596 lines
24 KiB
C++
596 lines
24 KiB
C++
// Copyright (c) 2010-2022, Lawrence Livermore National Security, LLC. Produced
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// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
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// LICENSE and NOTICE for details. LLNL-CODE-806117.
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//
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// This file is part of the MFEM library. For more information and source code
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// availability visit https://mfem.org.
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//
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// MFEM is free software; you can redistribute it and/or modify it under the
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// terms of the BSD-3 license. We welcome feedback and contributions, see file
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// CONTRIBUTING.md for details.
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#include "lor_nd.hpp"
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#include "lor_util.hpp"
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#include "../../linalg/dtensor.hpp"
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#include "../../general/forall.hpp"
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namespace mfem
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{
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template <int ORDER>
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void BatchedLOR_ND::Assemble2D()
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{
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const int nel_ho = fes_ho.GetNE();
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static constexpr int nv = 4;
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static constexpr int ne = 4;
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static constexpr int dim = 2;
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static constexpr int ddm2 = (dim*(dim+1))/2;
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static constexpr int ngeom = ddm2 + 1;
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static constexpr int o = ORDER;
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static constexpr int op1 = ORDER + 1;
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static constexpr int ndof_per_el = dim*o*op1;
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static constexpr int nnz_per_row = 7;
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static constexpr int sz_local_mat = ne*ne;
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const bool const_mq = c1.Size() == 1;
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const auto MQ = const_mq
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? Reshape(c1.Read(), 1, 1, 1)
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: Reshape(c1.Read(), op1, op1, nel_ho);
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const bool const_dq = c2.Size() == 1;
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const auto DQ = const_dq
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? Reshape(c2.Read(), 1, 1, 1)
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: Reshape(c2.Read(), op1, op1, nel_ho);
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sparse_ij.SetSize(nnz_per_row*ndof_per_el*nel_ho);
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auto V = Reshape(sparse_ij.Write(), nnz_per_row, o*op1, dim, nel_ho);
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auto X = X_vert.Read();
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MFEM_FORALL_2D(iel_ho, nel_ho, ORDER, ORDER, 1,
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{
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// Assemble a sparse matrix over the macro-element by looping over each
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// subelement.
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// V(j,ix,iy) stores the jth nonzero in the row of the sparse matrix
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// corresponding to local DOF (ix, iy).
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MFEM_FOREACH_THREAD(iy,y,o)
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{
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MFEM_FOREACH_THREAD(ix,x,op1)
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{
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for (int c=0; c<2; ++c)
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{
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for (int j=0; j<nnz_per_row; ++j)
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{
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V(j,ix+iy*op1,c,iel_ho) = 0.0;
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}
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}
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}
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}
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MFEM_SYNC_THREAD;
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// Loop over the sub-elements
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MFEM_FOREACH_THREAD(ky,y,ORDER)
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{
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MFEM_FOREACH_THREAD(kx,x,ORDER)
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{
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// Compute geometric factors at quadrature points
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double Q_[ngeom*nv];
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double local_mat_[sz_local_mat];
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DeviceTensor<3> Q(Q_, ngeom, 2, 2);
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DeviceTensor<2> local_mat(local_mat_, ne, ne);
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// local_mat is the local (dense) stiffness matrix
