113     Index remainingRows = rows - k;  variable
117     mat.col(k).tail(remainingRows)
120     mat.bottomRightCorner(remainingRows, remainingCols)
121        .applyHouseholderOnTheLeft(mat.col(k).tail(remainingRows-1), mat.coeff(k,k), tempData);
129     mat.bottomRightCorner(remainingRows-1, remainingCols)
178     Index remainingRows = brows - k;  in upperbidiagonalization_blocked_helper()  local
181     SubMatType X_k1( X.block(k,0, remainingRows,k) );  in upperbidiagonalization_blocked_helper()
182     SubMatType V_k1( A.block(k,0, remainingRows,k) );  in upperbidiagonalization_blocked_helper()
185     SubColumnType v_k = A.col(k).tail(remainingRows);  in upperbidiagonalization_blocked_helper()
207         y_k.noalias()  = A.block(k,k+1, remainingRows,remainingCols).adjoint() * v_k; // bottleneck  in upperbidiagonalization_blocked_helper()
232         SubColumnType x_k ( X.col(k).tail(remainingRows-1) );  in upperbidiagonalization_blocked_helper()
239 … x_k.noalias()   = A.block(k+1,k+1, remainingRows-1,remainingCols) * u_k.transpose(); // bottleneck  in upperbidiagonalization_blocked_helper()
241         x_k.noalias()  -= X_k1.bottomRows(remainingRows-1) * tmp0;  in upperbidiagonalization_blocked_helper()
243         x_k.noalias()  -= A.block(k+1,0, remainingRows-1,k+1) * tmp1;  in upperbidiagonalization_blocked_helper()