Update README.md

README.md

@@ -1,27 +1,28 @@
 # ThunderSVM
 [![Build Status](https://travis-ci.org/zeyiwen/thundersvm.svg?branch=master)](https://travis-ci.org/zeyiwen/thundersvm)
+[![Documentation Status](https://readthedocs.org/projects/thundersvm/badge/?version=latest)](https://thundersvm.readthedocs.org)
+[![GitHub license](http://dmlc.github.io/img/apache2.svg)](./LICENSE)
 
 <div align="center">
+<img src="https://github.com/zeyiwen/thundersvm/raw/master/logo.png" width="250" height="200" align=left/>
 <img src="https://github.com/zeyiwen/thundersvm/raw/master/docs/_static/lang-logo.png" width="250" height="200" align=left/>
 <img src="https://github.com/zeyiwen/thundersvm/raw/master/docs/_static/overall.png" width="250" height="200" align=left/>
 </div>
 
 ## Overview
-The mission of ThunderSVM is to help users easily and efficiently apply SVMs to solve problems. Some key features of ThunderSVM are as follows.
-* Support one-class, binary and multi-class SVM classification, SVM regression, and SVMs with probability outputs.
-* Have Python, R and Matlab interfaces.
+The mission of ThunderSVM is to help users easily and efficiently apply SVMs to solve problems. ThunderSVM exploits GPUs and multi-core CPUs to achieve high efficiency. Key features of ThunderSVM are as follows.
+* Support all functionalities of LibSVM such as one-class SVMs, SVC, SVR and probabilistic SVMs.
+* Use same command line options as LibSVM.
+* Support Python, R and Matlab interfaces.
 
+[Documentations](http://thundersvm.readthedocs.io) | [Installation](http://thundersvm.readthedocs.io/en/latest/how-to.html) | [API Reference (doxygen)](http://zeyiwen.github.io/thundersvm/)
 ## Contents
 - [Getting Started](https://github.com/zeyiwen/thundersvm/tree/improve-doc#getting-started)
 - [Advanced](https://github.com/zeyiwen/thundersvm/tree/improve-doc#advanced)
 - [Working without GPUs](https://github.com/zeyiwen/thundersvm/tree/improve-doc#working-without-gpus)
-- [Documentations](http://thundersvm.readthedocs.io)
-- [API Reference (doxygen)](http://zeyiwen.github.io/thundersvm/)
 ## Getting Started
 ### Prerequisites
-* [CUDA](https://developer.nvidia.com/cuda-downloads)
-* cmake > 2.8
-* gcc > 4.8
+* [CUDA](https://developer.nvidia.com/cuda-downloads) 7.5 or above | cmake 2.8 or above | gcc 4.8 or above
 ### Download
 ```bash
 git clone git@github.com:zeyiwen/thundersvm.git
@@ -56,9 +57,11 @@ mkdir build && cd build && cmake -DUSE_CUDA=OFF -DUSE_EIGEN=ON .. && make -j
 Now ThunderSVM will work solely on CPUs and does not rely on CUDA.
 
 ## Related websites
-* [LibSVM](https://www.csie.ntu.edu.tw/~cjlin/libsvm/)
-* [SVM<sup>light</sup>](http://svmlight.joachims.org/)
-* [OHD-SVM](https://github.com/OrcusCZ/OHD-SVM)
+* [LibSVM](https://www.csie.ntu.edu.tw/~cjlin/libsvm/) | [SVM<sup>light</sup>](http://svmlight.joachims.org/) | [OHD-SVM](https://github.com/OrcusCZ/OHD-SVM) | [NVIDIA Machine Learning](http://www.nvidia.com/object/machine-learning.html)
 
 ## TODO
 - integrate with interfaces
+
+## Acknowlegement 
+* We acknowledge NVIDIA for their hardware donations.
+* This project is hosted by NUS, collaborating with Prof. Jian Chen (South China University of Technology). Initial work of this project was done when Zeyi Wen worked at The University of Melbourne.