diff --git a/README_CN.md b/README_CN.md
index a96ddb0275fa58814184dccb0b2617b627dee443..2d749bc95292ae8a9f547ab4d51c03ccbf57550c 100644
--- a/README_CN.md
+++ b/README_CN.md
@@ -23,7 +23,7 @@ MindInsight为MindSpore提供了简单易用的调优调试能力。在训练过
 请从[MindSpore下载页面](https://www.mindspore.cn/versions)下载并安装whl包。
 
 ```
-pip install mindinsight-{version}-cp37-cp37m-linux_{arch}.whl
+pip install -U mindinsight-{version}-cp37-cp37m-linux_{arch}.whl
 ```
 
 更多MindInsight的安装方法，请点击[安装教程](https://www.mindspore.cn/install/)中的MindInsight章节进行查看。
diff --git a/mindinsight/backend/config/gunicorn_conf.py b/mindinsight/backend/config/gunicorn_conf.py
index 37221a4ef59081f70a6907c9f8b41c8b1004920d..0993a0b2692be4ccf343f18b10d8457fa703eb05 100644
--- a/mindinsight/backend/config/gunicorn_conf.py
+++ b/mindinsight/backend/config/gunicorn_conf.py
@@ -15,9 +15,13 @@
 """Config file for gunicorn."""
 
 import os
+import multiprocessing
+import signal
 import threading
+import time
 from importlib import import_module
 
+import psutil
 import gunicorn
 
 
@@ -43,3 +47,44 @@ def on_starting(server):
     hook_module = import_module('mindinsight.utils.hook')
     for hook in hook_module.HookUtils.instance().hooks():
         threading.Thread(target=hook.on_startup, args=(server.log,)).start()
+
+
+def post_fork(server, worker):
+    """
+    Launch a process to listen worker after gunicorn fork worker.
+
+    Children processes of gunicorn worker should be killed when worker has been killed
+    because gunicorn master murders this worker for some reasons such as worker timeout.
+
+    Args:
+        server (Arbiter): gunicorn server instance.
+        worker (ThreadWorker): worker instance.
+    """
+    def murder_worker_children_processes():
+        processes_to_kill = []
+        # sleep 3 seconds so that all worker children processes have been launched.
+        time.sleep(3)
+        process = psutil.Process(worker.pid)
+        for child in process.children(recursive=True):
+            if child.pid != os.getpid():
+                processes_to_kill.append(child)
+        while True:
+            if os.getppid() != worker.pid:
+                current_worker_pid = os.getppid()
+                for proc in processes_to_kill:
+                    server.log.info("Original worker pid: %d, current worker pid: %d, stop process %d",
+                                    worker.pid, current_worker_pid, proc.pid)
+                    try:
+                        proc.send_signal(signal.SIGKILL)
+                    except psutil.NoSuchProcess:
+                        continue
+                    except psutil.Error as ex:
+                        server.log.error("Stop process %d failed. Detail: %s.", proc.pid, str(ex))
+                server.log.info("%d processes have been killed.", len(processes_to_kill))
+                break
+            time.sleep(1)
+
+    listen_process = multiprocessing.Process(target=murder_worker_children_processes,
+                                             name="murder_worker_children_processes")
+    listen_process.start()
+    server.log.info("Server pid: %d, start to listening.", server.pid)
diff --git a/mindinsight/datavisual/data_transform/tensor_container.py b/mindinsight/datavisual/data_transform/tensor_container.py
index 0f865800e95cc6e47bbe63fe6937fc040c6b97e0..0bdc94d8f6475dc42f051357688a5c6ce14d8e9d 100644
--- a/mindinsight/datavisual/data_transform/tensor_container.py
+++ b/mindinsight/datavisual/data_transform/tensor_container.py
@@ -193,8 +193,10 @@ class TensorContainer:
         self._stats = get_statistics_from_tensor(self._np_array)
         original_buckets = calc_original_buckets(self._np_array, self._stats)
         self._count = sum(bucket.count for bucket in original_buckets)
-        self._max = self._stats.max
-        self._min = self._stats.min
+        # convert the type of max and min value to np.float64 so that it cannot overflow
+        # when calculating width of histogram.
+        self._max = np.float64(self._stats.max)
+        self._min = np.float64(self._stats.min)
         self._histogram = Histogram(tuple(original_buckets), self._max, self._min, self._count)
 
     @property