diff --git a/mindspore/ccsrc/profiler/device/ascend/parallel_strategy_profiling.cc b/mindspore/ccsrc/profiler/device/ascend/parallel_strategy_profiling.cc
index 1822635d672..23d9e9f622f 100644
--- a/mindspore/ccsrc/profiler/device/ascend/parallel_strategy_profiling.cc
+++ b/mindspore/ccsrc/profiler/device/ascend/parallel_strategy_profiling.cc
@@ -38,7 +38,7 @@ namespace profiler {
 namespace ascend {
 bool has_save_parallel_strategy = false;
 bool has_got_parallel_strategy_data = false;
-bool profiling_parallel_strategy_enabled = false;
+bool profiling_parallel_strategy_enabled = true;
 irpb::ProfilingParallel cache_profiling_parallel_pb;
 
 bool IsProfilingParallelStrategyEnabled() {
@@ -168,7 +168,7 @@ void SaveParallelStrategyToFile() {
   if (rank_id.empty()) {
     rank_id = "0";
   }
-  std::string file_path = dir_path + std::string("/parallel_strategy_") + std::string(rank_id) + std::string(".json");
+  std::string file_path = dir_path + std::string("/parallel_strategy_pb_") + std::string(rank_id) + std::string(".bin");
 
   MS_LOG(INFO) << "Start to write parallel strategy string, file path is " << file_path;
   std::ofstream ofs(file_path);
@@ -178,9 +178,7 @@ void SaveParallelStrategyToFile() {
     return;
   }
 
-  std::string profiling_parallel_str;
-  google::protobuf::util::MessageToJsonString(cache_profiling_parallel_pb, &profiling_parallel_str);
-  ofs << profiling_parallel_str;
+  ofs << cache_profiling_parallel_pb.SerializeAsString();
   ofs.close();
 
   ChangeFileMode(file_path, S_IRUSR | S_IWUSR);
diff --git a/mindspore/python/mindspore/profiler/parser/integrator.py b/mindspore/python/mindspore/profiler/parser/integrator.py
index 800bfb0f29c..7fc0c2aef6f 100644
--- a/mindspore/python/mindspore/profiler/parser/integrator.py
+++ b/mindspore/python/mindspore/profiler/parser/integrator.py
@@ -1845,7 +1845,9 @@ class AscendTimelineGenerator(BaseTimelineGenerator):
     def _pynative_get_step_timeline_list(self, timeline_list):
         """Get step timeline list for pynative model."""
         step_list = []
-        if 'GetNext' not in timeline_list[0][self._op_name_idx]:
+        # The timeline starts with the GetNext op
+        if len(timeline_list) < 2 or 'GetNext' not in timeline_list[0][self._op_name_idx] and \
+                'GetNext' not in timeline_list[1][self._op_name_idx]:
             return step_list
         step = [-1, -1]
         step_num = 0
diff --git a/mindspore/python/mindspore/profiler/profiling.py b/mindspore/python/mindspore/profiler/profiling.py
index aec15e6c277..52e7c1401dd 100644
--- a/mindspore/python/mindspore/profiler/profiling.py
+++ b/mindspore/python/mindspore/profiler/profiling.py
@@ -17,11 +17,13 @@ import os
 import stat
 import time
 import json
+from google.protobuf.json_format import MessageToJson
 
 from mindspore import log as logger, context
 from mindspore.communication.management import GlobalComm, get_rank, get_group_size
 import mindspore._c_expression as c_expression
 import mindspore._c_dataengine as cde
+from mindspore.train.profiling_parallel_pb2 import ProfilingParallel
 from mindspore.profiler.common.exceptions.exceptions import ProfilerFileNotFoundException, \
     ProfilerIOException, ProfilerException, ProfilerRawFileException
 from mindspore.profiler.common.exceptions.exceptions import ProfilerPathErrorException
@@ -139,6 +141,7 @@ class Profiler:
         self._job_id_env = None
         self._filt_optype_names = ''
         self._output_path = ''
+        self._rank_size = 0
         _environment_check()
         # get device_id and device_target
         self._get_devid_rankid_and_devtarget()
@@ -156,8 +159,6 @@ class Profiler:
         self._decide_device_target(kwargs)
         if self.start_profile:
             self.start()
-        elif context.get_context("mode") == context.PYNATIVE_MODE:
-            raise RuntimeError("Pynative model does not support conditional collection of performance data.")
 
     def _decide_device_target(self, kwargs):
         """Complete Profiler initialization according to device_target"""
@@ -532,6 +533,8 @@ class Profiler:
                                    self._dev_id, self._rank_id, is_training_mode_flag)
         logger.info("Profiling: analyzing the operation FLOPs.")
         flops_parser.execute()
+        logger.info("Profiling: analyzing the parallel strategy.")
+        self._analyse_parallel_strategy()
 
     @staticmethod
     def _check_output_path(output_path):
@@ -578,6 +581,8 @@ class Profiler:
              >>>     def end(self, run_context):
              ...         self.profiler.analyse()
         """
+        if not self.start_profile and context.get_context("mode") == context.PYNATIVE_MODE:
+            raise RuntimeError("Pynative model does not support conditional collection of performance data.")
 
         self._start_time = int(time.time() * 10000000)
         logger.info("Profiling: start time: %d", self._start_time)
@@ -1104,3 +1109,20 @@ class Profiler:
         hccl_parse = HcclParser(hccl_path, self._dev_id, self._rank_id, self._output_path)
         hccl_parse.parse()
         logger.info("Analyse hccl info successfully.")
+
+    def _analyse_parallel_strategy(self):
+        """Analyse parallel strategy from proto binary to json."""
+        binary_file = os.path.join(self._output_path, 'parallel_strategy_pb_{}.bin'.format(self._rank_id))
+        binary_file = validate_and_normalize_path(binary_file)
+        if not os.path.isfile(binary_file):
+            return
+        with open(binary_file, 'rb') as f:
+            data = f.read()
+        parallel = ProfilingParallel()
+        parallel.ParseFromString(data)
+        parallel_json = MessageToJson(parallel)
+
+        json_file = os.path.join(self._output_path, 'parallel_strategy_{}.json'.format(self._rank_id))
+        with os.fdopen(os.open(json_file, os.O_WRONLY | os.O_CREAT, 0o660), 'w') as f:
+            f.write(parallel_json)
+        os.remove(binary_file)