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fix(graph_engine): fixed major bug with jacobian sparsity

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previousl the sparsity calculations for the jacobian matrix were completly broken. The method subgraph_sparsity was returning that all derivities were only depenednt on temperature and density. It should have been reporting that they also depended on some of the abundances. This was resolved by switching to a different structural sparsity engine (for_jac_sparsity). This bug had turned the solver into a fixed point iteration solver which failed for the stiff system we have. Now that it is resolved the solver can once again evolved over Gyr timescales.
This commit is contained in:
Emily Boudreaux
2025-10-29 14:47:11 -04:00
parent 66b2471c13
commit 23df87f915
9 changed files with 258 additions and 107 deletions
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43
src/lib/solver/strategies/CVODE_solver_strategy.cpp
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@@ -160,6 +160,7 @@ namespace gridfire::solver {
check_cvode_flag(m_cvode_mem == nullptr ? -1 : 0, "CVodeCreate");
initialize_cvode_integration_resources(N, numSpecies, 0.0, equilibratedComposition, absTol, relTol, 0.0);
m_engine.generateJacobianMatrix(equilibratedComposition, T9, netIn.density);
CVODEUserData user_data;
user_data.solver_instance = this;
@@ -192,7 +193,7 @@ namespace gridfire::solver {
std::rethrow_exception(std::make_exception_ptr(*user_data.captured_exception));
}
log_step_diagnostics(user_data);
// log_step_diagnostics(user_data, false);
check_cvode_flag(flag, "CVode");
long int n_steps;
@@ -290,9 +291,17 @@ namespace gridfire::solver {
initialize_cvode_integration_resources(N, numSpecies, current_time, currentComposition, absTol, relTol, accumulated_energy);
check_cvode_flag(CVodeReInit(m_cvode_mem, current_time, m_Y), "CVodeReInit");
LOG_TRACE_L1(m_logger, "Regenerating jacobian matrix...");
m_engine.generateJacobianMatrix(currentComposition, T9, netIn.density);
LOG_TRACE_L1(m_logger, "Done regenerating jacobian matrix...");
}
}
// TODO: Need a more reliable way to get the final composition out, probably some methods that bubble it or something
// aside from that this now seems to be working
LOG_TRACE_L2(m_logger, "CVODE iteration complete");
sunrealtype* y_data = N_VGetArrayPointer(m_Y);
@@ -313,6 +322,7 @@ namespace gridfire::solver {
speciesNames.emplace_back(species.name());
}
LOG_TRACE_L2(m_logger, "Constructing final composition= with {} species", speciesNames.size());
fourdst::composition::Composition outputComposition(speciesNames);
outputComposition.setMassFraction(speciesNames, finalMassFractions);
bool didFinalize = outputComposition.finalize(true);
@@ -320,6 +330,7 @@ namespace gridfire::solver {
LOG_ERROR(m_logger, "Failed to finalize output composition after CVODE integration. Check output mass fractions for validity.");
throw std::runtime_error("Failed to finalize output composition after CVODE integration.");
}
LOG_TRACE_L2(m_logger, "Final composition constructed successfully!");
LOG_TRACE_L2(m_logger, "Constructing output data...");
NetOut netOut;
@@ -327,11 +338,13 @@ namespace gridfire::solver {
netOut.energy = accumulated_energy;
check_cvode_flag(CVodeGetNumSteps(m_cvode_mem, reinterpret_cast<long int *>(&netOut.num_steps)), "CVodeGetNumSteps");
LOG_TRACE_L2(m_logger, "generating final nuclear energy generation rate derivatives...");
auto [dEps_dT, dEps_dRho] = m_engine.calculateEpsDerivatives(
outputComposition,
T9,
netIn.density
);
LOG_TRACE_L2(m_logger, "Found dEps/dT: {:0.3E} and dEps/dRho: {:0.3E}", dEps_dT, dEps_dRho);
netOut.dEps_dT = dEps_dT;
netOut.dEps_dRho = dEps_dRho;
@@ -396,16 +409,19 @@ namespace gridfire::solver {
const long int N = SUNDenseMatrix_Columns(J);
for (size_t j = 0; j < numSpecies; ++j) {
const fourdst::atomic::Species& species_j = engine->getNetworkSpecies()[j];
for (size_t i = 0; i < numSpecies; ++i) {
const fourdst::atomic::Species& species_j = engine->getNetworkSpecies()[j];
const fourdst::atomic::Species& species_i = engine->getNetworkSpecies()[i];
// J(i,j) = d(f_i)/d(y_j)
// Column-major order format for SUNDenseMatrix: J_data[j*N + i]
J_data[j * N + i] = engine->getJacobianMatrixEntry(species_i, species_j);
// Column-major order format for SUNDenseMatrix: J_data[j*N + i] indexes J(i,j)
const double dYi_dt = engine->getJacobianMatrixEntry(species_i, species_j);
J_data[j * N + i] = dYi_dt;
}
}
// For now assume that the energy derivatives wrt. abundances are zero
// TODO: Need a better way to build this part of the output jacobian so it properly pushes the solver
// in the right direction. Currently we effectively are doing a fixed point iteration in energy space.
for (size_t i = 0; i < N; ++i) {
J_data[(N - 1) * N + i] = 0.0; // df(energy_dot)/df(y_i)
J_data[i * N + (N - 1)] = 0.0; // df(f_i)/df(energy_dot)
@@ -423,6 +439,15 @@ namespace gridfire::solver {
const size_t numSpecies = m_engine.getNetworkSpecies().size();
sunrealtype* y_data = N_VGetArrayPointer(y);
// Solver constraints should keep these values very close to 0 but floating point noise can still result in very
// small negative numbers which can result in NaN's and more immediate crashes in the composition
// finalization stage
for (size_t i = 0; i < numSpecies; ++i) {
if (y_data[i] < 0.0) {
y_data[i] = 0.0;
}
}
// PERF: The trade off of ensured index consistency is some performance here. If this becomes a bottleneck we can revisit.
// The specific trade off is that we have decided to enforce that all interfaces accept composition objects rather
// than raw vectors of molar abundances. This then lets any method lookup the species by name rather than relying on
@@ -539,7 +564,7 @@ namespace gridfire::solver {
}
}
void CVODESolverStrategy::log_step_diagnostics(const CVODEUserData &user_data) const {
void CVODESolverStrategy::log_step_diagnostics(const CVODEUserData &user_data, bool displayJacobianStiffness) const {
check_cvode_flag(CVodeGetEstLocalErrors(m_cvode_mem, m_YErr), "CVodeGetEstLocalErrors");
sunrealtype *y_data = N_VGetArrayPointer(m_Y);
@@ -616,9 +641,11 @@ namespace gridfire::solver {
std::cout << utils::format_table("Species Error Ratios", columns) << std::endl;
diagnostics::inspect_jacobian_stiffness(*user_data.engine, composition, user_data.T9, user_data.rho);
for (const auto& species : sorted_speciesNames) {
diagnostics::inspect_species_balance(*user_data.engine, species, composition, user_data.T9, user_data.rho);
if (displayJacobianStiffness) {
diagnostics::inspect_jacobian_stiffness(*user_data.engine, composition, user_data.T9, user_data.rho);
for (const auto& species : sorted_speciesNames) {
diagnostics::inspect_species_balance(*user_data.engine, species, composition, user_data.T9, user_data.rho);
}
}
}