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Update README.md (dmlc#1307)
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* Update README.md

 add News section for zz request.

* Update README.md

* Update README.md

Co-authored-by: Minjie Wang <[email protected]>
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zhjwy9343 and jermainewang authored Mar 4, 2020
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DGL is an easy-to-use, high performance and scalable Python package for deep learning on graphs. DGL is framework agnostic, meaning if a deep graph model is a component of an end-to-end application, the rest of the logics can be implemented in any major frameworks, such as PyTorch, Apache MXNet or TensorFlow.

<p align="center">
<img src="https://i.imgur.com/DwA1NbZ.png" alt="DGL v0.4 architecture" width="600">
<img src="http://data.dgl.ai/asset/image/DGL-Arch.png" alt="DGL v0.4 architecture" width="600">
<br>
<b>Figure</b>: DGL Overall Architecture
</p>

## <img src="http://data.dgl.ai/asset/image/new.png" width="30">DGL News
03/02/2020: DGL has be chosen as the implemenation base for [Graph Neural Network benchmark framework](https://arxiv.org/abs/2003.00982), which enchmarks framework to novel medium-scale graph datasets from mathematical modeling, computer vision, chemistry and combinatorial problems. Models implemented are [here](https://github.com/graphdeeplearning/benchmarking-gnns).

## Using DGL

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Table: Training time(in seconds) for 200 epochs and memory consumption(GB)

High memory utilization allows DGL to push the limit of single-GPU performance, as seen in below images.
| <img src="https://i.imgur.com/CvXc9Uu.png" width="400"> | <img src="https://i.imgur.com/HnCfJyU.png" width="400"> |
| <img src="http://data.dgl.ai/asset/image/DGLvsPyG-time1.png" width="400"> | <img src="http://data.dgl.ai/asset/image/DGLvsPyG-time2.png" width="400"> |
| -------- | -------- |

**Scalability**: DGL has fully leveraged multiple GPUs in both one machine and clusters for increasing training speed, and has better performance than alternatives, as seen in below images.

<p align="center">
<img src="https://i.imgur.com/IGERtVX.png" width="600">
<img src="http://data.dgl.ai/asset/image/one-four-GPUs.png" width="600">
</p>

| <img src="https://i.imgur.com/BugYro2.png"> | <img src="https://i.imgur.com/KQ4nVdX.png"> |
| <img src="http://data.dgl.ai/asset/image/one-four-GPUs-DGLvsGraphVite.png"> | <img src="http://data.dgl.ai/asset/image/one-fourMachines.png"> |
| :---------------------------------------: | -- |


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