[DEV] Updated README.md (#15)

README.md

@@ -1 +1,82 @@
-# triton-viz
+<a name="readme-top"></a>
+# Triton-Viz: A Visualization toolkit for GPU programming on Triton
+<!-- PROJECT LOGO -->
+<br />
+<div align="center">
+    <img src="Logo.jpg" alt="Logo" width="320" height="320">
+</div>
+<br/>
+
+Welcome to Triton-Viz, a visualization and profiling toolkit designed for deep learning applications. Built with the intention of making GPU programming on Triton more intuitive.
+<!-- TABLE OF CONTENTS -->
+<details>
+  <summary>Table of Contents</summary>
+  <ol>
+    <li>
+      <a href="#About">About</a>
+    <li>
+      <a href="#Getting-Started">Getting Started</a>
+      <ul>
+        <li><a href="#Prerequisites">Prerequisites</a></li>
+        <li><a href="#Installation-of-Triton_Viz">Installation of Triton_Viz</a></li>
+      </ul>
+    <li>
+      <a href="#Working-with-Examples">Working with examples</a>
+    <ul>
+        <li><a href="#More-Puzzles">More puzzles</a></li>
+      </ul>
+    </li>
+    <li><a href="#License">License</a></li>
+  </ol>
+</details>
+
+## About
+
+Triton-Viz is a visualization and analysis toolkit specifically designed to complement the development and optimization of applications written in OpenAI's Triton,an open-source programming language aimed at simplifying the task of coding for accelerators such as GPUs.
+Triton-Viz emerges as a pivotal tool for developers working in the realms of AI and high-performance computing, offering a suite of features to enhance the debugging, performance analysis, and understanding of Triton code.
+Given that Triton allows developers to program at a higher level while still targeting low-level accelerator devices, managing and optimizing resources like memory becomes a crucial aspect of development.
+Triton-Viz addresses these challenges by providing real-time visualization of tensor operations and their memory usage.Its interface is designed to be intuitive for users familiar with high-level array programming languages like Numpy and PyTorch.
+
+The toolkit aids in identifying bottlenecks and inefficient memory operations,which are often the primary hurdles in achieving optimal performance on GPUs and other accelerators.
+By visualizing how Triton code translates into actual device-level operations, Triton-Viz empowers developers to make informed decisions about code structure, memory management, and parallel execution patterns.
+Whether you're a novice learning the intricacies of accelerator programming or an expert tuning algorithms for maximum efficiency,Triton-Viz serves as an essential tool for all.
+
+The best part about this tool is that while it does focus on visualizing GPU operations,users are not required to have GPU resources to run examples on their system.
+
+## Getting Started
+
+### Prerequisites
+-Python installed(preferably the latest available version).
+</br>
+-[Triton](https://github.com/openai/triton/blob/main/README.md) installed.Follow the installation instructions in the linked repository.
+</br>
+</br>
+-Upon successfully installing Triton,install Torch using the following command
+```sh
+pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu121
+```
+-Upon successful installation of Torch make sure to uninstall 'pytorch-triton' using the following command.
+```sh
+pip uninstall pytorch-triton
+```
+### Installation of Triton_Viz
+Clone the repository to your local machine:
+```sh
+git clone https://github.com/Deep-Learning-Profiling-Tools/triton-viz.git
+cd triton-viz
+pip install -e .
+```
+You're all set !
+
+## Working with Examples:
+
+```sh
+cd examples
+python <file_name>.py
+```
+## More Puzzles
+If you're interested in fun puzzles to work with in Triton, do check out: [Triton Puzzles](https://github.com/srush/Triton-Puzzles)
+
+## License
+Triton-Viz is licensed under the MIT License. See the [LICENSE](LICENSE) for details.
+<p align="right">(<a href="#readme-top">back to top</a>)</p>