As data processing evolves towards large scale, distributed platforms, the network will necessarily play a substantial role in achieving efficiency and performance. Increasingly, switches, network cards, and protocols are becoming more flexible while programmability at all levels (aka, software defined networks) opens up many possibilities to tailor the network to data processing applications and to push processing down to the network elements.
In this paper, we propose DPI, an interface providing a set of simple yet powerful abstractions flexible enough to exploit features of modern networks (e.g., RDMA or in-network processing) suitable for data processing. Mirroring the concept behind the Message Passing Interface (MPI) used extensively in high-performance computing, DPI is an interface definition rather than an implementation so as to be able to bridge different networking technologies and to evolve with them. In the paper we motivate and discuss key primitives of the interface and present a number of use cases that show the potential of DPI for data-intensive applications, such as analytic engines and distributed database systems.

Examples can be found in the src/test/examples/ folder.

Simple example of appending to a buffer:

  string buffer_name = "buffer";
  char data1[] = "Hello ";
  char data2[] = "World!";
  int rcv_node_id = 1; //ID is mapped to a concrete node in cluster spec
  DPI_Context context;
  DPI_Init(context); 
  DPI_Create_buffer(buffer_name, rcv_node_id, context);
  DPI_Append(buffer_name, (void*)data1, sizeof(data1), context);
  DPI_Append(buffer_name, (void*)data2, sizeof(data2), context);
  DPI_Close_buffer(buffer_name, context);

  size_t buffer_size;
  void* buffer_ptr;
  DPI_Get_buffer(buffer_name, buffer_size, buffer_ptr, context);

  for(size_t i = 0; i < buffer_size; i++)
  {
    cout << ((char*)buffer_ptr)[i];
  }
  DPI_Finalize(context);