doc: added separate README for binary packages

oneapi-src · Dec 2, 2019 · 28f4c96 · 28f4c96
1 parent 79f204c
commit 28f4c96
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diff --git a/CMakeLists.txt b/CMakeLists.txt
@@ -105,6 +105,11 @@ configure_file(
 )
 include_directories(${PROJECT_BINARY_DIR}/include)
 
+configure_file(
+    "${PROJECT_SOURCE_DIR}/README.binary.in"
+    "${PROJECT_BINARY_DIR}/README"
+)
+
 if(DNNL_INSTALL_MODE STREQUAL "BUNDLE" AND NOT DEFINED CMAKE_INSTALL_LIBDIR)
     # define CMAKE_INSTALL_LIBDIR as "lib" in the case of bundle
     set(CMAKE_INSTALL_LIBDIR "lib")
@@ -119,8 +124,9 @@ add_subdirectory(tests)
 
 if(DNNL_INSTALL_MODE STREQUAL "BUNDLE")
     install(FILES LICENSE DESTINATION ${CMAKE_INSTALL_PREFIX})
-    install(FILES README.md DESTINATION ${CMAKE_INSTALL_PREFIX})
+    install(FILES ${PROJECT_BINARY_DIR}/README DESTINATION ${CMAKE_INSTALL_PREFIX})
 else()
     # Cannot use CMAKE_INSTALL_DOCDIR since it uses PROJECT_NAME and not LIB_NAME
     install(FILES LICENSE DESTINATION ${CMAKE_INSTALL_DATAROOTDIR}/doc/${LIB_NAME})
+    install(FILES ${PROJECT_BINARY_DIR}/README DESTINATION ${CMAKE_INSTALL_DATAROOTDIR}/doc/${LIB_NAME})
 endif()
diff --git a/README.binary.in b/README.binary.in
@@ -0,0 +1,115 @@
+Deep Neural Network Library (DNNL)
+==================================
+
+Deep Neural Network Library (DNNL) is an
+open-source performance library for deep learning applications. The library
+includes basic building blocks for neural networks optimized
+for Intel Architecture Processors and Intel Processor Graphics.
+
+This package contains DNNL v@PROJECT_VERSION@ (@DNNL_VERSION_HASH@).
+
+You can find information about the latest version and release notes
+at DNNL Github (https://github.com/intel/mkl-dnn/releases).
+
+Documentation
+-------------
+
+* Developer guide (https://intel.github.io/mkl-dnn/v@DNNL_VERSION_MAJOR@.@DNNL_VERSION_MINOR@)
+explains programming model, supported functionality, details of primitives
+implementations and includes annotated examples.
+* API reference (https://intel.github.io/mkl-dnn/v@DNNL_VERSION_MAJOR@.@DNNL_VERSION_MINOR@/modules.html)
+provides comprehensive reference of the library API.
+
+System Requirements
+-------------------
+
+DNNL supports systems based on Intel 64 architecture or
+compatible processors.
+
+The library is optimized for the following CPUs:
+* Intel Atom processor with Intel SSE4.1 support
+* 4th, 5th, 6th, 7th, and 8th generation Intel Core(TM) processor
+* Intel Xeon(R) processor E3, E5, and E7 family (formerly Sandy Bridge,
+  Ivy Bridge, Haswell, and Broadwell)
+* Intel Xeon Phi(TM) processor (formerly Knights Landing and Knights Mill)
+* Intel Xeon Scalable processor (formerly Skylake and Cascade Lake)
+* future Intel Xeon Scalable processor (code name Cooper Lake)
+
+DNNL detects instruction set architecture (ISA) in the runtime and uses
+just-in-time (JIT) code generation to deploy the code optimized
+for the latest supported ISA.
+
+The library is optimized for the following GPUs:
+* Intel HD Graphics
+* Intel UHD Graphics
+* Intel Iris Plus Graphics
+
+## Linux
+
+Common dependencies:
+* glibc 2.12 or later
+* GCC 4.8 or later
+
+Runtime specific dependencies:
+
+| Runtime configuration | Requirements                                         |
+| --------------------- | ---------------------------------------------------- |
+| `cpu_gomp`            | No additional requirements                           |
+| `cpu_iomp`            | Intel OpenMP runtime                                 |
+| `cpu_tbb`             | Threading Building Blocks 2017 or later              |
+
+## Windows
+
+Common dependencies:
+* Microsoft Visual C++ Redistributable 2015 or later
+
+Runtime specific dependencies:
+
+| Runtime configuration | Requirements                                         |
+| --------------------- | -----------------------------------------------------|
+| `cpu_vcomp`           | No additional requirements                           |
+| `cpu_iomp`            | Intel OpenMP runtime                                 |
+| `cpu_tbb`             | Threading Building Blocks 2017 or later              |
+
+## macOS
+
+Common dependencies:
+* macOS 10.13 (High Sierra) or later
+
+Runtime specific dependencies:
+
+| Runtime configuration | Requirements                                         |
+| --------------------- | -----------------------------------------------------|
+| `cpu_iomp`            | Intel OpenMP runtime                                 |
+| `cpu_tbb`             | Threading Building Blocks 2017 or later              |
+
+Support
+-------
+
+Please submit your questions, feature requests, and bug reports on the
+GitHub issues page (https://github.com/intel/mkl-dnn/issues/new/choose).
+
+You may reach out to project maintainers privately at [email protected].
+
+WARNING:
+The following functionality has preview status and might be changed without
+prior notification in future releases:
+* Primitive cache
+
+License
+-------
+
+DNNL is licensed under Apache License Version 2.0. This
+software includes components with separate copyright notices and license
+terms. Your use of the source code for these components is subject to the terms
+and conditions of the following licenses.
+
+3-clause BSD license:
+* Xbyak (https://github.com/herumi/xbyak)
+* ittnotify (https://github.com/intel/IntelSEAPI)
+* CMake (https://github.com/Kitware/CMake)
+
+Boost Software License, Version 1.0:
+* Boost C++ Libraries (https://www.boost.org/)
+
+See accompanying LICENSE file for full license text and copyright notices.
diff --git a/README.md b/README.md
@@ -1,5 +1,5 @@
 Deep Neural Network Library (DNNL)
-========================================================================
+==================================
 
