1 // Copyright (c) 2017-2024, 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 #include <ceed.h> 13 14 #include "newtonian_state.h" 15 #include "newtonian_types.h" 16 #include "sgs_dd_utils.h" 17 #include "utils.h" 18 #include "utils_eigensolver_jacobi.h" 19 20 typedef struct SgsDDContext_ *SgsDDContext; 21 struct SgsDDContext_ { 22 CeedInt num_inputs, num_outputs; 23 CeedInt num_layers; 24 CeedInt num_neurons; 25 CeedScalar alpha; 26 27 struct NewtonianIdealGasContext_ gas; 28 struct { 29 size_t bias1, bias2; 30 size_t weight1, weight2; 31 size_t out_scaling; 32 } offsets; 33 size_t total_bytes; 34 CeedScalar data[1]; 35 }; 36 37 CEED_QFUNCTION_HELPER void LeakyReLU(CeedScalar *x, const CeedScalar alpha, const CeedInt N) { 38 for (CeedInt i = 0; i < N; i++) x[i] *= (x[i] < 0 ? alpha : 1.); 39 } 40 41 CEED_QFUNCTION_HELPER void DataDrivenInference(const CeedScalar *inputs, CeedScalar *outputs, SgsDDContext sgsdd_ctx) { 42 const CeedInt num_neurons = sgsdd_ctx->num_neurons; 43 const CeedInt num_inputs = sgsdd_ctx->num_inputs; 44 const CeedInt num_outputs = sgsdd_ctx->num_outputs; 45 const CeedScalar alpha = sgsdd_ctx->alpha; 46 const CeedScalar *bias1 = &sgsdd_ctx->data[sgsdd_ctx->offsets.bias1]; 47 const CeedScalar *bias2 = &sgsdd_ctx->data[sgsdd_ctx->offsets.bias2]; 48 const CeedScalar *weight1 = &sgsdd_ctx->data[sgsdd_ctx->offsets.weight1]; 49 const CeedScalar *weight2 = &sgsdd_ctx->data[sgsdd_ctx->offsets.weight2]; 50 CeedScalar V[20] = {0.}; 51 52 CopyN(bias1, V, num_neurons); 53 MatVecNM(weight1, inputs, num_neurons, num_inputs, CEED_NOTRANSPOSE, V); 54 LeakyReLU(V, alpha, num_neurons); 55 CopyN(bias2, outputs, num_outputs); 56 MatVecNM(weight2, V, num_outputs, num_neurons, CEED_NOTRANSPOSE, outputs); 57 } 58 59 CEED_QFUNCTION_HELPER void ComputeSgsDD_Fused(const CeedScalar grad_velo_aniso[3][3], const CeedScalar km_A_ij[6], const CeedScalar delta, 60 const CeedScalar viscosity, CeedScalar kmsgs_stress[6], SgsDDContext sgsdd_ctx) { 61 CeedScalar inputs[6], grad_velo_magnitude, eigenvectors[3][3], sgs_sframe_sym[6] = {0.}, new_bounds[6][2]; 62 // Copying new_bounds because Sycl online compiler doesn't like direct casting the pointer 63 CopyN(&sgsdd_ctx->data[sgsdd_ctx->offsets.out_scaling], (CeedScalar *)new_bounds, 12); 64 65 ComputeSgsDDInputs(grad_velo_aniso, km_A_ij, delta, viscosity, eigenvectors, inputs, &grad_velo_magnitude); 66 DataDrivenInference(inputs, sgs_sframe_sym, sgsdd_ctx); 67 ComputeSgsDDOutputs(sgs_sframe_sym, delta, eigenvectors, new_bounds, grad_velo_magnitude, kmsgs_stress); 68 } 69 70 // @brief Calculate subgrid stress at nodes using anisotropic data-driven model 71 CEED_QFUNCTION_HELPER int ComputeSgsDDNodal_Fused(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out, 72 StateVariable state_var) { 73 const CeedScalar(*q)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[0]; 74 const CeedScalar(*grad_velo)[3][CEED_Q_VLA] = (const CeedScalar(*)[3][CEED_Q_VLA])in[2]; 75 const CeedScalar(*A_ij_delta)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[3]; 76 const CeedScalar(*inv_multiplicity) = (const CeedScalar(*))in[4]; 77 CeedScalar(*v)[CEED_Q_VLA] = (CeedScalar(*)[CEED_Q_VLA])out[0]; 78 79 const SgsDDContext sgsdd_ctx = (SgsDDContext)ctx; 80 const NewtonianIdealGasContext gas = &sgsdd_ctx->gas; 81 82 CeedPragmaSIMD for (CeedInt i = 0; i < Q; i++) { 83 const CeedScalar qi[5] = {q[0][i], q[1][i], q[2][i], q[3][i], q[4][i]}; 84 const CeedScalar grad_velo_aniso[3][3] = { 85 {grad_velo[0][0][i], grad_velo[0][1][i], grad_velo[0][2][i]}, 86 {grad_velo[1][0][i], grad_velo[1][1][i], grad_velo[1][2][i]}, 87 {grad_velo[2][0][i], grad_velo[2][1][i], grad_velo[2][2][i]} 88 }; 89 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]}; 