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for (int i=0; i<sz_local_mat; ++i) { local_mat[i] = 0.0; }
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double vx[4], vy[4];
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LORVertexCoordinates2D<ORDER>(X, iel_ho, kx, ky, vx, vy);
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for (int iqx=0; iqx<2; ++iqx)
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{
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for (int iqy=0; iqy<2; ++iqy)
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{
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const double x = iqx;
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const double y = iqy;
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const double w = 1.0/4.0;
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double J_[2*2];
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DeviceTensor<2> J(J_, 2, 2);
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Jacobian2D(x, y, vx, vy, J);
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const double detJ = Det2D(J);
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const double w_detJ = w/detJ;
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Q(0,iqy,iqx) = w_detJ * (J(0,1)*J(0,1) + J(1,1)*J(1,1)); // 1,1
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Q(1,iqy,iqx) = -w_detJ * (J(0,1)*J(0,0) + J(1,1)*J(1,0)); // 1,2
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Q(2,iqy,iqx) = w_detJ * (J(0,0)*J(0,0) + J(1,0)*J(1,0)); // 2,2
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Q(3,iqy,iqx) = w_detJ;
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}
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}
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for (int iqx=0; iqx<2; ++iqx)
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{
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for (int iqy=0; iqy<2; ++iqy)
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{
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const double mq = const_mq ? MQ(0,0,0) : MQ(kx+iqx, ky+iqy, iel_ho);
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const double dq = const_dq ? DQ(0,0,0) : DQ(kx+iqx, ky+iqy, iel_ho);
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// Loop over x,y components. c=0 => x, c=1 => y
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for (int cj=0; cj<dim; ++cj)
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{
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for (int bj=0; bj<2; ++bj)
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{
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const double curl_j = ((cj == 0) ? 1 : -1)*((bj == 0) ? 1 : -1);
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const double bxj = (cj == 0) ? ((bj == iqy) ? 1 : 0) : 0;
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const double byj = (cj == 1) ? ((bj == iqx) ? 1 : 0) : 0;
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const double jj_loc = bj + 2*cj;
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for (int ci=0; ci<dim; ++ci)
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{
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for (int bi=0; bi<2; ++bi)
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{
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const double curl_i = ((ci == 0) ? 1 : -1)*((bi == 0) ? 1 : -1);
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const double bxi = (ci == 0) ? ((bi == iqy) ? 1 : 0) : 0;
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const double byi = (ci == 1) ? ((bi == iqx) ? 1 : 0) : 0;
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const double ii_loc = bi + 2*ci;
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// Only store the lower-triangular part of
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// the matrix (by symmetry).
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if (jj_loc > ii_loc) { continue; }
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double val = 0.0;
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val += bxi*bxj*Q(0,iqy,iqx);
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val += byi*bxj*Q(1,iqy,iqx);
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val += bxi*byj*Q(1,iqy,iqx);
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val += byi*byj*Q(2,iqy,iqx);
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val *= mq;
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val += dq*curl_i*curl_j*Q(3,iqy,iqx);
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local_mat(ii_loc, jj_loc) += val;
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}
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}
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}
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}
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}
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}
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// Assemble the local matrix into the macro-element sparse matrix
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// in a format similar to coordinate format. The (I,J) arrays
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// are implicit (not stored explicitly).
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for (int ii_loc=0; ii_loc<ne; ++ii_loc)
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{
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const int ci = ii_loc/2;
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const int bi = ii_loc%2;
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const int ix = (ci == 0) ? 0 : bi;
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const int iy = (ci == 1) ? 0 : bi;
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int ii = (ci == 0) ? kx+ix + (ky+iy)*o : kx+ix + (ky+iy)*op1;
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for (int jj_loc=0; jj_loc<ne; ++jj_loc)
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{
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const int cj = jj_loc/2;
