1 // Copyright (c) 2017-2023, Lawrence Livermore National Security, LLC and other CEED contributors. 2 // All Rights Reserved. See the top-level LICENSE and NOTICE files for details. 3 // 4 // SPDX-License-Identifier: BSD-2-Clause 5 // 6 // This file is part of CEED: http://github.com/ceed 7 8 /// @file 9 /// Structs and helper functions to evaluate data-driven subgrid-stress modeling 10 /// See 'Invariant data-driven subgrid stress modeling in the strain-rate eigenframe for large eddy simulation' 2022 and 'S-frame discrepancy 11 /// correction models for data-informed Reynolds stress closure' 2022 12 13 #ifndef sgs_dd_model_h 14 #define sgs_dd_model_h 15 16 #include <ceed.h> 17 18 #include "newtonian_state.h" 19 #include "newtonian_types.h" 20 #include "sgs_dd_utils.h" 21 #include "utils.h" 22 #include "utils_eigensolver_jacobi.h" 23 24 typedef struct SgsDDContext_ *SgsDDContext; 25 struct SgsDDContext_ { 26 CeedInt num_inputs, num_outputs; 27 CeedInt num_layers; 28 CeedInt num_neurons; 29 CeedScalar alpha; 30 31 struct NewtonianIdealGasContext_ gas; 32 struct { 33 size_t bias1, bias2; 34 size_t weight1, weight2; 35 size_t out_scaling; 36 } offsets; 37 size_t total_bytes; 38 CeedScalar data[1]; 39 }; 40 41 CEED_QFUNCTION_HELPER void LeakyReLU(CeedScalar *x, const CeedScalar alpha, const CeedInt N) { 42 for (CeedInt i = 0; i < N; i++) x[i] *= (x[i] < 0 ? alpha : 1.); 43 } 44 45 CEED_QFUNCTION_HELPER void DataDrivenInference(const CeedScalar *inputs, CeedScalar *outputs, SgsDDContext sgsdd_ctx) { 46 const CeedInt num_neurons = sgsdd_ctx->num_neurons; 47 const CeedInt num_inputs = sgsdd_ctx->num_inputs; 48 const CeedInt num_outputs = sgsdd_ctx->num_outputs; 49 const CeedScalar alpha = sgsdd_ctx->alpha; 50 const CeedScalar *bias1 = &sgsdd_ctx->data[sgsdd_ctx->offsets.bias1]; 51 const CeedScalar *bias2 = &sgsdd_ctx->data[sgsdd_ctx->offsets.bias2]; 52 const CeedScalar *weight1 = &sgsdd_ctx->data[sgsdd_ctx->offsets.weight1]; 53 const CeedScalar *weight2 = &sgsdd_ctx->data[sgsdd_ctx->offsets.weight2]; 54 CeedScalar V[20] = {0.}; 55 56 CopyN(bias1, V, num_neurons); 57 MatVecNM(weight1, inputs, num_neurons, num_inputs, CEED_NOTRANSPOSE, V); 58 LeakyReLU(V, alpha, num_neurons); 59 CopyN(bias2, outputs, num_outputs); 60 MatVecNM(weight2, V, num_outputs, num_neurons, CEED_NOTRANSPOSE, outputs); 61 } 62 63 CEED_QFUNCTION_HELPER void ComputeSgsDD_Fused(const CeedScalar grad_velo_aniso[3][3], const CeedScalar km_A_ij[6], const CeedScalar delta, 64 const CeedScalar viscosity, CeedScalar kmsgs_stress[6], SgsDDContext sgsdd_ctx) { 65 CeedScalar inputs[6], grad_velo_magnitude, eigenvectors[3][3], sgs_sframe_sym[6] = {0.