Example 4: Provide custom spezializations

In this example, we show how to write a specialized mpi_reduce_into for a custom type.

#include <mpi/mpi.hpp>
#include <iostream>
#include <vector>
 
// Custom type.
class foo {
  public:
  // Constructor.
  foo(int x = 5) : x_(x) {}
 
  // Get the value stored in the class.
  int x() const { return x_; }
 
  // Specialization of mpi_reduce_into for the custom type.
  friend void mpi_reduce_into(foo const &f_in, foo &f_out, mpi::communicator c = {}, int root = 0, bool all = false, MPI_Op op = MPI_SUM) {
    mpi::reduce_into(f_in.x_, f_out.x_, c, root, all, op);
  }
 
  private:
  int x_;
};
 
int main(int argc, char *argv[]) {
  // initialize MPI environment
  mpi::environment env(argc, argv);
  mpi::communicator world;
 
  // create a vector of foo objects
  std::vector<foo> vec {foo{1}, foo{2}, foo{3}, foo{4}, foo{5}};
 
  // reduce the vector of foo objects
  auto result = mpi::reduce(vec, world);
 
  // print the result on rank 0
  if (world.rank() == 0) {
    std::cout << "Reduced vector: ";
    for (auto const &f : result) std::cout << f.x() << " ";
    std::cout << "\n";
  }
}

Output (running with -n 4):

Reduced vector: 4 8 12 16 20

Note that by providing a simple mpi_reduce_into for our custom foo type, we are able to reduce a std::vector of foo objects without any additional work.

Under the hood, each foo object is reduced spearately using the above specialization. For large amounts of data or in performance critical code sections, this might not be desired. In such a case, it is usally better to make the type MPI compatible such that the reduction can be done with a single call to MPI C library. See Example 3: Custom type and operator for more details.