MFEM v4.7.0
Finite element discretization library
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tmop_pa_h2s_c0.cpp
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1// Copyright (c) 2010-2024, Lawrence Livermore National Security, LLC. Produced
2// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
3// LICENSE and NOTICE for details. LLNL-CODE-806117.
4//
5// This file is part of the MFEM library. For more information and source code
6// availability visit https://mfem.org.
7//
8// MFEM is free software; you can redistribute it and/or modify it under the
9// terms of the BSD-3 license. We welcome feedback and contributions, see file
10// CONTRIBUTING.md for details.
11
12#include "../tmop.hpp"
13#include "tmop_pa.hpp"
14#include "../linearform.hpp"
17
18namespace mfem
19{
20
21MFEM_REGISTER_TMOP_KERNELS(void, SetupGradPA_C0_2D,
22 const real_t lim_normal,
23 const Vector &lim_dist,
24 const Vector &c0_,
25 const int NE,
26 const DenseTensor &j_,
27 const Array<real_t> &w_,
28 const Array<real_t> &b_,
29 const Array<real_t> &bld_,
30 const Vector &x0_,
31 const Vector &x1_,
32 Vector &h0_,
33 const bool exp_lim,
34 const int d1d,
35 const int q1d)
36{
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;
41
42 const bool const_c0 = c0_.Size() == 1;
43 const auto C0 = const_c0 ?
44 Reshape(c0_.Read(), 1, 1, 1) :
45 Reshape(c0_.Read(), Q1D, Q1D, NE);
46 const auto LD = Reshape(lim_dist.Read(), D1D, D1D, NE);
47 const auto J = Reshape(j_.Read(), DIM, DIM, Q1D, Q1D, NE);
48 const auto b = Reshape(b_.Read(), Q1D, D1D);
49 const auto bld = Reshape(bld_.Read(), Q1D, D1D);
50 const auto W = Reshape(w_.Read(), Q1D, Q1D);
51 const auto X0 = Reshape(x0_.Read(), D1D, D1D, DIM, NE);
52 const auto X1 = Reshape(x1_.Read(), D1D, D1D, DIM, NE);
53
54 auto H0 = Reshape(h0_.Write(), DIM, DIM, Q1D, Q1D, NE);
55
56 mfem::forall_2D_batch(NE, Q1D, Q1D, NBZ, [=] MFEM_HOST_DEVICE (int e)
57 {
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;
63
64 MFEM_SHARED real_t B[MQ1*MD1];
65 MFEM_SHARED real_t BLD[MQ1*MD1];
66
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];
70
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];
74
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];
78
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);
82
83 kernels::internal::LoadB<MD1,MQ1>(D1D,Q1D,b,B);
84 kernels::internal::LoadB<MD1,MQ1>(D1D,Q1D,bld,BLD);
85
86 kernels::internal::EvalX<MD1,MQ1,NBZ>(D1D,Q1D,BLD,XY,DQ);
87 kernels::internal::EvalY<MD1,MQ1,NBZ>(D1D,Q1D,BLD,DQ,QQ);
88
89 kernels::internal::EvalX<MD1,MQ1,NBZ>(D1D,Q1D,B,XY0,DQ0);
90 kernels::internal::EvalY<MD1,MQ1,NBZ>(D1D,Q1D,B,DQ0,QQ0);
91
92 kernels::internal::EvalX<MD1,MQ1,NBZ>(D1D,Q1D,B,XY1,DQ1);
93 kernels::internal::EvalY<MD1,MQ1,NBZ>(D1D,Q1D,B,DQ1,QQ1);
94
95 MFEM_FOREACH_THREAD(qy,y,Q1D)
96 {
97 MFEM_FOREACH_THREAD(qx,x,Q1D)
98 {
99 const real_t *Jtr = &J(0,0,qx,qy,e);
100 const real_t detJtr = kernels::Det<2>(Jtr);
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;
104
105 real_t D, p0[2], p1[2];
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);
109
110 const real_t dist = D; // GetValues, default comp set to 0
111
112 // lim_func->Eval_d2(p1, p0, d_vals(q), grad_grad);
