C++ program with derived data type (nested class object) container using MPI/OpenMP

I have developed a program in C++11 and I want to speed up the performance.

I will use a simple example to show the structure of the program (not complete).

   //main.cpp
   #include "a.h"
   int main()
   {
     std::vector<a> a_container;
     for (auto i=0; i< 10K; i++)
     {
       a a_obj;
       a_container.push_back(a_obj);
     }

     for(time = 1; time< long_time; time++)
     {
       //i used openmp here already
       for (auto i=0; i< 10K; i++)
       {
         a_container[i].dosomething();
       }
       for (auto i=0; i< 10K; i++)
       {
         a_container[i].update();
       }
     }
     return 1;
   }
   //a.cpp
   //a.h
   #include "b.h"
   class a
   {
     int d;
     b b_obj;
     int dosomething();
   }
   //b.cpp
   //b.h

   class b
   {
      int c;
      double d;
      int dosomething();
   }

So in order to speed up the program, I want to use both MPI and OpenMP, mainly for the loop (could be up to 1 million~1 billion instances).

The class object a and b both contain complex member variables (standard and other containers, etc.) and functions.

By using OpenMP, I can take advantage of one HPC node with all cores/threads. But if I want to use MPI, I need to distribute all the instances to many nodes.

I haven't found a good solution to this yet, please provide some suggestion. Thanks.