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RoushelfyRoushelfy
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6_inv_free
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‎simulators/7_self_contact/CMakeLists.txt‎

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add_executable(7_self_contact)
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target_compile_options(7_self_contact PRIVATE -g)
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set_target_properties(7_self_contact PROPERTIES CUDA_SEPARABLE_COMPILATION ON)
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target_link_libraries(7_self_contact PRIVATE muda cusolver cublas cusparse)
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option(BUILD_SHARED_LIBS "Build shared libraries" OFF)
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include_directories(include)
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file(GLOB_RECURSE 7_self_contact_CU_SOURCE CONFIGURE_DEPENDS "src/*.cu")
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target_sources(7_self_contact PRIVATE ${7_self_contact_CU_SOURCE})
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file(GLOB_RECURSE 7_self_contact_CPP_SOURCE CONFIGURE_DEPENDS "src/*.cpp")
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target_sources(7_self_contact PRIVATE ${7_self_contact_CPP_SOURCE})
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target_link_libraries(7_self_contact PRIVATE sfml-graphics)

‎simulators/7_self_contact/include/BarrierEnergy.h‎

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#pragma once
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#include <memory>
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#include <Eigen/Dense>
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#include "uti.h"
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template <typename T, int dim>
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class BarrierEnergy
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{
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public:
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BarrierEnergy(const std::vector<T> &x, const std::vector<T> n, const std::vector<T> o, const std::vector<T> &contact_area);
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BarrierEnergy();
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~BarrierEnergy();
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BarrierEnergy(BarrierEnergy &&rhs);
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BarrierEnergy(const BarrierEnergy &rhs);
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BarrierEnergy &operator=(BarrierEnergy &&rhs);
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void update_x(const DeviceBuffer<T> &x);
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T val(); // Calculate the value of the energy
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const DeviceBuffer<T> &grad(); // Calculate the gradient of the energy
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const DeviceTripletMatrix<T, 1> &hess(); // Calculate the Hessian matrix of the energy
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const DeviceBuffer<T> compute_mu_lambda(T mu);
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T init_step_size(const DeviceBuffer<T> &p); // Calculate the initial step size for the line search
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private:
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// The implementation details of the VecAdder class are placed in the implementation class declared here.
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struct Impl;
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// The private pointer to the implementation class Impl
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std::unique_ptr<Impl> pimpl_;
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};

‎simulators/7_self_contact/include/FrictionEnergy.h‎

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#pragma once
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#include <memory>
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#include <Eigen/Dense>
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#include <vector>
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#include "uti.h"
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template <typename T, int dim>
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class FrictionEnergy
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{
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public:
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FrictionEnergy(const std::vector<T> &v, T hhat, const std::vector<T> &n);
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FrictionEnergy();
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~FrictionEnergy();
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FrictionEnergy(FrictionEnergy &&rhs);
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FrictionEnergy(const FrictionEnergy &rhs);
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FrictionEnergy &operator=(FrictionEnergy &&rhs);
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void update_v(const DeviceBuffer<T> &v);
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void update_mu_lambda(const DeviceBuffer<T> &mu_lambda);
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T val(); // Calculate the value of the energy
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const DeviceBuffer<T> &grad(); // Calculate the gradient of the energy
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const DeviceTripletMatrix<T, 1> &hess(); // Calculate the Hessian matrix of the energy
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private:
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struct Impl;
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std::unique_ptr<Impl> pimpl_;
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T __device__ f0(T vbarnorm, T Epsv, T hhat);
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T __device__ f1_div_vbarnorm(T vbarnorm, T Epsv);
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T __device__ f_hess_term(T vbarnorm, T Epsv);
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};

‎simulators/7_self_contact/include/GravityEnergy.h‎

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#pragma once
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#include <memory>
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#include <Eigen/Dense>
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#include "square_mesh.h"
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#include <muda/muda.h>
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#include <muda/container.h>
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#include <muda/ext/linear_system.h>
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using namespace muda;
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template <typename T, int dim>
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class GravityEnergy
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{
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public:
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GravityEnergy(int N, T m);
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GravityEnergy();
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~GravityEnergy();
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GravityEnergy(GravityEnergy &&rhs);
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GravityEnergy(const GravityEnergy &rhs);
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GravityEnergy &operator=(GravityEnergy &&rhs);
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GravityEnergy &operator=(const GravityEnergy &rhs);
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void update_x(const DeviceBuffer<T> &x);
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void update_x_tilde(const DeviceBuffer<T> &x_tilde);
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void update_m(T m);
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T val(); // Calculate the value of the energy
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const DeviceBuffer<T> &grad(); // Calculate the gradient of the energy
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private:
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// The implementation details of the VecAdder class are placed in the implementation class declared here.
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struct Impl;
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// The private pointer to the implementation class Impl
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std::unique_ptr<Impl> pimpl_;
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};