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const int bj = jj_loc%2;
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const int jj_off = (ci == cj) ? (bj - bi + 1) : (3 + bj + (1-bi)*2);
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// Symmetry
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const double val = (jj_loc <= ii_loc)
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? local_mat(ii_loc, jj_loc)
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: local_mat(jj_loc, ii_loc);
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AtomicAdd(V(jj_off, ii, ci, iel_ho), val);
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}
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}
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}
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}
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});
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sparse_mapping.SetSize(nnz_per_row*ndof_per_el);
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sparse_mapping = -1;
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auto map = Reshape(sparse_mapping.HostReadWrite(), nnz_per_row, ndof_per_el);
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for (int ci=0; ci<2; ++ci)
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{
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for (int i1=0; i1<o; ++i1)
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{
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for (int i2=0; i2<op1; ++i2)
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{
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const int ii_el = (ci == 0) ? i1 + i2*o : i2 + i1*op1 + o*op1;
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for (int cj=0; cj<2; ++cj)
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{
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const int j1_begin = (ci == cj) ? i1 : ((i2 > 0) ? i2-1 : i2);
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const int j1_end = (ci == cj) ? i1 : ((i2 < o) ? i2 : i2-1);
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const int j2_begin = (ci == cj) ? ((i2 > 0) ? i2-1 : i2) : i1;
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const int j2_end = (ci == cj) ? ((i2 < o) ? i2+1 : i2) : i1+1;
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for (int j1=j1_begin; j1<=j1_end; ++j1)
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{
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for (int j2=j2_begin; j2<=j2_end; ++j2)
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{
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const int jj_el = (cj == 0) ? j1 + j2*o : j2 + j1*op1 + o*op1;
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int jj_off = (ci == cj) ? (j2-i2+1) : 3 + (j2-i1) + 2*(j1-i2+1);
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map(jj_off, ii_el) = jj_el;
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}
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}
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}
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}
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}
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}
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}
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template <int ORDER>
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void BatchedLOR_ND::Assemble3D()
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{
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const int nel_ho = fes_ho.GetNE();
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static constexpr int nv = 8; // number of vertices in hexahedron
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static constexpr int ne = 12; // number of edges in hexahedron
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static constexpr int dim = 3;
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static constexpr int ddm2 = (dim*(dim+1))/2;
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static constexpr int ngeom = 2*ddm2; // number of geometric factors stored
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static constexpr int o = ORDER;
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static constexpr int op1 = ORDER + 1;
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static constexpr int ndof_per_el = dim*o*op1*op1;
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static constexpr int nnz_per_row = 33;
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static constexpr int sz_local_mat = ne*ne;
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const bool const_mq = c1.Size() == 1;
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const auto MQ = const_mq
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? Reshape(c1.Read(), 1, 1, 1, 1)
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: Reshape(c1.Read(), op1, op1, op1, nel_ho);
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const bool const_dq = c2.Size() == 1;
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const auto DQ = const_dq
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? Reshape(c2.Read(), 1, 1, 1, 1)
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: Reshape(c2.Read(), op1, op1, op1, nel_ho);
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sparse_ij.SetSize(nnz_per_row*ndof_per_el*nel_ho);
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auto V = Reshape(sparse_ij.Write(), nnz_per_row, o*op1*op1, dim, nel_ho);
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auto X = X_vert.Read();
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// Last thread dimension is lowered to avoid "too many resources" error
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MFEM_FORALL_3D(iel_ho, nel_ho, ORDER, ORDER, (ORDER>6)?4:ORDER,
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{
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MFEM_FOREACH_THREAD(iz,z,o)
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{
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MFEM_FOREACH_THREAD(iy,y,op1)