113 real_t grad_grad[4];
114
115 if (!exp_lim)
116 {
117 // d2.Diag(1.0 / (dist * dist), x.Size());
118 const real_t c = 1.0 / (dist * dist);
119 kernels::Diag<2>(c, grad_grad);
120 }
121 else
122 {
123 real_t tmp[2];
124 kernels::Subtract<2>(1.0, p1, p0, tmp);
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);
135 }
136 ConstDeviceMatrix gg(grad_grad,DIM,DIM);
137
138 for (int i = 0; i < DIM; i++)
139 {
140 for (int j = 0; j < DIM; j++)
141 {
142 H0(i,j,qx,qy,e) = weight_m * gg(i,j);
143 }
144 }
145 }
146 }
147 });
148}
149
151{
152 MFEM_CONTRACT_VAR(X);
153 const int N = PA.ne;
154 const int D1D = PA.maps_lim->ndof;
155 const int Q1D = PA.maps_lim->nqpt;
156 const int id = (D1D << 4 ) | Q1D;
157 const real_t ln = lim_normal;
158 const Vector &LD = PA.LD;
159 const DenseTensor &J = PA.Jtr;
160 const Array<real_t> &W = PA.ir->GetWeights();
161 const Array<real_t> &B = PA.maps->B;
162 const Array<real_t> &BLD = PA.maps_lim->B;
163 const Vector &C0 = PA.C0;
164 const Vector &X0 = PA.X0;
165 Vector &H0 = PA.H0;
166
167 auto el = dynamic_cast<TMOP_ExponentialLimiter *>(lim_func);
168 const bool exp_lim = (el) ? true : false;
169
170 MFEM_LAUNCH_TMOP_KERNEL(SetupGradPA_C0_2D,id,ln,LD,C0,N,J,W,B,BLD,X0,X,H0,
171 exp_lim);
172}
173
174} // namespace mfem
const T * Read(bool on_dev=true) const
Shortcut for mfem::Read(a.GetMemory(), a.Size(), on_dev).
Definition array.hpp:317
Rank 3 tensor (array of matrices)
const real_t * Read(bool on_dev=true) const
Shortcut for mfem::Read( GetMemory(), TotalSize(), on_dev).
A basic generic Tensor class, appropriate for use on the GPU.
Definition dtensor.hpp:82
Exponential limiter function in TMOP_Integrator.
Definition tmop.hpp:1224
TMOP_LimiterFunction * lim_func
Definition tmop.hpp:1765
void AssembleGradPA_C0_2D(const Vector &) const
struct mfem::TMOP_Integrator::@23 PA
Vector data type.
Definition vector.hpp:80
virtual const real_t * Read(bool on_dev=true) const
Shortcut for mfem::Read(vec.GetMemory(), vec.Size(), on_dev).
Definition vector.hpp:474
int Size() const
Returns the size of the vector.
Definition vector.hpp:218
virtual real_t * Write(bool on_dev=true)
Shortcut for mfem::Write(vec.GetMemory(), vec.Size(), on_dev).
Definition vector.hpp:482
real_t b
Definition lissajous.cpp:42
constexpr int DIM
MFEM_HOST_DEVICE real_t DistanceSquared(const real_t *x, const real_t *y)
Compute the square of the Euclidean distance to another vector.
Definition kernels.hpp:40
MFEM_HOST_DEVICE void Diag(const real_t c, real_t *data)
Creates n x n diagonal matrix with diagonal elements c.
Definition kernels.hpp:49
MFEM_HOST_DEVICE T Det(const T *data)
Compute the determinant of a square matrix of size dim with given data.
Definition kernels.hpp:237
MFEM_HOST_DEVICE void Subtract(const real_t a, const real_t *x, const real_t *y, real_t *z)
Vector subtraction operation: z = a * (x - y)
Definition kernels.hpp:58
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.
Definition dtensor.hpp:131
void forall_2D_batch(int N, int X, int Y, int BZ, lambda &&body)
Definition forall.hpp:769
float real_t
Definition config.hpp:43
std::function< real_t(const Vector &)> f(real_t mass_coeff)
Definition lor_mms.hpp:30