‎simulators/7_self_contact/include/InertialEnergy.h‎

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#pragma once
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#include <memory>
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#include <Eigen/Dense>
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#include "square_mesh.h"
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#include <muda/muda.h>
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#include <muda/container.h>
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#include <muda/ext/linear_system.h>
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using namespace muda;
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template <typename T, int dim>
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class InertialEnergy
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{
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public:
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InertialEnergy(int N, T m);
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InertialEnergy();
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~InertialEnergy();
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InertialEnergy(InertialEnergy &&rhs);
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InertialEnergy(const InertialEnergy &rhs);
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InertialEnergy &operator=(InertialEnergy &&rhs);
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void update_x(const DeviceBuffer<T> &x);
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void generate_hess();
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void update_x_tilde(const DeviceBuffer<T> &x_tilde);
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void update_m(T m);
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T val(); // Calculate the value of the energy
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const DeviceBuffer<T> &grad(); // Calculate the gradient of the energy
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const DeviceTripletMatrix<T, 1> &hess(); // Calculate the Hessian matrix of the energy
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private:
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// The implementation details of the VecAdder class are placed in the implementation class declared here.
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struct Impl;
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// The private pointer to the implementation class Impl
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std::unique_ptr<Impl> pimpl_;
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};

‎simulators/7_self_contact/include/NeoHookeanEnergy.h‎

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#pragma once
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#include <memory>
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#include <Eigen/Dense>
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#include "uti.h"
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#include "device_uti.h"
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template <typename T, int dim>
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class NeoHookeanEnergy
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{
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public:
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NeoHookeanEnergy(const std::vector<T> &x, const std::vector<int> &e, T mu, T lam);
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NeoHookeanEnergy();
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~NeoHookeanEnergy();
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NeoHookeanEnergy(NeoHookeanEnergy &&rhs);
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NeoHookeanEnergy(const NeoHookeanEnergy &rhs);
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NeoHookeanEnergy &operator=(NeoHookeanEnergy &&rhs);
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void update_x(const DeviceBuffer<T> &x);
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void init_vol_IB();
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T val(); // Calculate the value of the energy
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const DeviceBuffer<T> &grad(); // Calculate the gradient of the energy
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const DeviceTripletMatrix<T, 1> &hess(); // Calculate the Hessian matrix of the energy
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T init_step_size(const DeviceBuffer<T> &p); // Calculate the initial step size for the line search
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private:
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struct Impl;
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std::unique_ptr<Impl> pimpl_;
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// static __device__ void polar_svd(const Eigen::Matrix<T, dim, dim> &F, Eigen::Matrix<T, dim, dim> &U, Eigen::Matrix<T, dim, dim> &V, Eigen::Matrix<T, dim, 1> &s);
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// static __device__ Eigen::Matrix<T, dim, 1> dPsi_div_dsigma(const Eigen::Matrix<T, dim, 1> &s, T mu, T lam);
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// static __device__ Eigen::Matrix<T, dim, dim> d2Psi_div_dsigma2(const Eigen::Matrix<T, dim, 1> &s, T mu, T lam);
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// static __device__ T B_left_coef(const Eigen::Matrix<T, dim, 1> &s, T mu, T lam);
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// static __device__ T Psi(const Eigen::Matrix<T, dim, dim> &F, T mu, T lam);
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// static __device__ Eigen::Matrix<T, dim, dim> dPsi_div_dF(const Eigen::Matrix<T, dim, dim> &F, T mu, T lam);
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// static __device__ Eigen::Matrix<T, 4, 4> d2Psi_div_dF2(const Eigen::Matrix<T, dim, dim> &F, T mu, T lam);
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// static __device__ Eigen::Matrix<T, 6, 1> dPsi_div_dx(const Eigen::Matrix<T, dim, dim> &P, const Eigen::Matrix<T, dim, dim> &IB);
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// static __device__ Eigen::Matrix<T, 6, 6> d2Psi_div_dx2(const Eigen::Matrix<T, 4, 4> &dP_div_dF, const Eigen::Matrix<T, dim, dim> &IB);
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};