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{
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MFEM_FOREACH_THREAD(ix,x,op1)
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{
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for (int c=0; c<dim; ++c)
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{
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for (int j=0; j<nnz_per_row; ++j)
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{
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V(j,ix+iy*op1+iz*op1*op1,c,iel_ho) = 0.0;
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}
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}
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}
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}
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}
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MFEM_SYNC_THREAD;
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// Loop over the sub-elements
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MFEM_FOREACH_THREAD(kz,z,ORDER)
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{
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MFEM_FOREACH_THREAD(ky,y,ORDER)
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{
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MFEM_FOREACH_THREAD(kx,x,ORDER)
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{
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// Geometric factors at quadrature points (element vertices)
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double Q_[ngeom*nv];
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DeviceTensor<4> Q(Q_, ngeom, 2, 2, 2);
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double local_mat_[sz_local_mat];
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DeviceTensor<2> local_mat(local_mat_, ne, ne);
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for (int i=0; i<sz_local_mat; ++i) { local_mat[i] = 0.0; }
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double vx[8], vy[8], vz[8];
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LORVertexCoordinates3D<ORDER>(X, iel_ho, kx, ky, kz, vx, vy, vz);
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for (int iqz=0; iqz<2; ++iqz)
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{
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for (int iqy=0; iqy<2; ++iqy)
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{
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for (int iqx=0; iqx<2; ++iqx)
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{
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const double x = iqx;
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const double y = iqy;
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const double z = iqz;
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const double w = 1.0/8.0;
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double J_[3*3];
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DeviceTensor<2> J(J_, 3, 3);
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Jacobian3D(x, y, z, vx, vy, vz, J);
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const double detJ = Det3D(J);
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const double w_detJ = w/detJ;
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// adj(J)
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double A_[3*3];
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DeviceTensor<2> A(A_, 3, 3);
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Adjugate3D(J, A);
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Q(0,iqz,iqy,iqx) = w_detJ*(A(0,0)*A(0,0)+A(0,1)*A(0,1)+A(0,2)*A(0,2)); // 1,1
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Q(1,iqz,iqy,iqx) = w_detJ*(A(0,0)*A(1,0)+A(0,1)*A(1,1)+A(0,2)*A(1,2)); // 2,1
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Q(2,iqz,iqy,iqx) = w_detJ*(A(0,0)*A(2,0)+A(0,1)*A(2,1)+A(0,2)*A(2,2)); // 3,1
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Q(3,iqz,iqy,iqx) = w_detJ*(A(1,0)*A(1,0)+A(1,1)*A(1,1)+A(1,2)*A(1,2)); // 2,2
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Q(4,iqz,iqy,iqx) = w_detJ*(A(1,0)*A(2,0)+A(1,1)*A(2,1)+A(1,2)*A(2,2)); // 3,2
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Q(5,iqz,iqy,iqx) = w_detJ*(A(2,0)*A(2,0)+A(2,1)*A(2,1)+A(2,2)*A(2,2)); // 3,3
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// w J^T J / det(J)
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Q(6,iqz,iqy,iqx) = w_detJ*(J(0,0)*J(0,0)+J(1,0)*J(1,0)+J(2,0)*J(2,0)); // 1,1
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Q(7,iqz,iqy,iqx) = w_detJ*(J(0,0)*J(0,1)+J(1,0)*J(1,1)+J(2,0)*J(2,1)); // 2,1
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Q(8,iqz,iqy,iqx) = w_detJ*(J(0,0)*J(0,2)+J(1,0)*J(1,2)+J(2,0)*J(2,2)); // 3,1
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Q(9,iqz,iqy,iqx) = w_detJ*(J(0,1)*J(0,1)+J(1,1)*J(1,1)+J(2,1)*J(2,1)); // 2,2
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Q(10,iqz,iqy,iqx) = w_detJ*(J(0,1)*J(0,2)+J(1,1)*J(1,2)+J(2,1)*J(2,2)); // 3,2
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Q(11,iqz,iqy,iqx) = w_detJ*(J(0,2)*J(0,2)+J(1,2)*J(1,2)+J(2,2)*J(2,2)); // 3,3
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}
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}
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}
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for (int iqz=0; iqz<2; ++iqz)
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{
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for (int iqy=0; iqy<2; ++iqy)
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{
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for (int iqx=0; iqx<2; ++iqx)
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{
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const double mq = const_mq ? MQ(0,0,0,0) : MQ(kx+iqx, ky+iqy, kz+iqz, iel_ho);
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const double dq = const_dq ? DQ(0,0,0,0) : DQ(kx+iqx, ky+iqy, kz+iqz, iel_ho);
