Add omp target to omp parallel for in AMR applications

[ouankou]

In 3D-LBM-AMR and Gamer, omp parallel for is widely used for computing on CPU. If the involved data are properly mapped, we can offload the computing to GPU. However, both of them use the complex data structure to hold both data and computing methods. https://github.com/ouankou/3D-LBM-AMR/blob/master/src/Node.h

class Node
{
public: 
    double u0,u1,u2,usqr,rho,xcoord,ycoord,zcoord,nu0;
//    double u0_prev,u1_prev,u_error,u_sum;
//  double m1eq,m2eq,m4eq,m6eq,m7eq,m8eq;//moments (starting from 0, to 8)
//  double m1,m2,m4,m6,m7,m8;//moments (starting from 0, to 8)
//  double Q11,Q12,Q21,Q22,Q,Smag,OmegaStar,Cs;
    double Smag,OmegaStar,Cs;
//  double PI11, PI22, PI33, PI12, PI13, PI23;
//  double PI11,PI22,PI12;
    double u0avg, u1avg, u2avg;
    int image,level,outnumb,edge;
    bool feqflag;//1 if MeqToFeq was used
    Node * Parent;
    std::vector<double> f,feq,ftemp,delta,m,meq;
    std::vector<Node *> nb;
    Node * child[8];
    Node();
    Node(Node& parent);
    void Initialize(double u0_ini,double u1_ini,double u2_ini,double rho_ini,int x,int y,int z);
    void SetImage(int Image_val);
    void ComputeM();//compute M from f and meq
    void ComputeFeq();
    void Collide();
    void ComputeMacros();
    void VelAverage(int tStep);//compute time averaged velocity
    void Symmetry();
    void Periodic(Node *);
    void BounceBack();
    void CurvedB();
    void BBForce(double& ForceX,double& ForceY,double& ForceZ,int BBimage);
    void BoundaryMacro();
    void InletOutlet();
    void RegularizedBoundary();
    void DeleteNode();
    void Refine();
    void ChildNeighbor();
    void Stream1();
    void Stream2();
    void SpatialInterp1();
    void SpatialInterp2();
    void SpatialAverage();
    void TemporalInterp();
    void TemporalInterp2();
    void MeqToFeq();
    void MToF();
    void ComputeDelta(double obX,double obY,double obX2,double obY2,double R);
//  void Outlet2();

};

It has a 3D array of this object. We could either figure out a way to map this 3D array to GPU, which would need much less changes to the code, or pick up the involve data to create a new data array and rewrite a kernel function based current computing methods.