diff --git a/paddle/majel/README.md b/paddle/majel/README.md
index 5539853056797284ca1fa5ef5ab16fa0059907f0..0f49b83c2ac724ac9d036d134d761c53b89a6260 100644
--- a/paddle/majel/README.md
+++ b/paddle/majel/README.md
@@ -48,7 +48,9 @@ int main()
 }
 ```
 
-In Majel, `DDimVar` is derived from `Dim`, `DArrayVar` is from `Array`.
+In Majel, `DDimVar` is derived from `Dim`, `DArrayVar` is from 
+`Array`.
+
 
 ```c++
 template<int i>
@@ -68,8 +70,8 @@ private:
     Dim<D> stride_;
     T* ptr_;
 };
-```
-
+``` 
+ 
 ```c++
 typedef boost::variant<GpuPlace, CpuPlace> Place;
 typedef boost::variant<Dim<1>, Dim<2>, Dim<3>, Dim<4>, Dim<5>,
@@ -93,6 +95,20 @@ typedef boost::variant<
 
 Because `variant` may be thought of as "multi-type, single value", we can utilize it to implement unified interfaces for PaddlePaddle.
 
+`DDim` plays two kinds of roles in Majel. First, it is used to indicate the size of a tensor. For example, we can construct a new `DArray` by following way:
+ 
+ ```c++
+ DArray arr = make_darray(make_ddim({2,3}), 0.0f);
+ ```
+ It means that `arr` will be a two-dimension tensor, or a matrix. The size of its first dimension is 2 and the second is 3. All the element value of `arr` will be initialized as 0.0 .
+ 
+ The second meaning of `DDim` is tensor index. For example, if we want to access the value in the 1st row and 2nd column of `arr` and set it to 1.0, we can do like this:
+
+ ```c++
+ arr[make_ddim({0, 1})] = 1.0；
+ ```
+
+
 ## implement Tensor in Paddle
 
 Before writing code, please make sure you already look through Majel Source Code and grabbed the design philosophy of `DArray` in Majel.
@@ -113,8 +129,8 @@ To assign subtasks to our colleagues, we have to discuss how to divide it to ind
 
 - [ ] 3. Re-implement `Dim`.
 
-    `Dim` is an excellent implementation in Majel. 
-
+    `Dim` is an excellent implementation in Majel.
+    
 > ???
 
 - [ ] 4. Re-implement `Array/Tensor`.