diff --git a/tutorials/source_en/advanced_use/performance_profiling.md b/tutorials/source_en/advanced_use/performance_profiling.md
index b8cd049a9f9338e1fba399c9e7bc244ec5808969..f51f31e21189f7378ea5a54130d3bd770fdfbcb1 100644
--- a/tutorials/source_en/advanced_use/performance_profiling.md
+++ b/tutorials/source_en/advanced_use/performance_profiling.md
@@ -29,7 +29,7 @@ Performance data like operators' execution time is recorded in files and can be
 
 ## Preparing the Training Script
 
-To enable the performance profiling of neural networks, MindSpore Profiler APIs should be added into the script. At first, the MindSpore `Profiler` object need to be set after set context and before the network initialization. Then, at the end of the training, `Profiler.analyse()` should be called to finish profiling and generate the perforamnce analyse results.
+To enable the performance profiling of neural networks, MindSpore Profiler APIs should be added into the script. At first, the MindSpore `Profiler` object need to be set after set context and before the network and HCCL initialization. Then, at the end of the training, `Profiler.analyse()` should be called to finish profiling and generate the perforamnce analyse results.
 
 The sample code is as follows:
 
diff --git a/tutorials/source_zh_cn/advanced_use/performance_profiling.md b/tutorials/source_zh_cn/advanced_use/performance_profiling.md
index 0d8fb2d26e5e56c578a7f95860d039f73bf2ba63..6eef098c28019cca717e839afe1f0f4608ea6b96 100644
--- a/tutorials/source_zh_cn/advanced_use/performance_profiling.md
+++ b/tutorials/source_zh_cn/advanced_use/performance_profiling.md
@@ -31,7 +31,7 @@
 ## 准备训练脚本
 
 为了收集神经网络的性能数据，需要在训练脚本中添加MindSpore Profiler相关接口。  
-- 在`set_context`之后和初始化网络之前，需要初始化MindSpore `Profiler`对象。
+- `set_context`之后，初始化网络和HCCL之前，需要初始化MindSpore `Profiler`对象。
 - 在训练结束后，调用`Profiler.analyse()`停止性能数据收集并生成性能分析结果。
 
 样例代码如下：