 > **Note**
 >
@@ -35,6 +35,14 @@ applications enabled with DNNL:
 * [PyTorch\*](https://pytorch.org/)
 * [Tensorflow\*](https://www.tensorflow.org)
 
+# Documentation
+
+* [Developer guide](https://intel.github.io/mkl-dnn) explains programming
+model, supported functionality, details of primitives implementations and
+includes annotated examples.
+* [API reference](https://intel.github.io/mkl-dnn/modules.html) provides
+comprehensive reference of the library API.
+
 # Installation
 
 Pre-built binaries for Linux\*, Windows\*, and macOS\* are available for download
@@ -67,56 +75,8 @@ details on CPU and GPU runtimes.
 If the configuration you need is not available, you can
 [build the library from source](http://intel.github.io/mkl-dnn/dev_guide_build.html).
 
-# Contributing
-We welcome community contributions to DNNL. If you have an idea on how
-to improve the library:
-
-* For changes impacting the public API, submit
-  an [RFC pull request](CONTRIBUTING.md#RFC_pull_requests).
-* Ensure that the changes are consistent with the
- [code contribution guidelines](CONTRIBUTING.md#code_contribution_guidelines)
- and [coding style](CONTRIBUTING.md#coding_style).
-* Ensure that you can build the product and run all the examples with your
-  patch.
-* Submit a [pull request](https://github.com/intel/mkl-dnn/pulls).
-
-For additional details, see [contribution guidelines](CONTRIBUTING.md).
-
-# Support
-
-> **WARNING**
->
-> The following functionality has preview status and might be changed without prior notification in future releases:
-> * [Primitive cache](https://intel.github.io/mkl-dnn/dev_guide_primitive_cache.html)
-
-Please submit your questions, feature requests, and bug reports on the
-[GitHub issues](https://github.com/intel/mkl-dnn/issues) page.
-
-# License
-DNNL is licensed under
-[Apache License Version 2.0](http://www.apache.org/licenses/LICENSE-2.0). This
-software includes the following third-party components:
-* [Xbyak](https://github.com/herumi/xbyak) distributed under
-[3-clause BSD licence](src/cpu/xbyak/COPYRIGHT)
-* [gtest](https://github.com/google/googletest) distributed under
-[3-clause BSD license](tests/gtests/gtest/LICENSE)
-* [ittnotify](https://github.com/intel/IntelSEAPI) distributed under
-[3-clause BSD license](src/cpu/jit_utils/jitprofiling/LICENSE.BSD)
-* [Cmake](https://github.com/Kitware/CMake) distributed under
-[3-clause BSD license](cmake/Copyright.txt)
-* [MathJax](https://github.com/mathjax/MathJax) distributed under
-[Apache License Version 2.0](doc/assets/mathjax/LICENSE)
-* [Boost C++ Libraries](https://www.boost.org/) distributed under
-[Boost Software License, Version 1.0](src/common/LICENSE_1_0)
-
-# Documentation
-* [Developer guide](https://intel.github.io/mkl-dnn) explains programming
-model, supported functionality, details of primitives implementations and
-includes annotated examples.
-* [API reference](https://intel.github.io/mkl-dnn/modules.html) provides
-comprehensive reference of the library API.
-
 # System Requirements
+
 DNNL supports systems based on Intel 64 architecture or
 compatible processors.
 
