Merge remote-tracking branch 'origin/master' into r0.10

Author: Adam Procter

cmake/external_mkldnn.cmake

@@ -114,6 +114,7 @@ if(${CMAKE_VERSION} VERSION_LESS 3.2)
             -DCMAKE_CXX_COMPILER=${CMAKE_CXX_COMPILER}
             -DCMAKE_INSTALL_PREFIX=${EXTERNAL_PROJECTS_ROOT}/mkldnn
             -DMKLROOT=${MKL_ROOT}
+            "-DARCH_OPT_FLAGS=-march=${NGRAPH_TARGET_ARCH} -mtune=${NGRAPH_TARGET_ARCH}"
         TMP_DIR "${EXTERNAL_PROJECTS_ROOT}/mkldnn/tmp"
         STAMP_DIR "${EXTERNAL_PROJECTS_ROOT}/mkldnn/stamp"
         DOWNLOAD_DIR "${EXTERNAL_PROJECTS_ROOT}/mkldnn/download"
@@ -145,6 +146,7 @@ else()
             -DCMAKE_CXX_COMPILER=${CMAKE_CXX_COMPILER}
             -DCMAKE_INSTALL_PREFIX=${EXTERNAL_PROJECTS_ROOT}/mkldnn
             -DMKLROOT=${MKL_ROOT}
+            "-DARCH_OPT_FLAGS=-march=${NGRAPH_TARGET_ARCH} -mtune=${NGRAPH_TARGET_ARCH}"
         TMP_DIR "${EXTERNAL_PROJECTS_ROOT}/mkldnn/tmp"
         STAMP_DIR "${EXTERNAL_PROJECTS_ROOT}/mkldnn/stamp"
         DOWNLOAD_DIR "${EXTERNAL_PROJECTS_ROOT}/mkldnn/download"

doc/sphinx/source/branding-notice.rst

@@ -6,26 +6,29 @@
 Branding Notice
 ===============
 
-The Intel® nGraph™ library is an open source project providing code and component 
-reference for many kinds of machine learning, deep learning, and DNN applications. 
+The Intel® nGraph Library and Compiler stack is an open source project providing 
+code and component reference for many kinds of machine learning, deep learning, 
+and DNN applications. 
 
-Documentation may include references to frontend frameworks, modules, extensions, 
-or other libraries that may be wholly or partially open source, or that may be 
-claimed as the property of others.  
+Our documentation may include references to various frontends / frameworks, 
+modules, extensions, or other libraries that may be wholly or partially open 
+source, or that may be claimed as the property of others.
 
+Intel, the Intel logo and Intel Nervana are trademarks of Intel Corporation or 
+its subsidiaries in the U.S. and/or other countries.
 
-Intel nGraph library core documentation
----------------------------------------
+Documentation notice
+---------------------
 
 .. note:: The branding notice below applies to code and documentation 
-   contributions intended to be added directly to Intel nGraph library core.   
+   contributions intended to be added directly to the Intel nGraph repo.   
 
 Use the first or most prominent usage with symbols as described below.
 
 Subsequent references on the same document, or on a file with an 
 already-present prominent form (such as Sphinx\* documentation sidebars), 
 may be done as an abbreviated form (sub-bullet items) and/or without the 
-repeated use of the trademark / branding symbols. 
+repeated use of the trademark / branding symbols.
 
 * Intel® Nervana™ Neural Network Processor 
 
@@ -39,15 +42,16 @@ repeated use of the trademark / branding symbols.
 
 * Intel® nGraph™
 
-* Intel® nGraph™ library 
+* Intel® nGraph Library 
+
+* Intel® nGraph Compiler
+
+* Intel® nGraph Backend 
+
+* Intel® nGraph API 
+
+* Movidius™ Myriad™ 
 
-    * nGraph library
-    * ``ngraph`` API
-    * ``ngraph`` library
-    * ``ngraph`` backend
-    * nGraph abstraction layer
-    * neon™ frontend framework 
-    
 * Intel® Math Kernel Library
 
   * Intel® MKL
@@ -59,3 +63,20 @@ repeated use of the trademark / branding symbols.
 * Intel® Nervana™ Graph (deprecated)
 
 
+
+Optimization Notices
+====================
+
+Software and workloads used in performance tests may have been optimized for 
+performance only on Intel microprocessors. Performance tests, such as SYSmark 
+and MobileMark, are measured using specific computer systems, components, 
+software, operations and functions. Any change to any of those factors may 
+cause the results to vary. You should consult other information and performance 
+tests to assist you in fully evaluating your contemplated purchases, including 
+the performance of that product when combined with other products.  For more 
+complete information visit http://www.intel.com/benchmarks.  
+
+Intel technologies' features and benefits depend on system configuration and may 
+require enabled hardware, software or service activation. Performance varies 
+depending on system configuration. No computer system can be absolutely secure. 
+Check with your system manufacturer or retailer or learn more at intel.com. 

doc/sphinx/source/conf.py

@@ -62,7 +62,7 @@
 master_doc = 'index'
 
 # General information about the project.
-project = u'Intel® nGraph Library'
+project = u'nGraph Compiler stack'
 copyright = '2018, Intel Corporation'
 author = 'Intel Corporation'
 

doc/sphinx/source/index.rst

@@ -28,12 +28,13 @@ See the latest :doc:`project/release-notes`.
    :width: 599px
 
 
-nGraph is an open-source C++ library, compiler, and runtime accelerator for 
-software engineering in the :abbr:`Deep Learning (DL)` ecosystem. nGraph 
+nGraph is an open-source C++ library, compiler stack, and runtime accelerator 
+for software engineering in the :abbr:`Deep Learning (DL)` ecosystem. nGraph 
 simplifies development and makes it possible to design, write, compile, and
-deploy :abbr:`Deep Neural Network (DNN)`-based solutions. A more detailed 
-explanation of the feature set of nGraph Compiler, as well as a high-level 
-overview, can be found on our project :doc:`project/about`. 
+deploy :abbr:`Deep Neural Network (DNN)`-based solutions that can be adapted and 
+deployed across many frameworks and backends. A more detailed explanation, as
+well as a high-level overview, can be found on our project :doc:`project/about`.  
+For more generalized discussion on the ecosystem, see the `ecosystem`_ document.
 
 
 .. _quickstart:
@@ -89,7 +90,7 @@ We have many documentation pages to help you get started.
    Intel Movidius™ Myriad™ 2 (VPU), Coming soon, Yes
 
 
-.. note:: The Library code is under active development as we're continually 
+.. note:: The code in this repo is under active development as we're continually 
    adding support for more kinds of DL models and ops, compiler optimizations, 
    and backend optimizations.
 
@@ -131,3 +132,4 @@ Indices and tables
 .. _contributions: https://github.com/NervanaSystems/ngraph#how-to-contribute
 .. _TensorFlow bridge to nGraph: https://github.com/NervanaSystems/ngraph-tf/blob/master/README.md
 .. _Compiling MXNet with nGraph: https://github.com/NervanaSystems/ngraph-mxnet/blob/master/README.md
+.. _ecosystem: https://github.com/NervanaSystems/ngraph/blob/master/ecosystem-overview.md