diff --git a/doc/fluid/howto/optimization/cpu_profiling_cn.md b/doc/fluid/howto/optimization/cpu_profiling_cn.md
index 8266dec3c6125a09b90ac0ccd4aa5464f5c7db31..198a05a79e19227e90eaafe116217a164cd51a7d 100644
--- a/doc/fluid/howto/optimization/cpu_profiling_cn.md
+++ b/doc/fluid/howto/optimization/cpu_profiling_cn.md
@@ -1,3 +1,5 @@
+# CPU性能调优
+
 此教程会介绍如何使用Python的cProfile包、Python库yep、Google perftools来进行性能分析 (profiling) 与调优（performance tuning）。
 
 Profling 指发现性能瓶颈。系统中的瓶颈可能和程序员开发过程中想象的瓶颈相去甚远。Tuning 指消除瓶颈。性能优化的过程通常是不断重复地 profiling 和 tuning。
@@ -8,7 +10,7 @@ PaddlePaddle 用户一般通过调用 Python API 编写深度学习程序。大
 * Python 与 C++ 混合代码的性能分析
 
 
-# Python代码的性能分析
+## Python代码的性能分析
 
 ### 生成性能分析文件
 
diff --git a/doc/fluid/howto/optimization/cpu_profiling_en.md b/doc/fluid/howto/optimization/cpu_profiling_en.md
index e95556dd608b7ff0a3eb18873df0015a2da94e7c..216694965b3c878a8a5f3ccd2a0cba8d21d9ce05 100644
--- a/doc/fluid/howto/optimization/cpu_profiling_en.md
+++ b/doc/fluid/howto/optimization/cpu_profiling_en.md
@@ -1,3 +1,5 @@
+# Tune CPU performance
+
 This tutorial introduces techniques we use to profile and tune the
 CPU performance of PaddlePaddle.  We will use Python packages
 `cProfile` and `yep`, and Google's `perftools`.
@@ -14,7 +16,7 @@ the profiling and tuning of
 1. the Python code and
 1. the mixture of Python and C++ code.
 
-# Profiling the Python Code
+## Profiling the Python Code
 
 ### Generate the Performance Profiling File