}, new_bounds[6][2]; 66 // Copying new_bounds because Sycl online compiler doesn't like direct casting the pointer 67 CopyN(&sgsdd_ctx->data[sgsdd_ctx->offsets.out_scaling], (CeedScalar *)new_bounds, 12); 68 69 ComputeSgsDDInputs(grad_velo_aniso, km_A_ij, delta, viscosity, eigenvectors, inputs, &grad_velo_magnitude); 70 DataDrivenInference(inputs, sgs_sframe_sym, sgsdd_ctx); 71 ComputeSgsDDOutputs(sgs_sframe_sym, delta, eigenvectors, new_bounds, grad_velo_magnitude, kmsgs_stress); 72 } 73 74 // @brief Calculate subgrid stress at nodes using anisotropic data-driven model 75 CEED_QFUNCTION_HELPER int ComputeSgsDDNodal_Fused(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out, 76 StateVariable state_var) { 77 const CeedScalar(*q)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[0]; 78 const CeedScalar(*grad_velo)[3][CEED_Q_VLA] = (const CeedScalar(*)[3][CEED_Q_VLA])in[2]; 79 const CeedScalar(*A_ij_delta)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[3]; 80 const CeedScalar(*inv_multiplicity) = (const CeedScalar(*))in[4]; 81 CeedScalar(*v)[CEED_Q_VLA] = (CeedScalar(*)[CEED_Q_VLA])out[0]; 82 83 const SgsDDContext sgsdd_ctx = (SgsDDContext)ctx; 84 const NewtonianIdealGasContext gas = &sgsdd_ctx->gas; 85 86 CeedPragmaSIMD for (CeedInt i = 0; i < Q; i++) { 87 const CeedScalar qi[5] = {q[0][i], q[1][i], q[2][i], q[3][i], q[4][i]}; 88 const CeedScalar grad_velo_aniso[3][3] = { 89 {grad_velo[0][0][i], grad_velo[0][1][i], grad_velo[0][2][i]}, 90 {grad_velo[1][0][i], grad_velo[1][1][i], grad_velo[1][2][i]}, 91 {grad_velo[2][0][i], grad_velo[2][1][i], grad_velo[2][2][i]} 92 }; 93 const CeedScalar km_A_ij[6] = {A_ij_delta[0][i], A_ij_delta[1][i], A_ij_delta[2][i], A_ij_delta[3][i], A_ij_delta[4][i], A_ij_delta[5][i]}; 94 const CeedScalar delta = A_ij_delta[6][i]; 95 const State s = StateFromQ(gas, qi, state_var); 96 CeedScalar km_sgs[6]; 97 98 ComputeSgsDD_Fused(grad_velo_aniso, km_A_ij, delta, gas->mu / s.U.density, km_sgs, sgsdd_ctx); 99 100 for (int j = 0; j < 6; j++) v[j][i] = inv_multiplicity[i] * km_sgs[j]; 101 } 102 return 0; 103 } 104 105 CEED_QFUNCTION(ComputeSgsDDNodal_Prim)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 106 return ComputeSgsDDNodal_Fused(ctx, Q, in, out, STATEVAR_PRIMITIVE); 107 } 108 109 CEED_QFUNCTION(ComputeSgsDDNodal_Conserv)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 110 return ComputeSgsDDNodal_Fused(ctx, Q, in, out, STATEVAR_CONSERVATIVE); 111 } 112 113 // @brief Calculate inputs to anisotropic data-driven model 114 CEED_QFUNCTION_HELPER int ComputeSgsDDNodal_Sequential_Inputs(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out, 115 StateVariable state_var) { 116 const CeedScalar(*q)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[0]; 117 const CeedScalar(*grad_velo)[3][CEED_Q_VLA] = (const CeedScalar(*)[3][CEED_Q_VLA])in[1]; 118 const CeedScalar(*A_ij_delta)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[2]; 119 const CeedScalar(*inv_multiplicity) = (const CeedScalar(*))in[3]; 120 CeedScalar(*eigenvectors_stored) = out[0]; 121 CeedScalar(*model_inputs)[CEED_Q_VLA] = (CeedScalar(*)[CEED_Q_VLA])out[1]; 122 123 const SgsDDContext sgsdd_ctx = (SgsDDContext)ctx; 124 const NewtonianIdealGasContext gas = &sgsdd_ctx->gas; 125 126 CeedPragmaSIMD for (CeedInt