doc update for neon v2.4.0 release (#1089)

* doc update for neon v2.4.0 release * update mkl info
NervanaSystems · Nov 27, 2017 · 85253da · 85253da
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diff --git a/ChangeLog b/ChangeLog
@@ -1,5 +1,16 @@
 # ChangeLog
 
+## v2.4.0 (2017-11-27):
+
+* Enabled pip install through pypi
+* Updated MKLML to version 20171007 with performance improve of ~3X for mnist datalayer/nondatalayer and ~1.6X for DCGAN/WGAN datalayer
+* Updated resnet model to optimize performance with MKLML 20171007
+* Updated Alexnet weight file and fixed bug for deep dream
+* Fixed faster-rcnn inference model loading issue
+* Added data_loading time measurement and enabled GAN networks benchmarking
+* Updated to Aeon version 1.2.0
+* Enabled neon build with mklEngine on Windows systems
+
 ## v2.3.0 (2017-10-27):
 
 * Optimized DeepSpeech2 MKL backend performance (~7X improvement over the CPU backend)

diff --git a/README.md b/README.md
@@ -34,6 +34,14 @@ neon (conda users see the [guide](http://neon.nervanasys.com/docs/latest/install
 
 Starting after neon v2.2.0, the master branch of neon will be updated weekly with work-in-progress toward the next release. Check out a release tag (e.g., "git checkout v2.2.0") for a stable release. Or simply check out the "latest" release tag to get the latest stable release (i.e., "git checkout latest")
 
+From version 2.4.0, we re-enabled pip install. Neon can be installed using package name nervananeon. 
+
+```bash
+    pip install nervananeon
+```
+
+It is noted that [aeon](https://aeon.nervanasys.com/index.html/getting_started.html) needs to be installed separately. The latest release v2.4.0 uses aeon v1.2.0.
+
 **Warning**
 
 > Between neon v2.1.0 and v2.2.0, the aeon manifest file format has been changed. When updating from neon < v2.2.0 manifests have to be recreated using ingest scripts (in examples folder) or updated using [this](neon/data/convert_manifest.py) script.

diff --git a/doc/source/index.rst b/doc/source/index.rst
@@ -28,19 +28,22 @@ Features include:
 * Support for commonly used models including convnets, RNNs, LSTMs, and
   autoencoders.  You can find many pre-trained implementations of these in our
   `model zoo`_
-* Tight integration with our `state-of-the-art`_ GPU kernel library
+* Tight integration with our `state-of-the-art`_ GPU kernel library and Intel CPU MKLML library
 * 3s/macrobatch (3072 images) on AlexNet on Titan X (Full run on 1 GPU ~ 32 hrs)
 * Basic automatic differentiation support
 * Framework for visualization
 * Swappable hardware backends: write code once and deploy on CPUs, GPUs, or Nervana hardware
 
 New features in this release:
 
-* Optimized DeepSpeech2 MKL backend performance (~7X improvement over the CPU backend)
-* Fused convolution and bias layer which significantly boosted AlexNet and VGG performance on Intel architectures with MKL backend
-* Made SSD and Faster-RNN use VGG weight files in new format
-* Fixed use of reset_cells hyperparameter
-* Fixed MKL backend bug for GAN and Faster-RCNN models
+* Enabled pip install through pypi
+* Updated MKLML to version 20171007 with up to 3X performance increase
+* Updated resnet model to optimize performance with MKLML 20171007
+* Updated Alexnet weight file and fixed bug for deep dream
+* Fixed faster-rcnn inference model loading issue
+* Added data_loading time measurement and enabled GAN networks benchmarking
+* Updated Aeon version to 1.2.0
+* Enabled neon build with mklEngine on Windows systems
 * See more in the `change log`_.
 
 We use neon internally at Intel Nervana to solve our `customers' problems`_

diff --git a/doc/source/installation.rst b/doc/source/installation.rst
@@ -63,6 +63,14 @@ Or on Mac OS X:
 Installation
 ~~~~~~~~~~~~
 
+Neon v2.4.0 and after is pip installable through pypi with package name nervananeon.
+
+.. code-block:: bash
+
+    pip install nervananeon
+
+It is noted `aeon <https://aeon.nervanasys.com/index.html/getting_started.html>`__ needs to be installed separately. The latest release v2.4.0 uses aeon v1.2.0.
+
 We recommend installing neon within a `virtual
 environment <http://docs.python-guide.org/en/latest/dev/virtualenvs/>`__
 to ensure a self-contained environment. To install neon within an
@@ -76,7 +84,7 @@ setup neon in this manner, run the following commands:
     git clone https://github.com/NervanaSystems/neon.git
     cd neon; git checkout latest; make
 
-The above checks out the latest stable release (e.g. a tagged release version v2.3.0) and build neon.
+The above checks out the latest stable release (e.g. a tagged release version v2.4.0) and build neon.
 Alternatively, you can check out and build the latest master branch:
 
 .. code-block:: bash

diff --git a/doc/source/previous_versions.rst b/doc/source/previous_versions.rst
@@ -16,6 +16,17 @@
 
 Previous Versions
 =================
+neon v2.3.0
+-----------
+
+|Docs230|_
+
+* Optimized DeepSpeech2 MKL backend performance (~7X improvement over the CPU backend)
+* Fused convolution and bias layer which significantly boosted AlexNet and VGG performance on Intel architectures with MKL backend
+* Made SSD and Faster-RNN use VGG weight files in new format
+* Fixed use of reset_cells hyperparameter
+* Fixed MKL backend bug for GAN and Faster-RCNN models
+
 neon v2.2.0
 -----------
 
@@ -473,6 +484,7 @@ neon v0.8.1
 
 Initial public release of neon.
 
+.. |Docs230| replace:: Docs
 .. |Docs220| replace:: Docs
 .. |Docs200| replace:: Docs
 .. |Docs190| replace:: Docs
@@ -501,6 +513,7 @@ Initial public release of neon.
 .. |Docs9| replace:: Docs
 .. |Docs8| replace:: Docs
 .. _cudanet: https://github.com/NervanaSystems/cuda-convnet2
+.. _Docs230: http://neon.nervanasys.com/docs/2.3.0
 .. _Docs220: http://neon.nervanasys.com/docs/2.2.0
 .. _Docs200: http://neon.nervanasys.com/docs/2.0.0
 .. _Docs190: http://neon.nervanasys.com/docs/1.9.0

diff --git a/setup.py b/setup.py
@@ -18,7 +18,7 @@
 import subprocess
 
 # Define version information
-VERSION = '2.3.0'
+VERSION = '2.4.0'
 FULLVERSION = VERSION
 write_version = True
 
@@ -96,9 +96,9 @@
 
 setup(name='nervananeon',
       version=VERSION,
-      description="Nervana's deep learning framework",
+      description="Intel Nervana's deep learning framework",
       long_description=readme_file,
-      author='Nervana Systems',
+      author='Intel Nervana Systems',
       author_email='[email protected]',
       url='http://www.intelnervana.com',
       license='License :: OSI Approved :: Apache Software License',