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-# Caffe
-
-[![Build Status](https://travis-ci.org/BVLC/caffe.svg?branch=master)](https://travis-ci.org/BVLC/caffe)
+# CaffeOnACL
 [![License](https://img.shields.io/badge/license-BSD-blue.svg)](LICENSE)
 
-Caffe is a deep learning framework made with expression, speed, and modularity in mind.
-It is developed by the Berkeley Vision and Learning Center ([BVLC](http://bvlc.eecs.berkeley.edu)) and community contributors.
+CaffeOnACL is a project that is maintained by **OPEN** AI LAB, it uses Arm Compute Library (NEON+GPU) to speed up [Caffe](http://caffe.berkeleyvision.org/) and provide utilities to debug, profile and tune application performance. 
+
+The release version is 0.3.0, is based on [Rockchip RK3399](http://www.rock-chips.com/plus/3399.html) Platform, target OS is Ubuntu 16.04. Can download the source code from [OAID/CaffeOnACL](https://github.com/OAID/CaffeOnACL)
+
+* The ARM Computer Vision and Machine Learning library is a set of functions optimised for both ARM CPUs and GPUs using SIMD technologies. See also [Arm Compute Library](https://github.com/ARM-software/ComputeLibrary).
+* Caffe is a fast open framework for deep learning. See also [Caffe](https://github.com/BVLC/caffe).
+
+### Documents
+* [Installation instructions](https://github.com/OAID/CaffeOnACL/blob/master/acl_openailab/installation.md)
+* [User Manuals PDF](https://github.com/OAID/CaffeOnACL/blob/master/acl_openailab/user_manual.pdf)
+* [Performance Report PDF](https://github.com/OAID/CaffeOnACL/blob/master/acl_openailab/performance_report.pdf)
+
+### Arm Compute Library Compatibility Issues :
+There are some compatibility issues between ACL and Caffe Layers, we bypass it to Caffe's original layer class as the workaround solution for the below issues
+
+* Normalization in-channel issue
+* Tanh issue
+* Softmax supporting multi-dimension issue
+* Group issue
+
+Performance need be fine turned in the future
+
+# Release History
+The Caffe based version is [793bd96351749cb8df16f1581baf3e7d8036ac37](https://github.com/BVLC/caffe/tree/793bd96351749cb8df16f1581baf3e7d8036ac37).
 
-Check out the [project site](http://caffe.berkeleyvision.org) for all the details like
+### Version 0.3.0 - Aug 26, 2017
+Support Arm Compute Library version 17.06 with 4 new layers added
 
-- [DIY Deep Learning for Vision with Caffe](https://docs.google.com/presentation/d/1UeKXVgRvvxg9OUdh_UiC5G71UMscNPlvArsWER41PsU/edit#slide=id.p)
-- [Tutorial Documentation](http://caffe.berkeleyvision.org/tutorial/)
-- [BVLC reference models](http://caffe.berkeleyvision.org/model_zoo.html) and the [community model zoo](https://github.com/BVLC/caffe/wiki/Model-Zoo)
-- [Installation instructions](http://caffe.berkeleyvision.org/installation.html)
+* Batch Normalization Layer
+* Direct convolution Layer
+* Locally Connect Layer
+* Concatenate layer
 
-and step-by-step examples.
 
-[![Join the chat at https://gitter.im/BVLC/caffe](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/BVLC/caffe?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
+### Version 0.2.0 - Jul 2, 2017
 
-Please join the [caffe-users group](https://groups.google.com/forum/#!forum/caffe-users) or [gitter chat](https://gitter.im/BVLC/caffe) to ask questions and talk about methods and models.
-Framework development discussions and thorough bug reports are collected on [Issues](https://github.com/BVLC/caffe/issues).
+Fix the issues:
 
-Happy brewing!
+* Compatible with Arm Compute Library version 17.06
+* When OpenCL initialization fails, even if Caffe uses CPU-mode,it doesn't work properly.
 
-## License and Citation
+### Version 0.1.0 - Jun 2, 2017 
+   
+  Initial version supports 10 Layers accelerated by Arm Compute Library version 17.05 : 
 
-Caffe is released under the [BSD 2-Clause license](https://github.com/BVLC/caffe/blob/master/LICENSE).
-The BVLC reference models are released for unrestricted use.
+* Convolution Layer
+* Pooling Layer
+* LRN Layer
+* ReLU Layer
+* Sigmoid Layer
+* Softmax Layer
+* TanH Layer
+* AbsVal Layer
+* BNLL Layer
+* InnerProduct Layer
 
-Please cite Caffe in your publications if it helps your research:
+# 3 Issue Report
+Encounter any issue, please report on [issue report](https://github.com/OAID/CaffeOnACL/issues). Issue report should contain the following information :
 
-    @article{jia2014caffe,
-      Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
-      Journal = {arXiv preprint arXiv:1408.5093},
-      Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
-      Year = {2014}
-    }
+*  The exact description of the steps that are needed to reproduce the issue 
+* The exact description of what happens and what you think is wrong