i = 0; i < Q; i++) { 127 const CeedScalar qi[5] = {q[0][i], q[1][i], q[2][i], q[3][i], q[4][i]}; 128 const CeedScalar grad_velo_aniso[3][3] = { 129 {grad_velo[0][0][i], grad_velo[0][1][i], grad_velo[0][2][i]}, 130 {grad_velo[1][0][i], grad_velo[1][1][i], grad_velo[1][2][i]}, 131 {grad_velo[2][0][i], grad_velo[2][1][i], grad_velo[2][2][i]} 132 }; 133 const CeedScalar km_A_ij[6] = {A_ij_delta[0][i], A_ij_delta[1][i], A_ij_delta[2][i], A_ij_delta[3][i], A_ij_delta[4][i], A_ij_delta[5][i]}; 134 const CeedScalar delta = A_ij_delta[6][i]; 135 const State s = StateFromQ(gas, qi, state_var); 136 137 CeedScalar model_inputs_i[6], grad_velo_magnitude, eigenvectors[3][3]; 138 ComputeSgsDDInputs(grad_velo_aniso, km_A_ij, delta, gas->mu / s.U.density, eigenvectors, model_inputs_i, &grad_velo_magnitude); 139 140 ScaleN(model_inputs_i, inv_multiplicity[i], 6); 141 StoredValuesPack(Q, i, 0, 6, model_inputs_i, (CeedScalar *)model_inputs); 142 StoredValuesPack(Q, i, 0, 9, (const CeedScalar *)eigenvectors, eigenvectors_stored); 143 StoredValuesPack(Q, i, 9, 1, &grad_velo_magnitude, eigenvectors_stored); 144 } 145 return CEED_ERROR_SUCCESS; 146 } 147 148 CEED_QFUNCTION(ComputeSgsDDNodal_Sequential_Inputs_Prim)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 149 return ComputeSgsDDNodal_Sequential_Inputs(ctx, Q, in, out, STATEVAR_PRIMITIVE); 150 } 151 152 CEED_QFUNCTION(ComputeSgsDDNodal_Sequential_Inputs_Conserv)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 153 return ComputeSgsDDNodal_Sequential_Inputs(ctx, Q, in, out, STATEVAR_CONSERVATIVE); 154 } 155 156 // @brief Runs inference on the data-driven model, used predominantsly for testing and validation 157 CEED_QFUNCTION(ComputeSgsDDNodal_Sequential_Inference)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 158 const CeedScalar(*model_inputs) = in[0]; 159 const CeedScalar(*inv_multiplicity) = in[1]; 160 CeedScalar(*model_outputs) = out[0]; 161 162 const SgsDDContext sgsdd_ctx = (SgsDDContext)ctx; 163 164 CeedPragmaSIMD for (CeedInt i = 0; i < Q; i++) { 165 CeedScalar model_inputs_i[6], model_outputs_i[6]; 166 167 StoredValuesUnpack(Q, i, 0, 6, (const CeedScalar *)model_inputs, model_inputs_i); 168 DataDrivenInference(model_inputs_i, model_outputs_i, sgsdd_ctx); 169 ScaleN(model_outputs_i, inv_multiplicity[i], 6); 170 StoredValuesPack(Q, i, 0, 6, model_outputs_i, model_outputs); 171 } 172 return CEED_ERROR_SUCCESS; 173 } 174 175 // @brief Calculates SGS from outputs of anisotropic data-driven model 176 CEED_QFUNCTION(ComputeSgsDDNodal_Sequential_Outputs)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 177 const CeedScalar(*model_outputs) = in[0]; 178 const CeedScalar(*A_ij_delta)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[1]; 179 const CeedScalar(*inv_multiplicity) = (const CeedScalar(*))in[2]; 180 const CeedScalar(*eigenvectors_stored) = in[3]; 181 CeedScalar(*kmsgs_stress)[CEED_Q_VLA] = (CeedScalar(*)[CEED_Q_VLA])out[0]; 182 183 const