diff --git a/fastdeploy/worker/worker_process.py b/fastdeploy/worker/worker_process.py
index 3750827a2d5..e744c4c7e1f 100644
--- a/fastdeploy/worker/worker_process.py
+++ b/fastdeploy/worker/worker_process.py
@@ -312,6 +312,18 @@ def _broadcast_model_weights_signal(self, src: int, group) -> int:
         value = model_weights_signal_tensor.numpy()[0]
         return int(value)
 
+    def _get_exist_task_flag(self) -> bool:
+        if self.nnode > 1:
+            return self.task_queue.read_finish_flag.get() == 1
+        else:
+            return self.exist_task_signal.value[0] == ExistTaskStatus.EXIST
+
+    def _update_exist_task_flag(self, flag: bool) -> None:
+        if self.nnode > 1:
+            self.task_queue.read_finish_flag.set(1 if flag else 0)
+        else:
+            self.exist_task_signal.value[0] = ExistTaskStatus.EXIST if flag else ExistTaskStatus.EMPTY
+
     def _tp_barrier_wait(self):
         if current_platform.is_xpu() or self.enable_overlap_schedule:
             self.task_queue.worker_process_tp_barrier.wait()
@@ -436,7 +448,7 @@ def event_loop_normal(self) -> None:
         self._init_eplb_signal()
         tp_size = self.parallel_config.tensor_parallel_size
         # Currently, only support single node
-        self.nnode = (tp_size + self.max_chips_per_node) // self.max_chips_per_node
+        self.nnode = (tp_size + self.max_chips_per_node - 1) // self.max_chips_per_node
         max_occupied_batch_index = 0
         tp_rank = self.local_rank % tp_size
 
@@ -454,16 +466,17 @@ def event_loop_normal(self) -> None:
             req_dicts = None
             self.worker_healthy_live_signal.value[tp_rank % self.max_chips_per_node] = int(time.time())
 
+            self._tp_barrier_wait() if tp_size > 1 else None
+
             # The first worker detects whether there are tasks in the task queue
             if tp_rank == 0:
                 if self.task_queue.exist_tasks():
                     if envs.ENABLE_V1_KVCACHE_SCHEDULER or not (
                         self.fd_config.enable_mm_runtime and self.worker.exist_prefill()
                     ):
-                        if self.nnode > 1:
-                            self.task_queue.read_finish_flag.set(1)
-                        else:
-                            self.exist_task_signal.value[0] = ExistTaskStatus.EXIST
+                        self._update_exist_task_flag(True)
+                else:
+                    self._update_exist_task_flag(False)
 
             # Synchronize the signal set by tp_rank0 visiable to other workers
             self._tp_barrier_wait() if tp_size > 1 else None
@@ -521,17 +534,14 @@ def event_loop_normal(self) -> None:
                             )  # 所有 Rank 已同步唤醒，启动权重更新流程
                     continue
 
-            if self.exist_task_signal.value[0] == ExistTaskStatus.EXIST or self.task_queue.read_finish_flag.get() == 1:
-                logger.info(f"Rank: {self.local_rank} Detected new requests.")
+            if self._get_exist_task_flag():
+                logger.debug(f"Rank: {self.local_rank} Detected new requests.")
 
                 tasks, read_finish = self.task_queue.get_tasks()
                 # Only one of all tp_size client will get read_finish == True.
                 if read_finish:
-                    # Reset the two signal.
-                    if self.nnode > 1:
-                        self.task_queue.read_finish_flag.set(0)
-                    else:
-                        self.exist_task_signal.value[0] = ExistTaskStatus.EMPTY
+                    self._update_exist_task_flag(False)
+                self._tp_barrier_wait() if tp_size > 1 else None
 
                 req_dicts, control_reqs = [], []
                 for req_dict, bsz in tasks: