doc: adding sections in oneDNN

doc/build/build_options.md

@@ -1,5 +1,5 @@
-Build Options {#dev_guide_build_options}
-====================================
+Use Build Options {#dev_guide_build_options}
+============================================
 
 oneDNN supports the following build-time options.
 

doc/build/link.md

@@ -1,5 +1,5 @@
-Linking to the Library {#dev_guide_link}
-===========================================
+Link to the Library {#dev_guide_link}
+=====================================
 
 oneDNN includes several header files providing C and C++ APIs
 for the functionality and one or several libraries depending

doc/build/system_requirements.md

@@ -0,0 +1,5 @@
+System Requirements {#dev_guide_system_requirements}
+====================================================
+
+oneDNN supports a broad list of hardware platforms, operating systems, and compilers. 
+For details, see [oneDNN System Requirements](https://github.com/uxlfoundation/oneDNN?tab=readme-ov-file#system-requirements).

doc/rst/build_and_link.rst

@@ -1,9 +1,10 @@
-Building and Linking
-######################
+Build and Link oneDNN
+#####################
 
 .. toctree::
    :maxdepth: 1
 
+   dev_guide_system_requirements
    dev_guide_build
    dev_guide_build_options
    dev_guide_link

doc/rst/index.rst

@@ -1,10 +1,47 @@
 oneAPI Deep Neural Network Library (oneDNN) Developer Guide and Reference
 =========================================================================
 
+oneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform 
+performance library of basic building blocks for deep learning applications.
+
+The library is optimized for Intel(R) Architecture Processors, Intel Graphics, 
+and Arm(R) 64-bit Architecture (AArch64)-based processors. oneDNN has experimental 
+support for the following architectures: NVIDIA* GPU, AMD* GPU, 
+OpenPOWER* Power ISA (PPC64), IBMz* (s390x), and RISC-V.
+
+oneDNN is intended for deep learning applications and framework developers 
+interested in improving application performance on CPUs and GPUs.
+
 .. toctree::
+   :caption: About
+   :hidden:
+   :maxdepth: 1
+
+   Introduction<self>
+
+.. toctree::
+   :caption: Get Started 
+   :hidden:
+   :maxdepth: 1
+
+   dev_guide_system_requirements
+   dev_guide_build
+   dev_guide_build_options
+   dev_guide_link
+   
+.. toctree::
+   :caption: Learn oneDNN 
+   :hidden:
+   :maxdepth: 1
+
+   Key Concepts<dev_guide_basic_concepts>
+   Build oneDNN API Basic Workflow<page_getting_started_cpp>
+
+.. toctree::
+   :caption: Developer Guide
+   :hidden:
    :maxdepth: 1
 
-   build_and_link
    programming_model
    supported_primitives
    graph_extension
@@ -12,12 +49,10 @@ oneAPI Deep Neural Network Library (oneDNN) Developer Guide and Reference
    performance_profiling_and_inspection
    advanced_topics
    ukernels
-   group_dnnl_api.rst
 
-oneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform performance library of basic building blocks for deep learning applications. The library is optimized for Intel Architecture Processors, Intel Processor Graphics and Xe Architecture graphics. Support for other architectures such as Arm* 64-bit Architecture (AArch64) and OpenPOWER* Power ISA (PPC64) is experimental.
+.. toctree::
+   :caption: Developer Reference  
+   :hidden:
+   :maxdepth: 1
 
-oneDNN is intended for deep learning applications and framework developers interested in improving application performance. Deep learning practitioners should use one of the applications enabled with oneDNN.
-
-.. rubric:: Reference and Index:
-
-:ref:`genindex`
+   group_dnnl_api.rst

doc/rst/programming_model.rst

@@ -1,11 +1,9 @@
-Programming Model
-#####################
+oneDNN Concepts
+###############
 
 .. toctree::
    :maxdepth: 1
 
-   dev_guide_basic_concepts
-   page_getting_started_cpp
    page_memory_format_propagation_cpp
    dev_guide_inference_and_training_aspects
    dev_guide_attributes