SgsDDContext sgsdd_ctx = (SgsDDContext)ctx; 184 CeedScalar new_bounds[6][2]; 185 CopyN(&sgsdd_ctx->data[sgsdd_ctx->offsets.out_scaling], (CeedScalar *)new_bounds, 12); 186 187 CeedPragmaSIMD for (CeedInt i = 0; i < Q; i++) { 188 CeedScalar model_outputs_i[6]; 189 const CeedScalar delta = A_ij_delta[6][i]; 190 191 StoredValuesUnpack(Q, i, 0, 6, model_outputs, model_outputs_i); 192 CeedScalar grad_velo_magnitude, eigenvectors[3][3], kmsgs_stress_i[6]; 193 StoredValuesUnpack(Q, i, 0, 9, eigenvectors_stored, (CeedScalar *)eigenvectors); 194 StoredValuesUnpack(Q, i, 9, 1, eigenvectors_stored, &grad_velo_magnitude); 195 ComputeSgsDDOutputs(model_outputs_i, delta, eigenvectors, new_bounds, grad_velo_magnitude, kmsgs_stress_i); 196 197 for (int j = 0; j < 6; j++) kmsgs_stress[j][i] = inv_multiplicity[i] * kmsgs_stress_i[j]; 198 } 199 return CEED_ERROR_SUCCESS; 200 } 201 202 // @brief Adds subgrid stress to residual (during IFunction evaluation) 203 CEED_QFUNCTION_HELPER int FluxSubgridStress(const StatePrimitive Y, const CeedScalar km_sgs[6], CeedScalar Flux[5][3]) { 204 CeedScalar sgs[3][3]; 205 206 KMUnpack(km_sgs, sgs); 207 for (CeedInt j = 0; j < 3; j++) { 208 Flux[0][j] = 0.; 209 for (CeedInt k = 0; k < 3; k++) Flux[k + 1][j] = sgs[k][j]; 210 Flux[4][j] = Y.velocity[0] * sgs[0][j] + Y.velocity[1] * sgs[1][j] + Y.velocity[2] * sgs[2][j]; 211 } 212 return 0; 213 } 214 215 CEED_QFUNCTION_HELPER int IFunction_NodalSgs(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out, StateVariable state_var) { 216 const CeedScalar(*q)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[0]; 217 const CeedScalar(*q_data) = in[1]; 218 const CeedScalar(*km_sgs)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[2]; 219 CeedScalar(*Grad_v)[5][CEED_Q_VLA] = (CeedScalar(*)[5][CEED_Q_VLA])out[0]; 220 221 NewtonianIdealGasContext gas = (NewtonianIdealGasContext)ctx; 222 223 CeedPragmaSIMD for (CeedInt i = 0; i < Q; i++) { 224 const CeedScalar qi[5] = {q[0][i], q[1][i], q[2][i], q[3][i], q[4][i]}; 225 const State s = StateFromQ(gas, qi, state_var); 226 227 CeedScalar wdetJ, dXdx[3][3]; 228 QdataUnpack_3D(Q, i, q_data, &wdetJ, dXdx); 229 230 CeedScalar Flux[5][3]; 231 const CeedScalar km_sgs_i[6] = {km_sgs[0][i], km_sgs[1][i], km_sgs[2][i], km_sgs[3][i], km_sgs[4][i], km_sgs[5][i]}; 232 FluxSubgridStress(s.Y, km_sgs_i, Flux); 233 234 for (CeedInt k = 0; k < 3; k++) { 235 for (CeedInt j = 0; j < 5; j++) { 236 Grad_v[k][j][i] = -wdetJ * (dXdx[k][0] * Flux[j][0] + dXdx[k][1] * Flux[j][1] + dXdx[k][2] * Flux[j][2]); 237 } 238 } 239 } 240 return 0; 241 } 242 243 CEED_QFUNCTION(IFunction_NodalSgs_Conserv)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 244 return IFunction_NodalSgs(ctx, Q, in, out, STATEVAR_CONSERVATIVE); 245 } 246 247 CEED_QFUNCTION(IFunction_NodalSgs_Prim)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 248 return IFunction_NodalSgs(ctx, Q, in, out, STATEVAR_PRIMITIVE); 249 } 250 251 #endif // sgs_dd_model_h 252