Leona/doc logo (#2565)

* Update gold release date and features

* Diagram that shows FW & HW support for main md

* Simplified nGraph architecture for CPU

* Complex architecture diagram for all backends

* Replace

* Add ngraph stack diagram with FW and HW support

* relocate

* Relocate

* Replace stack diagram with NNP-L & NNP-I

* Updated copy and removed the disclaimer

* Removed "more detailed" sentence

* Update README.md

* Fixed sentence

* Update README.md

* nGraph logo small version

* Update README.md

* Added logo

* nGraph logo smallest version

* nGraph logo with header

* Update README.md

* Delete ngraph_logo_header.png

* nGraph logo with header

* Update README.md

* nGraph header on the main repo page

* Added header

* nGraph architecture simplified for CPU

* nGraph architecture complex

* Added architecture simple architecture diagram

* Modified the full stack diagram

* nGraph architecture simple diagram with padding

* Added padding to simple architecture image

* Update ABOUT.md

* Add new logo to doc landpage

* Fix typo

ABOUT.md

@@ -10,8 +10,7 @@ that the stack diagram is simplified to show how nGraph executes deep
 learning workloads with two hardware backends; however, many other
 deep learning frameworks and backends currently are functioning.
 
-![](doc/sphinx/source/graphics/stackngrknl.png)
-
+![](doc/sphinx/source/graphics/arch_simple_pad.png)
 
 #### Bridge
 
@@ -117,7 +116,7 @@ release of nGraph. nGraph currently has limited support for dynamic graphs.
 Current nGraph Compiler full stack
 ----------------------------------
 
-![](doc/sphinx/source/graphics/about_fullstack.png)
+![](doc/sphinx/source/graphics/arch_complex.png)
 
 
 In addition to IA and NNP transformers, nGraph Compiler stack has transformers

README.md

-# nGraph Compiler Stack (Beta)
-
+![nGraph Compiler stack](doc/sphinx/source/graphics/ngraph_header.png)
+===========================
 [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/NervanaSystems/ngraph/blob/master/LICENSE) [![Build Status][build-status-badge]][build-status] 
 
 <div align="left">
@@ -30,44 +30,39 @@ The Python wheels for nGraph have been tested and are supported on the following
 * Debian 10
 * macOS 10.14.3 (Mojave)
 
-:exclamation: Note that the ``pip`` package option works only Intel® Xeon® CPUs. 
-CPUs without Intel® Advanced Vector Extensions 512 (Intel® AVX-512) will not run 
-these packages; the alternative is to build from source. Wider support for other 
-CPUs will be offered in later releases.  
-
 Frameworks using nGraph Compiler stack to execute workloads have shown 
 [**up to 45X**](https://ai.intel.com/ngraph-compiler-stack-beta-release/) 
 performance boost when compared to native framework implementations. We've also 
 seen performance boosts running workloads that are not included on the list of 
-[Validated workloads], thanks to our powerful subgraph pattern matching.
-
-Additional work is also being done via [PlaidML] which will feature running 
-compute for Deep Learning with GPU accleration. See our 
-[Architecture and features] for what the stack looks like today and watch our 
-[Release Notes] for recent changes.
+[Validated workloads], thanks to nGraph's powerful subgraph pattern matching.
 
+Additionally we have integrated nGraph with [PlaidML] to provide deep learning 
+performance acceleration on Intel, nVidia, & AMD GPUs. More details on current 
+architecture of the nGraph Compiler stack can be found in [Architecture and features],
+and recent changes to the stack are explained in [Release Notes].
 
 ## What is nGraph Compiler? 
 
-nGraph Compiler aims to accelerate developing and deploying AI workloads 
-using any deep learning framework with a variety of hardware targets. 
-We strongly believe in providing freedom, performance, and ease-of-use to AI 
-developers. 
+nGraph Compiler aims to accelerate developing AI workloads using any deep learning
+framework and deploying to a variety of hardware targets. We strongly believe in 
+providing freedom, performance, and ease-of-use to AI developers. 
 
-The diagram below shows what deep learning frameworks and hardware targets
-we support. More details on these current and future plans are in the [ecosystem]
-section. 
+The diagram below shows deep learning frameworks and hardware targets
+supported by nGraph. The Intel® Nervana™ Neural Network Processor (Intel® Nervana™ NNP-L 
+for Learning and the NNP-I for Inference) refer to Intel's next generation deep 
+learning accelators for training and inference respectively. Future plans 
+for supporting addtional deep learning frameworks and backends are outlined in
+the [ecosystem] section. 
 
 
-![nGraph wireframe][ngraph_wireframes_with_notice]
+![](doc/sphinx/source/graphics/main_diagram_fw_hw.png)
 
 
 While the ecosystem shown above is all functioning, we have validated 
-performance for deep learning inference on CPU processors such as Intel® Xeon®. 
-Please refer to the [Release notes] to learn more. The Gold release 
-is targeted for April 2019; it will feature broader workload coverage, 
-including quantized graphs, and more detail on our advanced support for 
-``int8``. 
+performance for deep learning inference on CPU processors, such as Intel® Xeon® 
+for the Beta release of nGraph. The Gold release is targeted for June 2019; it 
+will feature broader workload coverage including quantized graphs (int8) and 
+will implement support for dynamic shapes. 
 
 Our documentation has extensive information about how to use nGraph Compiler 
 stack to create an nGraph computational graph, integrate custom frameworks, 
@@ -102,18 +97,17 @@ to improve it:
 [Validated workloads]: https://ngraph.nervanasys.com/docs/latest/frameworks/validation.html
 [Functional]: https://github.com/NervanaSystems/ngraph-onnx/ 
 [How to contribute]: How-to-contribute
-[framework integration guides]: http://ngraph.nervanasys.com/docs/latest/framework-integration-guides.html
+[framework integration guides]: https://ngraph.nervanasys.com/docs/latest/frameworks/index.html
 [release notes]: https://ngraph.nervanasys.com/docs/latest/project/release-notes.html
 [Github issues]: https://github.com/NervanaSystems/ngraph/issues
 [contrib guide]: https://ngraph.nervanasys.com/docs/latest/project/contribution-guide.html
 [pull request]: https://github.com/NervanaSystems/ngraph/pulls
 [how to import]: https://ngraph.nervanasys.com/docs/latest/howto/import.html
 [ngraph_wireframes_with_notice]: doc/sphinx/source/graphics/readme_stack.png "nGraph wireframe"
+[ngraph_diagram_with fw_hw]: doc/sphinx/source/graphics/main_diagram_fw_hw.png "nGraph stack with current framework & backend support"
 [ngraph-compiler-stack-readme]: doc/sphinx/source/graphics/ngraph-compiler-stack-readme.png "nGraph Compiler Stack"
 [build-status]: https://travis-ci.org/NervanaSystems/ngraph/branches
 [build-status-badge]: https://travis-ci.org/NervanaSystems/ngraph.svg?branch=master
-[develop-without-lockin]: doc/sphinx/source/graphics/develop-without-lockin.png "Develop on any part of the stack wtihout lockin"
-[Movidius™ Myriad™ 2]:https://www.movidius.com/solutions/vision-processing-unit
 [PlaidML]: https://github.com/plaidml/plaidml
 [Source compile]: https://github.com/NervanaSystems/ngraph-mxnet/blob/master/README.md
 [nGraph-ONNX]: https://github.com/NervanaSystems/ngraph-onnx/blob/master/README.md