37   constexpr int DIM = 2;
 
   38   constexpr int NBZ = 1;
 
   39   const int D1D = T_D1D ? T_D1D : d1d;
 
   40   const int Q1D = T_Q1D ? T_Q1D : q1d;
 
   42   const bool const_c0 = c0_.
Size() == 1;
 
   43   const auto C0 = const_c0 ?
 
   46   const auto LD = 
Reshape(lim_dist.
Read(), D1D, D1D, NE);
 
   58      const int D1D = T_D1D ? T_D1D : d1d;
 
   59      const int Q1D = T_Q1D ? T_Q1D : q1d;
 
   60      constexpr int NBZ = 1;
 
   61      constexpr int MQ1 = T_Q1D ? T_Q1D : T_MAX;
 
   62      constexpr int MD1 = T_D1D ? T_D1D : T_MAX;
 
   64      MFEM_SHARED 
real_t B[MQ1*MD1];
 
   65      MFEM_SHARED 
real_t BLD[MQ1*MD1];
 
   67      MFEM_SHARED 
real_t XY[NBZ][MD1*MD1];
 
   68      MFEM_SHARED 
real_t DQ[NBZ][MD1*MQ1];
 
   69      MFEM_SHARED 
real_t QQ[NBZ][MQ1*MQ1];
 
   71      MFEM_SHARED 
real_t XY0[2][NBZ][MD1*MD1];
 
   72      MFEM_SHARED 
real_t DQ0[2][NBZ][MD1*MQ1];
 
   73      MFEM_SHARED 
real_t QQ0[2][NBZ][MQ1*MQ1];
 
   75      MFEM_SHARED 
real_t XY1[2][NBZ][MD1*MD1];
 
   76      MFEM_SHARED 
real_t DQ1[2][NBZ][MD1*MQ1];
 
   77      MFEM_SHARED 
real_t QQ1[2][NBZ][MQ1*MQ1];
 
   79      kernels::internal::LoadX<MD1,NBZ>(e,D1D,LD,XY);
 
   80      kernels::internal::LoadX<MD1,NBZ>(e,D1D,X0,XY0);
 
   81      kernels::internal::LoadX<MD1,NBZ>(e,D1D,X1,XY1);
 
   83      kernels::internal::LoadB<MD1,MQ1>(D1D,Q1D,
b,B);
 
   84      kernels::internal::LoadB<MD1,MQ1>(D1D,Q1D,bld,BLD);
 
   86      kernels::internal::EvalX<MD1,MQ1,NBZ>(D1D,Q1D,BLD,XY,DQ);
 
   87      kernels::internal::EvalY<MD1,MQ1,NBZ>(D1D,Q1D,BLD,DQ,QQ);
 
   89      kernels::internal::EvalX<MD1,MQ1,NBZ>(D1D,Q1D,B,XY0,DQ0);
 
   90      kernels::internal::EvalY<MD1,MQ1,NBZ>(D1D,Q1D,B,DQ0,QQ0);
 
   92      kernels::internal::EvalX<MD1,MQ1,NBZ>(D1D,Q1D,B,XY1,DQ1);
 
   93      kernels::internal::EvalY<MD1,MQ1,NBZ>(D1D,Q1D,B,DQ1,QQ1);
 
   95      MFEM_FOREACH_THREAD(qy,y,Q1D)
 
   97         MFEM_FOREACH_THREAD(qx,x,Q1D)
 
   99            const real_t *Jtr = &J(0,0,qx,qy,e);
 
  101            const real_t weight = W(qx,qy) * detJtr;
 
  102            const real_t coeff0 = const_c0 ? C0(0,0,0) : C0(qx,qy,e);
 
  103            const real_t weight_m = weight * lim_normal * coeff0;
 
  106            kernels::internal::PullEval<MQ1,NBZ>(Q1D,qx,qy,QQ,D);
 
  107            kernels::internal::PullEval<MQ1,NBZ>(Q1D,qx,qy,QQ0,p0);
 
  108            kernels::internal::PullEval<MQ1,NBZ>(Q1D,qx,qy,QQ1,p1);
 
  118               const real_t c = 1.0 / (dist * dist);
 
  126               real_t dist_squared = dist*dist;
 
  127               real_t dist_squared_squared = dist_squared*dist_squared;
 
  128               real_t f = exp(10.0*((dsq / dist_squared)-1.0));
 
  129               grad_grad[0] = ((400.0*tmp[0]*tmp[0]*
f)/dist_squared_squared)+
 
  130                              (20.0*
f/dist_squared);
 
  131               grad_grad[1] = (400.0*tmp[0]*tmp[1]*
f)/dist_squared_squared;
 
  132               grad_grad[2] = grad_grad[1];
 
  133               grad_grad[3] = ((400.0*tmp[1]*tmp[1]*
f)/dist_squared_squared)+
 
  134                              (20.0*
f/dist_squared);
 
  138            for (
int i = 0; i < 
DIM; i++)
 
  140               for (
int j = 0; j < 
DIM; j++)
 
  142                  H0(i,j,qx,qy,e) = weight_m * gg(i,j);
 
 
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)