Out-of-band Communication

Typically, Ray actor communication is done through actor method calls and data is shared through the distributed object store. However, in some use cases out-of-band communication can be useful.

Wrapping Library Processes

Many libraries already have mature, high-performance internal communication stacks and they leverage Ray as a language-integrated actor scheduler. The actual communication between actors is mostly done out-of-band using existing communication stacks. For example, Horovod-on-Ray uses NCCL or MPI-based collective communications, and RayDP uses Spark's internal RPC and object manager. See Ray Distributed Library Patterns <https://www.anyscale.com/blog/ray-distributed-library-patterns>_ for more details.

Ray Collective

Ray's collective communication library (\ ray.util.collective\ ) allows efficient out-of-band collective and point-to-point communication between distributed CPUs or GPUs. See :ref:Ray Collective <ray-collective> for more details.

HTTP Server

You can start an HTTP server inside the actor and expose HTTP endpoints to clients so users outside of the Ray cluster can communicate with the actor.

.. tab-set::

.. tab-item:: Python

    .. literalinclude:: ../doc_code/actor-http-server.py

Similarly, you can expose other types of servers as well (e.g., gRPC servers).

Limitations

When using out-of-band communication with Ray actors, keep in mind that Ray does not manage the calls between actors. This means that functionality like distributed reference counting will not work with out-of-band communication, so you should take care not to pass object references in this way.