# Commnunication initialize with mscclpp API

In this tutorial, you will write a simple program to initialize communication between eight GPUs using MSCCL++ C++ API. You will also learn how to use the Python API to initialize communication.

## Prerequisites
A system with eight GPUs is required to run this tutorial.

Also make sure that you have installed MSCCL++ on your system. If not, please follow the [quick start](../quickstart.md).

## Initialize Communication with C++ API
We will setup a mesh topology with eight GPUs. Each GPU will be connected to its neighbors. The following code shows how to initialize communication with MSCCL++ C++ API.

```cpp
#include <mscclpp/core.hpp>
#include <mscclpp/gpu_utils.hpp>
#include <mscclpp/port_channel.hpp>

#include <memory>
#include <string>
#include <vector>

template <class T>
using DeviceHandle = mscclpp::DeviceHandle<T>;
__constant__ DeviceHandle<mscclpp::PortChannel> constPortChans[8];

void setupMeshTopology(int rank, int worldsize, void* data, size_t dataSize) {
  std::string ip_port = "10.0.0.4:50000";
  auto bootstrap = std::make_shared<mscclpp::TcpBootstrap>(rank, worldsize);
  bootstrap->initialize(ip_port);
  mscclpp::Communicator comm(bootstrap);
  mscclpp::ProxyService proxyService;

  std::vector<mscclpp::SemaphoreId> semaphoreIds;
  std::vector<mscclpp::RegisteredMemory> localMemories;
  std::vector<std::shared_future<std::shared_ptr<mscclpp::Connection>>> connections(world_size);
  std::vector<std::shared_future<mscclpp::RegisteredMemory>> remoteMemories;

  for (int r = 0; r < world_size; ++r) {
    if (r == rank) continue;
    mscclpp::Transport transport = mscclpp::Transport::CudaIpc;
    // Connect with all other ranks
    connections[r] = comm.connect(transport, r);
    auto memory = comm.registerMemory(data, dataSize, mscclpp::Transport::CudaIpc | ibTransport);
    localMemories.push_back(memory);
    comm.sendMemory(memory, r);
    remoteMemories.push_back(comm.recvMemory(r));
  }

  for (int r = 0; r < world_size; ++r) {
    if (r == rank) continue;
    auto sema = communicator->buildSemaphore(connections[r].get(), r).get();
    semaphoreIds.push_back(proxyService->addSemaphore(sema));
  }

  std::vector<DeviceHandle<mscclpp::PortChannel>> portChannels;
  for (size_t i = 0; i < semaphoreIds.size(); ++i) {
    portChannels.push_back(mscclpp::deviceHandle(mscclpp::PortChannel(
        proxyService.portChannel(semaphoreIds[i]), proxyService.addMemory(remoteMemories[i].get()),
        proxyService.addMemory(localMemories[i]))));
  }

  if (portChannels.size() > sizeof(constPortChans) / sizeof(DeviceHandle<mscclpp::PortChannel>)) {
    std::runtime_error("unexpected error");
  }
  CUDACHECK(cudaMemcpyToSymbol(constPortChans, portChannels.data(),
                              sizeof(DeviceHandle<mscclpp::PortChannel>) * portChannels.size()));
}
```