‎simulators/7_self_contact/include/NeoHookean_auto.h‎

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#pragma once
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#include "Eigen/Dense"
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#include <muda/cub/device/device_reduce.h>
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#include <muda/container.h>
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#include <muda/muda.h>
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#include <muda/ext/linear_system.h>
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template <typename T>
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__device__ __host__ void NeoHookeanEnergyVal(T &E, const T &Mu, const T &Lambda, const Eigen::Vector<T, 6> &X, const Eigen::Matrix<T, 2, 2> &IB, const T &vol);
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template <typename T>
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__device__ __host__ void NeoHookeanEnergyGradient(Eigen::Vector<T, 6> &G, const T &Mu, const T &Lambda, const Eigen::Vector<T, 6> &X, const Eigen::Matrix<T, 2, 2> &IB, const T &vol);
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template <typename T>
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__device__ __host__ void NeoHookeanEnergyHessian(Eigen::Matrix<T, 6, 6> &H, const T &Mu, const T &Lambda, const Eigen::Vector<T, 6> &X, const Eigen::Matrix<T, 2, 2> &IB, const T &vol);

‎simulators/7_self_contact/include/SparseMatrix.h‎

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#pragma once
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#include <vector>
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template <typename T>
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class SparseMatrix
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{
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public:
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SparseMatrix(int size);
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SparseMatrix();
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~SparseMatrix();
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SparseMatrix(SparseMatrix<T> &&rhs);
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SparseMatrix<T> &operator=(SparseMatrix<T> &&rhs);
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SparseMatrix<T> &operator=(SparseMatrix<T> &rhs);
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SparseMatrix<T> &operator*(const T &a);
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SparseMatrix(const SparseMatrix<T> &rhs);
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void set_value(int row, int col, T val, int loc);
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void set_diagonal(T val);
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const std::vector<int> &get_row_buffer() const;
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const std::vector<int> &get_col_buffer() const;
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const std::vector<T> &get_val_buffer() const;
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std::vector<int> &set_row_buffer();
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std::vector<int> &set_col_buffer();
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std::vector<T> &set_val_buffer();
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SparseMatrix<T> &combine(const SparseMatrix<T> &other);
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int get_size() const;
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private:
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int size;
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std::vector<int> row_idx;
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std::vector<int> col_idx;
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std::vector<T> val;
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};

‎simulators/7_self_contact/include/SpringEnergy.h‎

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#pragma once
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#include <memory>
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#include <vector>
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#include <Eigen/Dense>
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#include "uti.h"
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#include "device_uti.h"
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template <typename T, int dim>
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class SpringEnergy
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{
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public:
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SpringEnergy(const std::vector<T> &x, const std::vector<T> &m, const std::vector<int> &DBC, T k);
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SpringEnergy();
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~SpringEnergy();
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SpringEnergy(SpringEnergy &&rhs);
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SpringEnergy(const SpringEnergy &rhs);
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SpringEnergy &operator=(SpringEnergy &&rhs);
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void update_x(const DeviceBuffer<T> &x);
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void update_DBC_target(const std::vector<T> &DBC_target);
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void update_k(T new_k);
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T val(); // Calculate the value of the energy
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const DeviceBuffer<T> &grad(); // Calculate the gradient of the energy
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const DeviceTripletMatrix<T, 1> &hess(); // Calculate the Hessian matrix of the energy
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private:
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struct Impl;
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std::unique_ptr<Impl> pimpl_;
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};

‎simulators/7_self_contact/include/device_uti.h‎

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#include <muda/muda.h>
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#include <muda/container.h>
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#include <muda/cub/device/device_reduce.h>
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#include <Eigen/Dense>
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// utility functions
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template <typename T>
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T devicesum(const muda::DeviceBuffer<T> &buffer);
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template <typename T, int Size>
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void __device__ make_PSD(const Eigen::Matrix<T, Size, Size> &hess, Eigen::Matrix<T, Size, Size> &PSD);

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