From: Martin Kronbichler Date: Wed, 6 Feb 2019 11:53:20 +0000 (+0100) Subject: Avoid underflow in MF::ShapeInfo for very large number of q points. X-Git-Tag: v9.1.0-rc1~354^2~4 X-Git-Url: https://gitweb.dealii.org/cgi-bin/gitweb.cgi?a=commitdiff_plain;h=05d5673e3adf15c9844760ea9561e63b0bb82dcd;p=dealii.git Avoid underflow in MF::ShapeInfo for very large number of q points. --- diff --git a/include/deal.II/matrix_free/shape_info.templates.h b/include/deal.II/matrix_free/shape_info.templates.h index 18ed6fba80..af18d30c80 100644 --- a/include/deal.II/matrix_free/shape_info.templates.h +++ b/include/deal.II/matrix_free/shape_info.templates.h @@ -266,44 +266,51 @@ namespace internal } // get gradient and Hessian transformation matrix for the polynomial - // space associated with the quadrature rule (collocation space) - { - const unsigned int stride = (n_q_points_1d + 1) / 2; - shape_gradients_collocation_eo.resize(n_q_points_1d * stride); - shape_hessians_collocation_eo.resize(n_q_points_1d * stride); - FE_DGQArbitraryNodes<1> fe(quad.get_points()); - for (unsigned int i = 0; i < n_q_points_1d / 2; ++i) - for (unsigned int q = 0; q < stride; ++q) - { - shape_gradients_collocation_eo[i * stride + q] = - 0.5 * - (fe.shape_grad(i, quad.get_points()[q])[0] + - fe.shape_grad(i, quad.get_points()[n_q_points_1d - 1 - q])[0]); - shape_gradients_collocation_eo[(n_q_points_1d - 1 - i) * stride + - q] = - 0.5 * - (fe.shape_grad(i, quad.get_points()[q])[0] - - fe.shape_grad(i, quad.get_points()[n_q_points_1d - 1 - q])[0]); - shape_hessians_collocation_eo[i * stride + q] = - 0.5 * (fe.shape_grad_grad(i, quad.get_points()[q])[0][0] + - fe.shape_grad_grad( - i, quad.get_points()[n_q_points_1d - 1 - q])[0][0]); - shape_hessians_collocation_eo[(n_q_points_1d - 1 - i) * stride + - q] = - 0.5 * (fe.shape_grad_grad(i, quad.get_points()[q])[0][0] - - fe.shape_grad_grad( - i, quad.get_points()[n_q_points_1d - 1 - q])[0][0]); - } - if (n_q_points_1d % 2 == 1) - for (unsigned int q = 0; q < stride; ++q) - { - shape_gradients_collocation_eo[n_q_points_1d / 2 * stride + q] = - fe.shape_grad(n_q_points_1d / 2, quad.get_points()[q])[0]; - shape_hessians_collocation_eo[n_q_points_1d / 2 * stride + q] = - fe.shape_grad_grad(n_q_points_1d / 2, - quad.get_points()[q])[0][0]; - } - } + // space associated with the quadrature rule (collocation space). We + // need to avoid the case with more than a few hundreds of quadrature + // points when the Lagrange polynomials constructed in + // FE_DGQArbitraryNodes underflow. + if (n_q_points_1d < 200) + { + const unsigned int stride = (n_q_points_1d + 1) / 2; + shape_gradients_collocation_eo.resize(n_q_points_1d * stride); + shape_hessians_collocation_eo.resize(n_q_points_1d * stride); + FE_DGQArbitraryNodes<1> fe(quad.get_points()); + for (unsigned int i = 0; i < n_q_points_1d / 2; ++i) + for (unsigned int q = 0; q < stride; ++q) + { + shape_gradients_collocation_eo[i * stride + q] = + 0.5 * + (fe.shape_grad(i, quad.get_points()[q])[0] + + fe.shape_grad(i, + quad.get_points()[n_q_points_1d - 1 - q])[0]); + shape_gradients_collocation_eo[(n_q_points_1d - 1 - i) * + stride + + q] = + 0.5 * + (fe.shape_grad(i, quad.get_points()[q])[0] - + fe.shape_grad(i, + quad.get_points()[n_q_points_1d - 1 - q])[0]); + shape_hessians_collocation_eo[i * stride + q] = + 0.5 * (fe.shape_grad_grad(i, quad.get_points()[q])[0][0] + + fe.shape_grad_grad( + i, quad.get_points()[n_q_points_1d - 1 - q])[0][0]); + shape_hessians_collocation_eo[(n_q_points_1d - 1 - i) * stride + + q] = + 0.5 * (fe.shape_grad_grad(i, quad.get_points()[q])[0][0] - + fe.shape_grad_grad( + i, quad.get_points()[n_q_points_1d - 1 - q])[0][0]); + } + if (n_q_points_1d % 2 == 1) + for (unsigned int q = 0; q < stride; ++q) + { + shape_gradients_collocation_eo[n_q_points_1d / 2 * stride + q] = + fe.shape_grad(n_q_points_1d / 2, quad.get_points()[q])[0]; + shape_hessians_collocation_eo[n_q_points_1d / 2 * stride + q] = + fe.shape_grad_grad(n_q_points_1d / 2, + quad.get_points()[q])[0][0]; + } + } if (element_type == tensor_general && check_1d_shapes_symmetric(n_q_points_1d))