update doc link

README.md

@@ -3,6 +3,7 @@
 [![Latest Release](https://img.shields.io/github/release/microsoft/mscclpp.svg)](https://github.com/microsoft/mscclpp/releases/latest)
 [![License](https://img.shields.io/github/license/microsoft/mscclpp.svg)](LICENSE)
 [![CodeQL](https://github.com/microsoft/mscclpp/actions/workflows/codeql-analysis.yml/badge.svg?branch=main)](https://github.com/microsoft/mscclpp/actions/workflows/codeql-analysis.yml)
+[![Docs Build](https://github.com/microsoft/mscclpp/actions/workflows/doc-build.yaml/badge.svg)](https://microsoft.github.io/mscclpp/)
 
 | Pipelines                | Build Status      |
 |--------------------------|-------------------|
@@ -12,7 +13,7 @@
 
 A GPU-driven communication stack for scalable AI applications.
 
-See [Quick Start](docs/getting-started/quickstart.md) to quickly get started.
+See [Quick Start](https://microsoft.github.io/mscclpp/getting-started/quickstart.html) to quickly get started.
 
 ## Overview
 

docs/design/mscclpp-dsl.md

@@ -1,5 +1,5 @@
 # MSCCLPP DSL
-## MSCCLPPLang Intruduction
+## MSCCLPPLang Introduction
 MSCCLPPLang is a Python moudule for writing high-performance commnunication algorithms. It is designed to be easy to use and efficient, while providing a high-level interface for writing communication algorithms. MSCCLPPLang program will be compiled to json based execution plan, which can be executed by MSCCLPP executor.
 
 ## How to use MSCCLPPLang
@@ -67,7 +67,7 @@ c = chunk(0, Buffer.input, 0, 2)
 ```
 
 #### Operation
-The operation can only be applied to the chunks. We provide a set of communicatoin operations for the users to use. For example, the `put` operation is used to send the data from one GPU to another GPU. The `get` operation is used to receive the data from another GPU.
+The operation can only be applied to the chunks. We provide a set of communications operations for the users to use. For example, the `put` operation is used to send the data from one GPU to another GPU. The `get` operation is used to receive the data from another GPU.
 
 ***Please notice***: MSCCLPPLang only provides one-sided communication operations. The user needs to make sure that the data is ready to be sent or received before calling the communication operations. Also we provides `wait/signal` operations to synchronize the communication across GPUs.