrix Multiplication > <http://www.iue.tuwien.ac.at/cse/index.php/gsoc/2014/ideas/167-viennacl-sparse-matrix-matrix-multiplication-2.html> > Description > View on www.iue.tuwien.ac.at > <http://www.iue.tuwien.ac.at/cse/index.php/gsoc/2014/ideas/167-viennacl-sparse-matrix-matrix-multiplication-2.html> > > Do you have any example in ViennaCL that actually does this? Can you > please point this out? I was rethinking my strategy and was wondering if > I formulate my Dense matrix multiplication as a sparse matrix > multiplication and, 1.7.0 will provide a sparse matrix-matrix product for compressed_matrix<>. Some code for the nightly tests is in tests/src/sparse_prod.cpp The API is the same as for dense matrices: A = viennacl::linalg::prod(B, C); for A, B, and C being of type compressed_matrix<T>. > a.) Use The modified Strassen algorithm to reduce the workload > Strassen's Matrix Multiplication Relabeled > <http://src.acm.org/loos/loos.html> I don't understand what you are trying to achieve with Strassen for sparse matrices. Strassen is (sometimes) useful for dense matrices, but not for sparse matrices. The algorithmic complexities involved in sparse and dense matrix-matrix multiplications are totally different. Best regards, Karli
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