diff --git a/pytorch_lightning/models/trainer.py b/pytorch_lightning/models/trainer.py
index d03d7c18..e5a0d7aa 100644
--- a/pytorch_lightning/models/trainer.py
+++ b/pytorch_lightning/models/trainer.py
@@ -336,8 +336,10 @@ class Trainer(TrainerIO):
 
         # set up server using proc 0's ip address
         # try to init for 20 times at max in case ports are taken
-        ip = self.__get_root_node_ip(self.proc_rank, self.nb_gpu_nodes)
-        self.__init_tcp_connection(ip)
+        ip_file_dir = os.path.join(self.cluster.log_path, 'ip_tables')
+        dist.init_process_group("nccl", init_method=f'file://{ip_file_dir}', rank=self.proc_rank,
+                                world_size=self.world_size)
+        # self.__init_tcp_connection(ip_file_dir)
 
         # CHOOSE OPTIMIZER
         # filter out the weights that were done on gpu so we can load on good old cpus
@@ -362,16 +364,16 @@ class Trainer(TrainerIO):
         # continue training routine
         self.__run_pretrain_routine(model)
 
-    def __init_tcp_connection(self, ip, port=12000, tries=0):
+    def __init_tcp_connection(self, path, port=12000, tries=0):
         if tries > 20:
             raise RuntimeError('Failed to connect using 20 different ip addresses')
 
         try:
-            dist.init_process_group("nccl", init_method=f'tcp://{ip}:{port}', rank=self.proc_rank, world_size=self.world_size)
+            dist.init_process_group("nccl", init_method=f'file://{path}:{port}', rank=self.proc_rank, world_size=self.world_size)
         except RuntimeError as e:
             # port taken
             warnings.warn(f'port {port} taken, trying port {port}...')
-            self.__init_tcp_connection(ip, port + 1, tries + 1)
+            self.__init_tcp_connection(path, port + 1, tries + 1)
 
     def __get_root_node_ip(self, world_gpu_nb, nb_gpu_nodes):
         """