@@ -139,6 +99,7 @@ The library is optimized for the following GPUs:
 * Intel Iris Plus Graphics
 
 ## Requirements for Building from Source
+
 DNNL supports systems meeting the following requirements:
 * Operating sytem with Intel 64 architecture support
 * C++ compiler with C++11 standard support
@@ -150,6 +111,7 @@ Configurations of CPU and GPU engines may introduce additional build time
 dependencies.
 
 ### CPU Engine
+
 Intel Architecture Processors and compatible devices are supported by the
 DNNL CPU engine. The CPU engine is built by default and cannot
 be disabled at build time. The engine can be configured to use the OpenMP or
@@ -163,6 +125,7 @@ Some implementations rely on OpenMP 4.0 SIMD extensions, and we recommend using
 the Intel C++ Compiler for the best performance results.
 
 ### GPU Engine
+
 Intel Processor Graphics is supported by the DNNL GPU engine. The GPU
 engine is disabled in the default build configuration. The following
 additional requirements apply when GPU engine is enabled:
@@ -171,10 +134,12 @@ additional requirements apply when GPU engine is enabled:
   with Intel subgroups extension support
 
 ### Runtime Dependencies
+
 When DNNL is built from source, the library runtime dependencies
 and specific versions are defined by the build environment.
 
 #### Linux
+
 Common dependencies:
 * System C/C++ runtime (libc.so, libstdc++.so)
 * Dynamic Linking Library (libdl.so)
@@ -183,39 +148,42 @@ Common dependencies:
 
 Runtime specific dependencies:
 
-| Runtime configuration    | Compiler                      | Dependency
-| :----------------------- | :---------------------------- | :---------
+| Runtime configuration  | Compiler                      | Dependency
+| :--------------------- | :---------------------------- | :---------
 | `DNNL_CPU_RUNTIME=OMP` | GCC                           | GNU OpenMP runtime (libgomp.so)
 | `DNNL_CPU_RUNTIME=OMP` | Intel C/C++ Compiler          | Intel OpenMP runtime (libiomp5.so)
 | `DNNL_CPU_RUNTIME=OMP` | Clang                         | Intel OpenMP runtime (libiomp5.so)
 | `DNNL_CPU_RUNTIME=TBB` | any                           | Threading Building Blocks (libtbb.so)
 | `DNNL_GPU_RUNTIME=OCL` | any                           | Intel Graphics Compute Runtime for OpenCL (libOpenCL.so)
 
 #### Windows
+
 Common dependencies:
 * Microsoft Visual C++ Redistributable (msvcrt.dll)
 
 Runtime specific dependencies:
 
-| Runtime configuration    | Compiler                      | Dependency
-| :----------------------- | :---------------------------- | :---------
+| Runtime configuration  | Compiler                      | Dependency
+| :--------------------- | :---------------------------- | :---------
 | `DNNL_CPU_RUNTIME=OMP` | Microsoft Visual C++ Compiler | No additional requirements
 | `DNNL_CPU_RUNTIME=OMP` | Intel C/C++ Compiler          | Intel OpenMP runtime (iomp5.dll)
 | `DNNL_CPU_RUNTIME=TBB` | any                           | Threading Building Blocks (tbb.dll)
 | `DNNL_GPU_RUNTIME=OCL` | any                           | Intel Graphics Driver (OpenCL.dll)
 
 #### macOS
+
 Common dependencies:
 * System C/C++ runtime (libc++.dylib, libSystem.dylib)
 
 Runtime specific dependencies:
 
