diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc
index b3d9e22dba8d244f5e57267a527de0bbdc534996..d812203c041ac1f2caa5b4685bdf48b8766fe1a0 100644
--- a/paddle/fluid/pybind/pybind.cc
+++ b/paddle/fluid/pybind/pybind.cc
@@ -1454,7 +1454,7 @@ All parameter, weight, gradient are variables in Paddle.
                      "number on your machine is %d",
                      dev_id, platform::GetCUDADeviceCount(),
                      platform::GetCUDADeviceCount());
-                 std::exit(-1);
+                 // std::exit(-1);
                }
              }
 
diff --git a/python/paddle/distributed/fleet/meta_optimizers/common.py b/python/paddle/distributed/fleet/meta_optimizers/common.py
index 9befdfff04bef14e756f41681f838ea0959d3759..3df1f127b31649c6fdf7feac858ab37161ca1977 100644
--- a/python/paddle/distributed/fleet/meta_optimizers/common.py
+++ b/python/paddle/distributed/fleet/meta_optimizers/common.py
@@ -73,9 +73,30 @@ class CollectiveHelper(object):
         other_endpoints.remove(current_endpoint)
         block = program.global_block()
         if core.is_compiled_with_cuda():
-            if rank == 0 and wait_port:
-                wait_server_ready(other_endpoints)
-            nccl_id_var = block.create_var(
+            if not wait_port:
+                temp_var = block.create_var(
+                    name=unique_name.generate('temp_var'),
+                    dtype=core.VarDesc.VarType.INT32,
+                    persistable=False,
+                    stop_gradient=True)
+                block.append_op(
+                    type='fill_constant',
+                    inputs={},
+                    outputs={'Out': [temp_var]},
+                    attrs={
+                        'shape': [1],
+                        'dtype': temp_var.dtype,
+                        'value': 1,
+                        'force_cpu': False,
+                        OP_ROLE_KEY: OpRole.Forward
+                    })
+                block.append_op(
+                    type='c_allreduce_sum',
+                    inputs={'X': [temp_var]},
+                    outputs={'Out': [temp_var]},
+                    attrs={'ring_id': 3,
+                           OP_ROLE_KEY: OpRole.Forward})
+            comm_id_var = block.create_var(
                 name=unique_name.generate('nccl_id'),
                 persistable=True,
                 type=core.VarDesc.VarType.RAW)
@@ -100,9 +121,7 @@ class CollectiveHelper(object):
                     OP_ROLE_KEY: OpRole.Forward
                 })
         elif core.is_compiled_with_npu():
-            endpoint_to_index_map = {
-                e: idx for idx, e in enumerate(endpoints)
-            }
+            endpoint_to_index_map = {e: idx for idx, e in enumerate(endpoints)}
             block.append_op(
                 type='c_comm_init_hcom',
                 inputs={},