30 constexpr int DIM = 2;
31 constexpr int NBZ = 1;
33 const int D1D = T_D1D ? T_D1D : d1d;
34 const int Q1D = T_Q1D ? T_Q1D : q1d;
44 constexpr int DIM = 2;
45 const int D1D = T_D1D ? T_D1D : d1d;
46 const int Q1D = T_Q1D ? T_Q1D : q1d;
47 constexpr int NBZ = 1;
48 constexpr int MQ1 = T_Q1D ? T_Q1D : T_MAX;
49 constexpr int MD1 = T_D1D ? T_D1D : T_MAX;
51 MFEM_SHARED
real_t B[MQ1*MD1];
53 MFEM_SHARED
real_t XY[2][NBZ][MD1*MD1];
54 MFEM_SHARED
real_t DQ[2][NBZ][MD1*MQ1];
55 MFEM_SHARED
real_t QQ[2][NBZ][MQ1*MQ1];
57 kernels::internal::LoadX<MD1,NBZ>(e,D1D,R,XY);
58 kernels::internal::LoadB<MD1,MQ1>(D1D,Q1D,
b,B);
60 kernels::internal::EvalX<MD1,MQ1,NBZ>(D1D,Q1D,B,XY,DQ);
61 kernels::internal::EvalY<MD1,MQ1,NBZ>(D1D,Q1D,B,DQ,QQ);
63 MFEM_FOREACH_THREAD(qy,y,Q1D)
65 MFEM_FOREACH_THREAD(qx,x,Q1D)
69 kernels::internal::PullEval<MQ1,NBZ>(Q1D,qx,qy,QQ,Xh);
73 for (
int i = 0; i <
DIM; i++)
75 for (
int j = 0; j <
DIM; j++)
77 H(i,j) = H0(i,j,qx,qy,e);
84 kernels::internal::PushEval<MQ1,NBZ>(Q1D,qx,qy,p2,QQ);
88 kernels::internal::LoadBt<MD1,MQ1>(D1D,Q1D,
b,B);
89 kernels::internal::EvalXt<MD1,MQ1,NBZ>(D1D,Q1D,B,QQ,DQ);
90 kernels::internal::EvalYt<MD1,MQ1,NBZ>(D1D,Q1D,B,DQ,Y,e);
MFEM_HOST_DEVICE void Mult(const int height, const int width, const TA *data, const TX *x, TY *y)
Matrix vector multiplication: y = A x, where the matrix A is of size height x width with given data,...
MFEM_REGISTER_TMOP_KERNELS(void, DatcSize, const int NE, const int ncomp, const int sizeidx, const real_t input_min_size, const DenseMatrix &w_, const Array< real_t > &b_, const Vector &x_, const Vector &nc_reduce, DenseTensor &j_, const int d1d, const int q1d)
MFEM_HOST_DEVICE DeviceTensor< sizeof...(Dims), T > Reshape(T *ptr, Dims... dims)
Wrap a pointer as a DeviceTensor with automatically deduced template parameters.