-| Runtime configuration    | Compiler                      | Dependency
-| :----------------------- | :---------------------------- | :---------
+| Runtime configuration  | Compiler                      | Dependency
+| :--------------------- | :---------------------------- | :---------
 | `DNNL_CPU_RUNTIME=OMP` | Intel C/C++ Compiler          | Intel OpenMP runtime (libiomp5.dylib)
 | `DNNL_CPU_RUNTIME=TBB` | any                           | Threading Building Blocks (libtbb.dylib)
 
 ### Validated Configurations
+
 CPU engine was validated on RedHat\* Enterprise Linux 7 with
 * GNU Compiler Collection 4.8, 5.4, 6.1, 7.2, and 8.1
 * Clang\* 3.8.0
@@ -249,40 +217,62 @@ on Windows Server 2019 with
 
 ## Requirements for Pre-built Binaries
 
-### Linux
-Common dependencies:
-* GCC 4.8 or later
+See README included into corresponding binary package.
 
-Runtime specific dependencies:
+# Support
 
-| Runtime configuration | Requirements
-| :-------------------- | :-----------
-| `cpu_gomp`            | No additional requirements
-| `cpu_iomp`            | Intel OpenMP runtime for Intel C/C++ Compiler 17.0 or later
-| `cpu_tbb`             | Threading Building Blocks 2017 or later
+Please submit your questions, feature requests, and bug reports on the
+[GitHub issues](https://github.com/intel/mkl-dnn/issues/new/choose) page.
 
-### Windows
-Common dependencies:
-* Microsoft Visual C++ Redistributable 2015 or later
+You may reach out to project maintainers privately at [email protected].
 
-Runtime specific dependencies:
+> **WARNING**
+>
+> The following functionality has preview status and might be changed without
+> prior notification in future releases:
+> * [Primitive cache](https://intel.github.io/mkl-dnn/dev_guide_primitive_cache.html)
 
-| Runtime configuration | Requirements
-| :-------------------- | :-----------
-| `cpu_vcomp`           | No additional requirements
-| `cpu_iomp`            | Intel OpenMP runtime for Intel C/C++ Compiler 17.0 or later
-| `cpu_tbb`             | Threading Building Blocks 2017 or later
+# Contributing
 
-### macOS
-Common dependencies:
-* macOS 10.13 (High Sierra) or later
+We welcome community contributions to DNNL. If you have an idea on how
+to improve the library:
 
-Runtime specific dependencies:
+* For changes impacting the public API, submit
+  an [RFC pull request](CONTRIBUTING.md#RFC_pull_requests).
+* Ensure that the changes are consistent with the
+ [code contribution guidelines](CONTRIBUTING.md#code_contribution_guidelines)
+ and [coding style](CONTRIBUTING.md#coding_style).
+* Ensure that you can build the product and run all the examples with your
+  patch.
+* Submit a [pull request](https://github.com/intel/mkl-dnn/pulls).
+
+For additional details, see [contribution guidelines](CONTRIBUTING.md).
+
+This project is intended to be a safe, welcoming space for collaboration, and
+contributors are expected to adhere to the
+[Contributor Covenant](CODE_OF_CONDUCT.md) code of conduct.
+
+# License
+
+DNNL is licensed under
+[Apache License Version 2.0](http://www.apache.org/licenses/LICENSE-2.0).  This
+software includes components with separate copyright notices and license
+terms. Your use of the source code for these components is subject to the terms
+and conditions of the following licenses.
+
+3-clause BSD license:
+* [Xbyak](https://github.com/herumi/xbyak)
+* [gtest](https://github.com/google/googletest)
+* [ittnotify](https://github.com/intel/IntelSEAPI)
+* [CMake](https://github.com/Kitware/CMake)
+
+Apache License Version 2.0:
+* [MathJax](https://github.com/mathjax/MathJax)
+
+Boost Software License, Version 1.0:
+* [Boost C++ Libraries](https://www.boost.org/)
 
-| Runtime configuration | Requirements
-| :-------------------- | :-----------
-| `cpu_iomp`            | Intel OpenMP runtime for Intel C/C++ Compiler 17.0 or later
-| `cpu_tbb`             | Threading Building Blocks 2017 or later
+See accompanying [LICENSE](LICENSE) file for full license text and copyright notices.
 
 --------