90 const CeedScalar delta = A_ij_delta[6][i]; 91 const State s = StateFromQ(gas, qi, state_var); 92 CeedScalar km_sgs[6]; 93 94 ComputeSgsDD_Fused(grad_velo_aniso, km_A_ij, delta, gas->mu / s.U.density, km_sgs, sgsdd_ctx); 95 96 for (int j = 0; j < 6; j++) v[j][i] = inv_multiplicity[i] * km_sgs[j]; 97 } 98 return 0; 99 } 100 101 CEED_QFUNCTION(ComputeSgsDDNodal_Prim)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 102 return ComputeSgsDDNodal_Fused(ctx, Q, in, out, STATEVAR_PRIMITIVE); 103 } 104 105 CEED_QFUNCTION(ComputeSgsDDNodal_Conserv)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 106 return ComputeSgsDDNodal_Fused(ctx, Q, in, out, STATEVAR_CONSERVATIVE); 107 } 108 109 // @brief Calculate inputs to anisotropic data-driven model 110 CEED_QFUNCTION_HELPER int ComputeSgsDDNodal_Sequential_Inputs(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out, 111 StateVariable state_var) { 112 const CeedScalar(*q)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[0]; 113 const CeedScalar(*grad_velo)[3][CEED_Q_VLA] = (const CeedScalar(*)[3][CEED_Q_VLA])in[1]; 114 const CeedScalar(*A_ij_delta)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[2]; 115 const CeedScalar(*inv_multiplicity) = (const CeedScalar(*))in[3]; 116 CeedScalar(*eigenvectors_stored) = out[0]; 117 CeedScalar(*model_inputs)[CEED_Q_VLA] = (CeedScalar(*)[CEED_Q_VLA])out[1]; 118 119 const SgsDDContext sgsdd_ctx = (SgsDDContext)ctx; 120 const NewtonianIdealGasContext gas = &sgsdd_ctx->gas; 121 122 CeedPragmaSIMD for (CeedInt i = 0; i < Q; i++) { 123 const CeedScalar qi[5] = {q[0][i], q[1][i], q[2][i], q[3][i], q[4][i]}; 124 const CeedScalar grad_velo_aniso[3][3] = { 125 {grad_velo[0][0][i], grad_velo[0][1][i], grad_velo[0][2][i]}, 126 {grad_velo[1][0][i], grad_velo[1][1][i], grad_velo[1][2][i]}, 127 {grad_velo[2][0][i], grad_velo[2][1][i], grad_velo[2][2][i]} 128 }; 129 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]}; 130 const CeedScalar delta = A_ij_delta[6][i]; 131 const State s = StateFromQ(gas, qi, state_var); 132 133 CeedScalar model_inputs_i[6], grad_velo_magnitude, eigenvectors[3][3]; 134 ComputeSgsDDInputs(grad_velo_aniso, km_A_ij, delta, gas->mu / s.U.density, eigenvectors, model_inputs_i, &grad_velo_magnitude); 135 136 ScaleN(model_inputs_i, inv_multiplicity[i], 6); 137 StoredValuesPack(Q, i, 0, 6, model_inputs_i, (CeedScalar *)model_inputs); 138 StoredValuesPack(Q, i, 0, 9, (const CeedScalar *)eigenvectors, eigenvectors_stored); 139 StoredValuesPack(Q, i, 9, 1, &grad_velo_magnitude, eigenvectors_stored); 140 } 141 return CEED_ERROR_SUCCESS; 142 } 143 144 CEED_QFUNCTION(ComputeSgsDDNodal_Sequential_Inputs_Prim)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 145 return ComputeSgsDDNodal_Sequential_Inputs(ctx, Q, in, out, STATEVAR_PRIMITIVE); 146 } 147 148 CEED_QFUNCTION(ComputeSgsDDNodal_Sequential_Inputs_Conserv)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 149 return ComputeSgsDDNodal_Sequential_Inputs(ctx, Q, in, out, STATEVAR_CONSERVATIVE); 150 } 151 152 // @brief Runs inference on the data-driven model, used predominantsly for testing and validation 153 CEED_QFUNCTION(ComputeSgsDDNodal_Sequential_Inference)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 154 const CeedScalar(*model_inputs) = in[0]; 155 const CeedScalar(*inv_multiplicity) = in[1]; 156 CeedScalar(*model_outputs) = out[0]; 157 158 const SgsDDContext sgsdd_ctx = (SgsDDContext)ctx; 159 160 CeedPragmaSIMD for (CeedInt i = 0; i < Q; i++) { 161 CeedScalar model_inputs_i[6], model_outputs_i[6]; 162 // CeedScalar model_outputs_i[6]; 163 // CeedScalar model_inputs_i[6] = {1, 2, 3, 4, 5, 6}; 164 165 StoredValuesUnpack(Q, i, 0, 6, (const