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// Loop over x,y,z components. 0 => x, 1 => y, 2 => z
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for (int cj=0; cj<dim; ++cj)
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{
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const double jq1 = (cj == 0) ? iqy : ((cj == 1) ? iqz : iqx);
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const double jq2 = (cj == 0) ? iqz : ((cj == 1) ? iqx : iqy);
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const int jd_0 = cj;
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const int jd_1 = (cj + 1)%3;
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const int jd_2 = (cj + 2)%3;
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for (int bj=0; bj<4; ++bj) // 4 edges in each dim
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{
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const int bj1 = bj%2;
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const int bj2 = bj/2;
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double curl_j[3];
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curl_j[jd_0] = 0.0;
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curl_j[jd_1] = ((bj1 == 0) ? jq1 - 1 : -jq1)*((bj2 == 0) ? 1 : -1);
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curl_j[jd_2] = ((bj2 == 0) ? 1 - jq2 : jq2)*((bj1 == 0) ? 1 : -1);
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double basis_j[3];
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basis_j[jd_0] = ((bj1 == 0) ? 1 - jq1 : jq1)*((bj2 == 0) ? 1 - jq2 : jq2);
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basis_j[jd_1] = 0.0;
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basis_j[jd_2] = 0.0;
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const int jj_loc = bj + 4*cj;
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for (int ci=0; ci<dim; ++ci)
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{
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const double iq1 = (ci == 0) ? iqy : ((ci == 1) ? iqz : iqx);
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const double iq2 = (ci == 0) ? iqz : ((ci == 1) ? iqx : iqy);
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const int id_0 = ci;
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const int id_1 = (ci + 1)%3;
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const int id_2 = (ci + 2)%3;
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for (int bi=0; bi<4; ++bi)
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{
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const int bi1 = bi%2;
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const int bi2 = bi/2;
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double curl_i[3];
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curl_i[id_0] = 0.0;
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curl_i[id_1] = ((bi1 == 0) ? iq1 - 1 : -iq1)*((bi2 == 0) ? 1 : -1);
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curl_i[id_2] = ((bi2 == 0) ? 1 - iq2 : iq2)*((bi1 == 0) ? 1 : -1);
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double basis_i[3];
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basis_i[id_0] = ((bi1 == 0) ? 1 - iq1 : iq1)*((bi2 == 0) ? 1 - iq2 : iq2);
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basis_i[id_1] = 0.0;
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basis_i[id_2] = 0.0;
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const int ii_loc = bi + 4*ci;
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// Only store the lower-triangular part of
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// the matrix (by symmetry).
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if (jj_loc > ii_loc) { continue; }
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double curl_curl = 0.0;
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curl_curl += Q(6,iqz,iqy,iqx)*curl_i[0]*curl_j[0];
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curl_curl += Q(7,iqz,iqy,iqx)*(curl_i[0]*curl_j[1] + curl_i[1]*curl_j[0]);
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curl_curl += Q(8,iqz,iqy,iqx)*(curl_i[0]*curl_j[2] + curl_i[2]*curl_j[0]);
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curl_curl += Q(9,iqz,iqy,iqx)*curl_i[1]*curl_j[1];
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curl_curl += Q(10,iqz,iqy,iqx)*(curl_i[1]*curl_j[2] + curl_i[2]*curl_j[1]);
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curl_curl += Q(11,iqz,iqy,iqx)*curl_i[2]*curl_j[2];
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|
|
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double basis_basis = 0.0;
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basis_basis += Q(0,iqz,iqy,iqx)*basis_i[0]*basis_j[0];
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basis_basis += Q(1,iqz,iqy,iqx)*(basis_i[0]*basis_j[1] + basis_i[1]*basis_j[0]);
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basis_basis += Q(2,iqz,iqy,iqx)*(basis_i[0]*basis_j[2] + basis_i[2]*basis_j[0]);
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basis_basis += Q(3,iqz,iqy,iqx)*basis_i[1]*basis_j[1];
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basis_basis += Q(4,iqz,iqy,iqx)*(basis_i[1]*basis_j[2] + basis_i[2]*basis_j[1]);
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basis_basis += Q(5,iqz,iqy,iqx)*basis_i[2]*basis_j[2];
|
|
|
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const double val = dq*curl_curl + mq*basis_basis;
|
|
|
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local_mat(ii_loc, jj_loc) += val;
|
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}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
// Assemble the local matrix into the macro-element sparse matrix
|
|
// The nonzeros of the macro-element sparse matrix are ordered as
|
|
// follows:
|
|
//
|
|
// The axes are ordered relative to the direction of the basis
|
|
// vector, e.g. for x-vectors, the axes are (x,y,z), for
|
|
// y-vectors the axes are (y,z,x), and for z-vectors the axes are
|
|
// (z,x,y).
