diff --git a/mindspore/profiler/parser/integrator.py b/mindspore/profiler/parser/integrator.py
index 45750f909b..45e880ae73 100644
--- a/mindspore/profiler/parser/integrator.py
+++ b/mindspore/profiler/parser/integrator.py
@@ -498,10 +498,6 @@ class BaseTimelineGenerator:
         'op_exe_times': 0
     }
 
-    def __init__(self, profiling_dir, device_id):
-        self._profiling_dir = profiling_dir
-        self._device_id = device_id
-
     def _load_timeline_data(self):
         """Load timeline data from file."""
 
@@ -640,6 +636,17 @@ class GpuTimelineGenerator(BaseTimelineGenerator):
     _output_gpu_activity_info_file_path = "gpu_activity_data_{}.csv"
     _activity_keys_list = []
 
+    def __init__(self, profiling_dir, device_id):
+        self._profiling_dir = profiling_dir
+        self._device_id = device_id
+        self._timeline_meta = []
+        self._timeline_summary = {
+            'total_time': 0,
+            'num_of_streams': 0,
+            'num_of_ops': 0,
+            'op_exe_times': 0
+            }
+
     def _get_and_validate_path(self, file_name):
         """Generate op or activity file path from file name, and validate this path."""
         file_path = os.path.join(
@@ -678,7 +685,7 @@ class GpuTimelineGenerator(BaseTimelineGenerator):
             timeline_dict['args'] = args_dict
         else:
             # Update total time of operator execution.
-            self._timeline_summary['total_time'] += dur
+            self._timeline_summary['total_time'] += dur / factor
             self._timeline_summary['op_exe_times'] += 1
 
         self._timeline_meta.append(timeline_dict)
@@ -744,15 +751,7 @@ class GpuTimelineGenerator(BaseTimelineGenerator):
 
 
     def init_timeline(self):
-        """
-        Init timeline metadata, adding all collected info.
-
-        Args:
-            all_reduce_info (list[list]): The metadata of AllReduce operator.
-            framework_info (dict): The framework metadata.
-            aicpu_info (dict): The metadata of AICPU operator.
-            min_cycle_counter (float): The minimum cycle counter of the timeline.
-        """
+        """Init timeline metadata, adding all collected info."""
         timeline_list = self._load_timeline_data()
 
         # Init a dict for counting the num of streams.
@@ -771,6 +770,10 @@ class AscendTimelineGenerator(BaseTimelineGenerator):
     _display_filename = 'ascend_timeline_display_{}.json'
     _timeline_summary_filename = 'ascend_timeline_summary_{}.json'
 
+    def __init__(self, profiling_dir, device_id):
+        self._profiling_dir = profiling_dir
+        self._device_id = device_id
+
     def _load_timeline_data(self):
         """Load timeline data from file."""
         file_path = os.path.join(
diff --git a/mindspore/profiler/profiling.py b/mindspore/profiler/profiling.py
index 8b4f970cde..4aa96be51a 100644
--- a/mindspore/profiler/profiling.py
+++ b/mindspore/profiler/profiling.py
@@ -286,10 +286,18 @@ class Profiler:
         """Used for gpu, generate timeline info, write to json format file."""
         try:
             size_limit = 100 * 1024 * 1024  # 100MB
-            timeline_generator = GpuTimelineGenerator(self._output_path, self._dev_id)
-            timeline_generator.init_timeline()
-            timeline_generator.write_timeline(size_limit)
-            timeline_generator.write_timeline_summary()
+            #stastic the number of dev_id
+            file_list = os.listdir(self._output_path)
+            dev_id_list = []
+            for file_name in file_list:
+                if file_name.startswith('gpu_op_detail'):
+                    _dev_id = file_name.split('.')[0].split('_')[-1]
+                    dev_id_list.append(_dev_id)
+            for dev_id in dev_id_list:
+                timeline_generator = GpuTimelineGenerator(self._output_path, dev_id)
+                timeline_generator.init_timeline()
+                timeline_generator.write_timeline(size_limit)
+                timeline_generator.write_timeline_summary()
         except (ProfilerIOException, ProfilerFileNotFoundException, RuntimeError) as err:
             logger.warning('Fail to write timeline data: %s', err)
             raise RuntimeError('Fail to write timeline data.')