12 #include "../tmop.hpp"
14 #include "../linearform.hpp"
15 #include "../../general/forall.hpp"
16 #include "../../linalg/kernels.hpp"
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;
42 MFEM_FORALL_2D(e, NE, Q1D, Q1D, NBZ,
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
double B[MQ1*MD1];
53 MFEM_SHARED
double XY[2][NBZ][MD1*MD1];
54 MFEM_SHARED
double DQ[2][NBZ][MD1*MQ1];
55 MFEM_SHARED
double 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);
97 const int D1D =
PA.maps->ndof;
98 const int Q1D =
PA.maps->nqpt;
99 const int id = (D1D << 4 ) | Q1D;
103 MFEM_LAUNCH_TMOP_KERNEL(AddMultGradPA_Kernel_C0_2D,
id,N,B,H0,R,C);
struct mfem::TMOP_Integrator::@23 PA
void AddMultGradPA_C0_2D(const Vector &, Vector &) const
MFEM_REGISTER_TMOP_KERNELS(void, DatcSize, const int NE, const int ncomp, const int sizeidx, const DenseMatrix &w_, const Array< double > &b_, const Vector &x_, DenseTensor &j_, const int d1d, const int q1d)
const T * Read(bool on_dev=true) const
Shortcut for mfem::Read(a.GetMemory(), a.Size(), on_dev).
A basic generic Tensor class, appropriate for use on the GPU.
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...
virtual double * ReadWrite(bool on_dev=true)
Shortcut for mfem::ReadWrite(vec.GetMemory(), vec.Size(), on_dev).
virtual const double * Read(bool on_dev=true) const
Shortcut for mfem::Read(vec.GetMemory(), vec.Size(), on_dev).
MFEM_HOST_DEVICE DeviceTensor< sizeof...(Dims), T > Reshape(T *ptr, Dims...dims)
Wrap a pointer as a DeviceTensor with automatically deduced template parameters.