22using Args = kernels::InvariantsEvaluator2D::Buffers;
 
   24static MFEM_HOST_DEVICE 
inline 
   27   kernels::InvariantsEvaluator2D ie(
Args().J(Jpt));
 
   31static MFEM_HOST_DEVICE 
inline 
   34   kernels::InvariantsEvaluator2D ie(
Args().J(Jpt));
 
   35   return 0.5 * ie.Get_I1b() - 1.0;
 
   38static MFEM_HOST_DEVICE 
inline 
   41   kernels::InvariantsEvaluator2D ie(
Args().J(Jpt));
 
   42   return ie.Get_I1() * (1.0 + 1.0/ie.Get_I2()) - 4.0;
 
   46static MFEM_HOST_DEVICE 
inline 
   49   kernels::InvariantsEvaluator2D ie(
Args().J(Jpt));
 
   50   const real_t I2b = ie.Get_I2b();
 
   51   return 0.5*(I2b + 1.0/I2b) - 1.0;
 
   54static MFEM_HOST_DEVICE 
inline 
   57   kernels::InvariantsEvaluator2D ie(
Args().J(Jpt));
 
   58   const real_t I2b = ie.Get_I2b();
 
   59   return 0.5*(I2b*I2b + 1./(I2b*I2b) - 2.);
 
   62static MFEM_HOST_DEVICE 
inline 
   65   return w[0] * EvalW_002(Jpt) + w[1] * EvalW_077(Jpt);
 
   68static MFEM_HOST_DEVICE 
inline 
   71   return w[0] * EvalW_002(Jpt) + w[1] * EvalW_056(Jpt);
 
   75                           const real_t metric_normal,
 
   90   MFEM_VERIFY(mid == 1 || mid == 2 || mid == 7 || mid == 77
 
   91               || mid == 80 || mid == 94,
 
   92               "2D metric not yet implemented!");
 
   94   const bool const_m0 = mc_.
Size() == 1;
 
   96   constexpr int DIM = 2;
 
   97   constexpr int NBZ = 1;
 
   99   const int D1D = T_D1D ? T_D1D : d1d;
 
  100   const int Q1D = T_Q1D ? T_Q1D : q1d;
 
  102   const auto MC = const_m0 ?
 
  113   const real_t *metric_data = metric_param.
Read();
 
  117      constexpr int NBZ = 1;
 
  118      constexpr int MQ1 = T_Q1D ? T_Q1D : T_MAX;
 
  119      constexpr int MD1 = T_D1D ? T_D1D : T_MAX;
 
  120      const int D1D = T_D1D ? T_D1D : d1d;
 
  121      const int Q1D = T_Q1D ? T_Q1D : q1d;
 
  123      MFEM_SHARED 
real_t BG[2][MQ1*MD1];
 
  124      MFEM_SHARED 
real_t XY[2][NBZ][MD1*MD1];
 
  125      MFEM_SHARED 
real_t DQ[4][NBZ][MD1*MQ1];
 
  126      MFEM_SHARED 
real_t QQ[4][NBZ][MQ1*MQ1];
 
  128      kernels::internal::LoadX<MD1,NBZ>(e,D1D,X,XY);
 
  129      kernels::internal::LoadBG<MD1,MQ1>(D1D,Q1D,
b,g,BG);
 
  131      kernels::internal::GradX<MD1,MQ1,NBZ>(D1D,Q1D,BG,XY,DQ);
 
  132      kernels::internal::GradY<MD1,MQ1,NBZ>(D1D,Q1D,BG,DQ,QQ);
 
  134      MFEM_FOREACH_THREAD(qy,y,Q1D)
 
  136         MFEM_FOREACH_THREAD(qx,x,Q1D)
 
  138            const real_t *Jtr = &J(0,0,qx,qy,e);
 
  140            const real_t m_coef = const_m0 ? MC(0,0,0) : MC(qx,qy,e);
 
  141            const real_t weight = metric_normal * m_coef * W(qx,qy) * detJtr;
 
  149            kernels::internal::PullGrad<MQ1,NBZ>(Q1D,qx,qy,QQ,Jpr);
 
  157               mid ==  1 ? EvalW_001(Jpt) :
 
  158               mid ==  2 ? EvalW_002(Jpt) :
 
  159               mid ==  7 ? EvalW_007(Jpt) :
 
  160               mid == 77 ? EvalW_077(Jpt) :
 
  161               mid == 80 ? EvalW_080(Jpt, metric_data) :
 
  162               mid == 94 ? EvalW_094(Jpt, metric_data) : 0.0;
 
  164            E(qx,qy,e) = weight * EvalW;
 
  168   return energy * ones;
 
 
  175   const int D1D = 
PA.maps->ndof;
 
  176   const int Q1D = 
PA.maps->nqpt;
 
  177   const int id = (D1D << 4 ) | Q1D;
 
  193   MFEM_LAUNCH_TMOP_KERNEL(EnergyPA_2D,
id,mn,
MC,mp,M,N,J,W,B,G,X,
O,
E);
 
 
const T * Read(bool on_dev=true) const
Shortcut for mfem::Read(a.GetMemory(), a.Size(), on_dev).
Rank 3 tensor (array of matrices)
const real_t * Read(bool on_dev=true) const
Shortcut for mfem::Read( GetMemory(), TotalSize(), on_dev).
TMOP_QualityMetric * metric
real_t GetLocalStateEnergyPA_2D(const Vector &) const
struct mfem::TMOP_Integrator::@26 PA
virtual int Id() const
Return the metric ID.
virtual const real_t * Read(bool on_dev=true) const
Shortcut for mfem::Read(vec.GetMemory(), vec.Size(), on_dev).
int Size() const
Returns the size of the vector.
virtual real_t * Write(bool on_dev=true)
Shortcut for mfem::Write(vec.GetMemory(), vec.Size(), on_dev).
MFEM_HOST_DEVICE void CalcInverse(const T *data, T *inv_data)
Return the inverse of a matrix with given size and data into the matrix with data inv_data.
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_HOST_DEVICE T Det(const T *data)
Compute the determinant of a square matrix of size dim 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.
void forall_2D_batch(int N, int X, int Y, int BZ, lambda &&body)
kernels::InvariantsEvaluator2D::Buffers Args