|
|
//
|
|
// The nonzeros are then given in "rotated lexicographic"
|
|
// ordering, according to these axes.
|
|
for (int ii_loc=0; ii_loc<ne; ++ii_loc)
|
|
{
|
|
const int ci = ii_loc/4;
|
|
const int bi = ii_loc%4;
|
|
|
|
const int id0 = ci;
|
|
const int id1 = (ci+1)%3;
|
|
const int id2 = (ci+2)%3;
|
|
|
|
const int i0 = 0;
|
|
const int i1 = bi%2;
|
|
const int i2 = bi/2;
|
|
|
|
int ii_lex[3];
|
|
ii_lex[id0] = i0;
|
|
ii_lex[id1] = i1;
|
|
ii_lex[id2] = i2;
|
|
|
|
const int nx = (ci == 0) ? o : op1;
|
|
const int ny = (ci == 1) ? o : op1;
|
|
|
|
const int ii = kx+ii_lex[0] + (ky+ii_lex[1])*nx + (kz+ii_lex[2])*nx*ny;
|
|
|
|
for (int jj_loc=0; jj_loc<ne; ++jj_loc)
|
|
{
|
|
const int cj = jj_loc/4;
|
|
// add 3 to take modulus (rather than remainder) when
|
|
// (cj - ci) is negative
|
|
const int cj_rel = (3 + cj - ci)%3;
|
|
|
|
const int bj = jj_loc%4;
|
|
|
|
const int jd0 = cj_rel;
|
|
const int jd1 = (cj_rel+1)%3;
|
|
const int jd2 = (cj_rel+2)%3;
|
|
|
|
int jj_rel[3];
|
|
jj_rel[jd0] = 0;
|
|
jj_rel[jd1] = bj%2;
|
|
jj_rel[jd2] = bj/2;
|
|
|
|
const int d0 = jj_rel[0] - i0;
|
|
const int d1 = 1 + jj_rel[1] - i1;
|
|
const int d2 = 1 + jj_rel[2] - i2;
|
|
int jj_off;
|
|
if (cj_rel == 0) { jj_off = d1 + 3*d2; }
|
|
else if (cj_rel == 1) { jj_off = 9 + d0 + 2*d1 + 4*d2; }
|
|
else /* if (cj_rel == 2) */ { jj_off = 21 + d0 + 2*d1 + 6*d2; }
|
|
|
|
// Symmetry
|
|
const double val = (jj_loc <= ii_loc)
|
|
? local_mat(ii_loc, jj_loc)
|
|
: local_mat(jj_loc, ii_loc);
|
|
AtomicAdd(V(jj_off, ii, ci, iel_ho), val);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
});
|
|
|
|
sparse_mapping.SetSize(nnz_per_row*ndof_per_el);
|
|
sparse_mapping = -1;
|
|
auto map = Reshape(sparse_mapping.HostReadWrite(), nnz_per_row, ndof_per_el);
|
|
for (int ci=0; ci<dim; ++ci)
|
|
{
|
|
const int i_off = ci*o*op1*op1;
|
|
const int id0 = ci;
|
|
const int id1 = (ci+1)%3;
|
|
const int id2 = (ci+2)%3;
|
|
|
|
const int nxi = (ci == 0) ? o : op1;
|
|
const int nyi = (ci == 1) ? o : op1;
|
|
|
|
for (int i0=0; i0<o; ++i0)
|
|
{
|
|
for (int i1=0; i1<op1; ++i1)
|
|
{
|
|
for (int i2=0; i2<op1; ++i2)
|
|
{
|
|
int ii_lex[3];
|
|
ii_lex[id0] = i0;
|
|
ii_lex[id1] = i1;
|
|
ii_lex[id2] = i2;
|
|
const int ii_el = i_off + ii_lex[0] + ii_lex[1]*nxi + ii_lex[2]*nxi*nyi;
|
|
|
|
for (int cj_rel=0; cj_rel<dim; ++cj_rel)
|
|
{
|
|
const int cj = (ci + cj_rel) % 3;
|
|
