diff options
| -rw-r--r-- | Eigen/src/SparseCore/ConservativeSparseSparseProduct.h | 18 |
1 files changed, 10 insertions, 8 deletions
diff --git a/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h b/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h index 608044a95..8067565f9 100644 --- a/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h +++ b/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h @@ -24,10 +24,10 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r Index rows = lhs.innerSize(); Index cols = rhs.outerSize(); eigen_assert(lhs.outerSize() == rhs.innerSize()); - - std::vector<bool> mask(rows,false); - Matrix<Scalar,Dynamic,1> values(rows); - Matrix<Index,Dynamic,1> indices(rows); + + ei_declare_aligned_stack_constructed_variable(bool, mask, rows, 0); + ei_declare_aligned_stack_constructed_variable(Scalar, values, rows, 0); + ei_declare_aligned_stack_constructed_variable(Index, indices, rows, 0); // estimate the number of non zero entries // given a rhs column containing Y non zeros, we assume that the respective Y columns @@ -77,7 +77,7 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r else { // alternative ordered insertion code: - const Index t200 = rows/(log2(200)*1.39); + const Index t200 = rows/11; // 11 == (log2(200)*1.39) const Index t = (rows*100)/139; // FIXME reserve nnz non zeros @@ -88,7 +88,7 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r // result is clearly very sparse we use a linear bound up to 200. if((nnz<200 && nnz<t200) || nnz * log2(nnz) < t) { - if(nnz>1) std::sort(indices.data(),indices.data()+nnz); + if(nnz>1) std::sort(indices,indices+nnz); for(Index k=0; k<nnz; ++k) { Index i = indices[k]; @@ -133,14 +133,16 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,C static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::Index> RowMajorMatrix; - typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrix; + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrixAux; + typedef typename sparse_eval<ColMajorMatrixAux,ResultType::RowsAtCompileTime,ResultType::ColsAtCompileTime>::type ColMajorMatrix; + ColMajorMatrix resCol(lhs.rows(),rhs.cols()); // FIXME, the following heuristic is probably not very good. if(lhs.rows()>=rhs.cols()) { // perform sorted insertion internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol, true); - res = resCol; + res.swap(resCol); } else { |