Update README.md

Author: pboechat

README.md

@@ -7,15 +7,15 @@ OperatorGraph
 
 [![ScreenShot](http://www.pedroboechat.com/images/OperatorGraph-video-thumbnail.png)](https://www.youtube.com/embed/CvAlSffwB18?list=PLgV_NS3scu1yDnjMd8m-hLoRgG8Ql7xWN)
 
-It's essentially a toolkit offers an end-to-end solution to compile shape grammars as programs that efficiently run on CUDA enabled GPUs.
+It's essentially a toolkit that offers an end-to-end solution to compile shape grammars as programs that efficiently run on CUDA enabled GPUs.
 
 This toolkit consists of: 
 - a shape grammar interpreter,
 - a C++/CUDA library and
-- a GPU execution auto-tuner.
+- an execution auto-tuner.
 
 
-The implemented shape grammar - __PGA-shape__ - is a rule-based language that enable users to express sequences of modeling operations in a high level of abstraction. 
+The implemented shape grammar - __PGA-shape__ - is a rule-based language that enables users to express sequences of modeling operations in a high level of abstraction. 
 
 
 __PGA-shape__ can be used as a C++/CUDA idiom or as a domain specific language (DSL). For example, to model a [Menger sponge](https://en.wikipedia.org/wiki/Menger_sponge),
@@ -29,7 +29,7 @@ you could write the following grammar in __PGA-shape__  C++/CUDA:
             DynParam<0>>, 1>,
         > {};
 
-or the equivalent grammar in __PGA-shape__  DSL:
+or the equivalent grammar in the __PGA-shape__  DSL:
 
         axiom Box A;
 
@@ -42,17 +42,13 @@ or the equivalent grammar in __PGA-shape__  DSL:
         SubY = SubDiv(Y) { -1: SubZ | -1: ZDiscard | -1: SubZ };
         SubX = SubDiv(X) { -1: SubY | -1: YDiscard | -1: SubY }
 
-Resulting in the following Menger sponge:
+Both resulting the following Menger sponge:
 
 ![Menger Sponge](http://www.pedroboechat.com/images/operator-graph-menger-sponge.png)
 
-Grammars written with the C++/CUDA variant can be embedded in OpenGL/Direct3D applications,
-while grammars written with the DSL can be executed on the GPU with the interpreter shipped with the toolkit. 
-The interpreter can also be embedded in an OpenGL/Direct3D application.
-
-
-The main difference between the two methods is that with C++/CUDA the structure of the grammars directly influence the GPU scheduling, 
-while with the DSL the execution on the GPU is scheduled the same way, independently of the grammar structure.
+Grammars written in the C++/CUDA idiom can be linked to OpenGL/Direct3D applications,
+while grammars written in the DSL can be embedded with the interpreter. 
+The difference between the two methods is that with C++/CUDA the structure of the grammars directly influences the GPU scheduling, while with the DSL the execution on the GPU is always scheduled the same way, independently of the grammar structure.
 
 
 Grammars written with __PGA-shape__  DSL can be analyzed by the auto-tunner and be optimized for GPU execution.