const int j_off = cj*o*op1*op1;
|
|
|
|
const int nxj = (cj == 0) ? o : op1;
|
|
const int nyj = (cj == 1) ? o : op1;
|
|
|
|
const int j0_begin = i0;
|
|
const int j0_end = (cj_rel == 0) ? i0 : i0 + 1;
|
|
const int j1_begin = (i1 > 0) ? i1-1 : i1;
|
|
const int j1_end = (cj_rel == 1)
|
|
? ((i1 < o) ? i1 : i1-1)
|
|
: ((i1 < o) ? i1+1 : i1);
|
|
const int j2_begin = (i2 > 0) ? i2-1 : i2;
|
|
const int j2_end = (cj_rel == 2)
|
|
? ((i2 < o) ? i2 : i2-1)
|
|
: ((i2 < o) ? i2+1 : i2);
|
|
|
|
for (int j0=j0_begin; j0<=j0_end; ++j0)
|
|
{
|
|
const int d0 = j0 - i0;
|
|
for (int j1=j1_begin; j1<=j1_end; ++j1)
|
|
{
|
|
const int d1 = j1 - i1 + 1;
|
|
for (int j2=j2_begin; j2<=j2_end; ++j2)
|
|
{
|
|
const int d2 = j2 - i2 + 1;
|
|
int jj_lex[3];
|
|
jj_lex[id0] = j0;
|
|
jj_lex[id1] = j1;
|
|
jj_lex[id2] = j2;
|
|
const int jj_el = j_off + jj_lex[0] + jj_lex[1]*nxj + jj_lex[2]*nxj*nyj;
|
|
int jj_off;
|
|
if (cj_rel == 0) { jj_off = d1 + 3*d2; }
|
|
else if (cj_rel == 1) { jj_off = 9 + d0 + 2*d1 + 4*d2; }
|
|
else /* if (cj_rel == 2) */ { jj_off = 21 + d0 + 2*d1 + 6*d2; }
|
|
map(jj_off, ii_el) = jj_el;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// Explicit template instantiations
|
|
template void BatchedLOR_ND::Assemble2D<1>();
|
|
template void BatchedLOR_ND::Assemble2D<2>();
|
|
template void BatchedLOR_ND::Assemble2D<3>();
|
|
template void BatchedLOR_ND::Assemble2D<4>();
|
|
template void BatchedLOR_ND::Assemble2D<5>();
|
|
template void BatchedLOR_ND::Assemble2D<6>();
|
|
template void BatchedLOR_ND::Assemble2D<7>();
|
|
template void BatchedLOR_ND::Assemble2D<8>();
|
|
|
|
template void BatchedLOR_ND::Assemble3D<1>();
|
|
template void BatchedLOR_ND::Assemble3D<2>();
|
|
template void BatchedLOR_ND::Assemble3D<3>();
|
|
template void BatchedLOR_ND::Assemble3D<4>();
|
|
template void BatchedLOR_ND::Assemble3D<5>();
|
|
template void BatchedLOR_ND::Assemble3D<6>();
|
|
template void BatchedLOR_ND::Assemble3D<7>();
|
|
template void BatchedLOR_ND::Assemble3D<8>();
|
|
|
|
BatchedLOR_ND::BatchedLOR_ND(BilinearForm &a,
|
|
FiniteElementSpace &fes_ho_,
|
|
Vector &X_vert_,
|
|
Vector &sparse_ij_,
|
|
Array<int> &sparse_mapping_)
|
|
: BatchedLORKernel(fes_ho_, X_vert_, sparse_ij_, sparse_mapping_)
|
|
{
|
|
ProjectLORCoefficient<VectorFEMassIntegrator>(a, c1);
|
|
ProjectLORCoefficient<CurlCurlIntegrator>(a, c2);
|
|
}
|
|
|
|
} // namespace mfem
|