Add AMGCL_cuda #70
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| Original file line number | Diff line number | Diff line change |
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| #ifdef POLYSOLVE_WITH_AMGCL | ||
| // #ifdef POLYSOLVE_WITH_CUDA | ||
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There was a problem hiding this comment. I commented it out because polysolve CMakeLists.txt does not have POLYSOLVE_WITH_CUDA flag, but polyfem has. So I deleted the flag here. |
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| //////////////////////////////////////////////////////////////////////////////// | ||
| #include "AMGCL_cuda.hpp" | ||
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| #include <boost/property_tree/ptree.hpp> | ||
| #include <boost/property_tree/json_parser.hpp> | ||
| //////////////////////////////////////////////////////////////////////////////// | ||
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| namespace polysolve::linear | ||
| { | ||
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| namespace | ||
| { | ||
| /* https://stackoverflow.com/questions/15904896/range-based-for-loop-on-a-dynamic-array */ | ||
| template <typename T> | ||
| struct WrappedArray | ||
| { | ||
| WrappedArray(const T *first, const T *last) | ||
| : begin_{first}, end_{last} {} | ||
| WrappedArray(const T *first, std::ptrdiff_t size) | ||
| : WrappedArray{first, first + size} {} | ||
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| const T *begin() const noexcept { return begin_; } | ||
| const T *end() const noexcept { return end_; } | ||
| const T &operator[](const size_t i) const { return begin_[i]; } | ||
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| const T *begin_; | ||
| const T *end_; | ||
| }; | ||
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| json default_params() | ||
| { | ||
| json params = R"({ | ||
| "precond": { | ||
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| "relax": { | ||
| "type": "spai0" | ||
| }, | ||
| "class": "amg", | ||
| "max_levels": 6, | ||
| "direct_coarse": false, | ||
| "ncycle": 2, | ||
| "coarsening": { | ||
| "type": "smoothed_aggregation", | ||
| "estimate_spectral_radius": true, | ||
| "relax": 1, | ||
| "aggr": { | ||
| "eps_strong": 0 | ||
| } | ||
| } | ||
| }, | ||
| "solver": { | ||
| "tol": 1e-10, | ||
| "maxiter": 1000, | ||
| "type": "cg" | ||
| } | ||
| })"_json; | ||
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| return params; | ||
| } | ||
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| void set_params(const json ¶ms, json &out) | ||
| { | ||
| if (params.contains("AMGCL_cuda")) | ||
| { | ||
| // Patch the stored params with input ones | ||
| if (params["AMGCL_cuda"].contains("precond")) | ||
| out["precond"].merge_patch(params["AMGCL_cuda"]["precond"]); | ||
| if (params["AMGCL_cuda"].contains("solver")) | ||
| out["solver"].merge_patch(params["AMGCL_cuda"]["solver"]); | ||
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| if (out["precond"]["class"] == "schur_pressure_correction") | ||
| { | ||
| // Initialize the u and p solvers with a tolerance that is comparable to the main solver's | ||
| if (!out["precond"].contains("usolver")) | ||
| { | ||
| out["precond"]["usolver"] = R"({"solver": {"maxiter": 100}})"_json; | ||
| out["precond"]["usolver"]["solver"]["tol"] = 10 * out["solver"]["tol"].get<double>(); | ||
| } | ||
| if (!out["precond"].contains("usolver")) | ||
| { | ||
| out["precond"]["psolver"] = R"({"solver": {"maxiter": 100}})"_json; | ||
| out["precond"]["psolver"]["solver"]["tol"] = 10 * out["solver"]["tol"].get<double>(); | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } // namespace | ||
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| //////////////////////////////////////////////////////////////////////////////// | ||
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| AMGCL_cuda::AMGCL_cuda() | ||
| { | ||
| params_ = default_params(); | ||
| // NOTE: usolver and psolver parameters are only used if the | ||
| // preconditioner class is "schur_pressure_correction" | ||
| precond_num_ = 0; | ||
| cusparseCreate(&backend_params_.cusparse_handle); | ||
| } | ||
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| // Set solver parameters | ||
| void AMGCL_cuda::set_parameters(const json ¶ms) | ||
| { | ||
| if (params.contains("AMGCL_cuda")) | ||
| { | ||
| set_params(params, params_); | ||
| } | ||
| } | ||
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| void AMGCL_cuda::get_info(json ¶ms) const | ||
| { | ||
| params["num_iterations"] = iterations_; | ||
| params["final_res_norm"] = residual_error_; | ||
| } | ||
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| //////////////////////////////////////////////////////////////////////////////// | ||
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| void AMGCL_cuda::factorize(const StiffnessMatrix &Ain) | ||
| { | ||
| assert(precond_num_ > 0); | ||
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| int numRows = Ain.rows(); | ||
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| WrappedArray<StiffnessMatrix::StorageIndex> ia(Ain.outerIndexPtr(), numRows + 1); | ||
| WrappedArray<StiffnessMatrix::StorageIndex> ja(Ain.innerIndexPtr(), Ain.nonZeros()); | ||
| WrappedArray<StiffnessMatrix::Scalar> a(Ain.valuePtr(), Ain.nonZeros()); | ||
| if (params_["precond"]["class"] == "schur_pressure_correction") | ||
| { | ||
| std::vector<char> pmask(numRows, 0); | ||
| for (size_t i = precond_num_; i < numRows; ++i) | ||
| pmask[i] = 1; | ||
| params_["precond"]["pmask"] = pmask; | ||
| } | ||
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| // AMGCL takes the parameters as a Boost property_tree (i.e., another JSON data structure) | ||
| std::stringstream ss_params; | ||
| ss_params << params_; | ||
| boost::property_tree::ptree pt_params; | ||
| boost::property_tree::read_json(ss_params, pt_params); | ||
| auto A = std::tie(numRows, ia, ja, a); | ||
| solver_ = std::make_unique<Solver>(A, pt_params, backend_params_); | ||
| // std::cout << *solver_.get() << std::endl; | ||
| iterations_ = 0; | ||
| residual_error_ = 0; | ||
| } | ||
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| //////////////////////////////////////////////////////////////////////////////// | ||
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| //////////////////////////////////////////////////////////////////////////////// | ||
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| void AMGCL_cuda::solve(const Eigen::Ref<const VectorXd> rhs, Eigen::Ref<VectorXd> result) | ||
| { | ||
| assert(result.size() == rhs.size()); | ||
| std::vector<double> _rhs(rhs.data(), rhs.data() + rhs.size()); | ||
| std::vector<double> x(result.data(), result.data() + result.size()); | ||
| auto rhs_b = Backend::copy_vector(_rhs, backend_params_); | ||
| auto x_b = Backend::copy_vector(x, backend_params_); | ||
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| std::tie(iterations_, residual_error_) = (*solver_)(*rhs_b, *x_b); | ||
| thrust::copy(x_b->begin(), x_b->end(), result.data()); | ||
| } | ||
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| //////////////////////////////////////////////////////////////////////////////// | ||
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| AMGCL_cuda::~AMGCL_cuda() | ||
| { | ||
| } | ||
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| } // namespace polysolve | ||
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| // #endif | ||
| #endif | ||
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leave pardiso off
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Fixed.