CeedScalar *)model_inputs, model_inputs_i); 166 DataDrivenInference(model_inputs_i, model_outputs_i, sgsdd_ctx); 167 ScaleN(model_outputs_i, inv_multiplicity[i], 6); 168 StoredValuesPack(Q, i, 0, 6, model_outputs_i, model_outputs); 169 } 170 return CEED_ERROR_SUCCESS; 171 } 172 173 // @brief Calculates SGS from outputs of anisotropic data-driven model 174 CEED_QFUNCTION(ComputeSgsDDNodal_Sequential_Outputs)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 175 const CeedScalar(*model_outputs) = in[0]; 176 const CeedScalar(*A_ij_delta)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[1]; 177 const CeedScalar(*inv_multiplicity) = (const CeedScalar(*))in[2]; 178 const CeedScalar(*eigenvectors_stored) = in[3]; 179 CeedScalar(*kmsgs_stress)[CEED_Q_VLA] = (CeedScalar(*)[CEED_Q_VLA])out[0]; 180 181 const SgsDDContext sgsdd_ctx = (SgsDDContext)ctx; 182 CeedScalar new_bounds[6][2]; 183 CopyN(&sgsdd_ctx->data[sgsdd_ctx->offsets.out_scaling], (CeedScalar *)new_bounds, 12); 184 185 CeedPragmaSIMD for (CeedInt i = 0; i < Q; i++) { 186 CeedScalar model_outputs_i[6]; 187 const CeedScalar delta = A_ij_delta[6][i]; 188 189 StoredValuesUnpack(Q, i, 0, 6, model_outputs, model_outputs_i); 190 CeedScalar grad_velo_magnitude, eigenvectors[3][3], kmsgs_stress_i[6]; 191 StoredValuesUnpack(Q, i, 0, 9, eigenvectors_stored, (CeedScalar *)eigenvectors); 192 StoredValuesUnpack(Q, i, 9, 1, eigenvectors_stored, &grad_velo_magnitude); 193 ComputeSgsDDOutputs(model_outputs_i, delta, eigenvectors, new_bounds, grad_velo_magnitude, kmsgs_stress_i); 194 195 for (int j = 0; j < 6; j++) kmsgs_stress[j][i] = inv_multiplicity[i] * kmsgs_stress_i[j]; 196 } 197 return CEED_ERROR_SUCCESS; 198 } 199 200 // @brief Adds subgrid stress to residual (during IFunction evaluation) 201 CEED_QFUNCTION_HELPER int FluxSubgridStress(const StatePrimitive Y, const CeedScalar km_sgs[6], CeedScalar Flux[5][3]) { 202 CeedScalar sgs[3][3]; 203 204 KMUnpack(km_sgs, sgs); 205 for (CeedInt j = 0; j < 3; j++) { 206 Flux[0][j] = 0.; 207 for (CeedInt k = 0; k < 3; k++) Flux[k + 1][j] = sgs[k][j]; 208 Flux[4][j] = Y.velocity[0] * sgs[0][j] + Y.velocity[1] * sgs[1][j] + Y.velocity[2] * sgs[2][j]; 209 } 210 return 0; 211 } 212 213 CEED_QFUNCTION_HELPER int IFunction_NodalSgs(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out, StateVariable state_var) { 214 const CeedScalar(*q)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[0]; 215 const CeedScalar(*q_data) = in[1]; 216 const CeedScalar(*km_sgs)[CEED_Q_VLA] = (const CeedScalar(*)[CEED_Q_VLA])in[2]; 217 CeedScalar(*Grad_v)[5][CEED_Q_VLA] = (CeedScalar(*)[5][CEED_Q_VLA])out[0]; 218 219 NewtonianIdealGasContext gas = (NewtonianIdealGasContext)ctx; 220 221 CeedPragmaSIMD for (CeedInt i = 0; i < Q; i++) { 222 const CeedScalar qi[5] = {q[0][i], q[1][i], q[2][i], q[3][i], q[4][i]}; 223 const State s = StateFromQ(gas, qi, state_var); 224 225 CeedScalar wdetJ, dXdx[3][3]; 226 QdataUnpack_3D(Q, i, q_data, &wdetJ, dXdx); 227 228 CeedScalar Flux[5][3]; 229 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]}; 230 FluxSubgridStress(s.Y, km_sgs_i, Flux); 231 232 for (CeedInt k = 0; k < 3; k++) { 233 for (CeedInt j = 0; j < 5; j++) { 234 Grad_v[k][j][i] = -wdetJ * (dXdx[k][0] * Flux[j][0] + dXdx[k][1] * Flux[j][1] + dXdx[k][2] * Flux[j][2]); 235 } 236 } 237 } 238 return 0; 239 } 240 241 CEED_QFUNCTION(IFunction_NodalSgs_Conserv)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 242 return IFunction_NodalSgs(ctx, Q, in, out, STATEVAR_CONSERVATIVE); 243 } 244 245 CEED_QFUNCTION(IFunction_NodalSgs_Prim)(void *ctx, CeedInt Q, const CeedScalar *const *in, CeedScalar *const *out) { 246 return IFunction_NodalSgs(ctx, Q, in, out, STATEVAR_PRIMITIVE); 247 } 248