Initial support for federated learning (#7831)

Federated learning plugin for xgboost:
* A gRPC server to aggregate MPI-style requests (allgather, allreduce, broadcast) from federated workers.
* A Rabit engine for the federated environment.
* Integration test to simulate federated learning.

Additional followups are needed to address GPU support, better security, and privacy, etc.

python-package/xgboost/federated.py

@@ -0,0 +1,36 @@
+"""XGBoost Federated Learning related API."""
+
+from .core import _LIB, _check_call, c_str, build_info, XGBoostError
+
+
+def run_federated_server(port: int,
+                         world_size: int,
+                         server_key_path: str,
+                         server_cert_path: str,
+                         client_cert_path: str) -> None:
+    """Run the Federated Learning server.
+
+    Parameters
+    ----------
+    port : int
+        The port to listen on.
+    world_size: int
+        The number of federated workers.
+    server_key_path: str
+        Path to the server private key file.
+    server_cert_path: str
+        Path to the server certificate file.
+    client_cert_path: str
+        Path to the client certificate file.
+    """
+    if build_info()['USE_FEDERATED']:
+        _check_call(_LIB.XGBRunFederatedServer(port,
+                                               world_size,
+                                               c_str(server_key_path),
+                                               c_str(server_cert_path),
+                                               c_str(client_cert_path)))
+    else:
+        raise XGBoostError(
+            "XGBoost needs to be built with the federated learning plugin "
+            "enabled in order to use this module"
+        )