clean up index

Signed-off-by: Peter Jun Park <peter.park@amd.com>

docs/index.rst

@@ -2,48 +2,64 @@
    :description: Omniperf documentation and reference
    :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD
 
-**********************
-Omniperf documentation
-**********************
+********
+Omniperf
+********
 
 Omniperf documentation provides a detailed breakdown of all facets of Omniperf.
-In addition to a full deployment guide with installation instructions, we also
-explain the design of the tool and each of its components.
+In addition to a full deployment guide with installation instructions, this 
+documentation also explains the ideas motivating the design behind the tool and
+its components.
 
-If you're new to Omniperf, gradually acquaint yourself with the tool by 
-following the chapters that following and progressively learn its more advanced
-features. To get started, see :doc:`What is Omniperf? <what-is-omniperf>`.
+If you're new to Omniperf, acquaint yourself with the tool by reviewing the
+chapters that follow and gradually learn its more advanced features. To get
+started, see :doc:`What is Omniperf? <what-is-omniperf>`.
 
 See Omniperf source code at `<https://github.com/ROCm/omniperf>`__.
 
 .. grid:: 2
-    :gutter: 3
+   :gutter: 3
 
-    .. grid-item-card:: Install
+   .. grid-item-card:: Install
 
-        * :doc:`Quick start <install/quick-start>`
-        * :doc:`Install Omniperf <install/omniperf>`
+      * :doc:`install/quick-start`
+      * :doc:`install/omniperf`
 
-    .. grid-item-card:: Conceptual
+   .. grid-item::
 
-        * :doc:`High-level design of Omniperf <conceptual/overview>`
-        * :doc:`Performance model <conceptual/performance-model>`
+Use the following topics to learn more about the advantages of Omniperf in your
+development toolkit, how it aims to model performance, and how to use Omniperf
+in practice.
 
-    .. grid-item-card:: How to
+.. grid:: 2
+   :gutter: 3
+
+   .. grid-item-card:: Conceptual
+
+      * :doc:`conceptual/overview`
+      * :doc:`conceptual/performance-model`
+
+   .. grid-item-card:: How to
 
-        * :doc:`Profiling <how-to/profiling>`
-        * :doc:`Analysis <how-to/analysis>`
+      * :doc:`how-to/profiling`
+      * :doc:`how-to/analysis`
 
-    .. grid-item-card:: Reference
+   .. grid-item-card:: Tutorials
 
-        * :doc:`FAQ <reference/faq>`
-        * :doc:`Glossary <reference/glossary>`
+      * `Omniperf example exercises <https://github.com/amd/HPCTrainingExamples/tree/main/OmniperfExamples>`_
 
-This project is proudly open source and we welcome all feedback! For more
+   .. grid-item-card:: Reference
+
+      * :doc:`reference/compatible-accelerators`
+      * :doc:`reference/faq`
+      * :doc:`reference/glossary`
+      * :doc:`license`
+
+
+This project is proudly open source and we welcome all feedback. For more
 details on how to contribute, refer to `Contributing to ROCm
 <https://rocm.docs.amd.com/en/latest/contribute/contributing.html>`_.
 
 Find licensing information on the
 `Licensing <https://rocm.docs.amd.com/en/latest/about/license.html>`_ page.
 
-

docs/what-is-omniperf.rst

@@ -1,3 +1,7 @@
+.. meta::
+   :description: What is Omniperf?
+   :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD
+
 *****************
 What is Omniperf?
 *****************
@@ -8,70 +12,51 @@ running on AMD Instinct™ accelerators.
 AMD Instinct MI-series accelerators are data center-class GPUs designed for
 compute and have some graphics capabilities disabled or removed. Omniperf
 primarily targets use with
-:doc:`accelerators in the MI100, MI200, and MI300 families <rocm:conceptual/gpu-arch>`.
+:doc:`accelerators in the MI300, MI200, and MI100 families <rocm:conceptual/gpu-arch>`.
 Development is in progress to support Radeon™ (RDNA) GPUs.
 
 Omniperf is built on top of :doc:`ROCProfiler <rocprofiler:rocprofv1>` to
 monitor hardware performance counters.
 
-Features
-========
+Omniperf features
+=================
 
-Omniperf performs profiling based on all available hardware counters for the
-target accelerator. It provides high-level performance analysis features
-including System Speed of Light (SOL), Hardware block-level SOL, Memory Chart
-Analysis, Roofline Analysis, Baseline Comparisons, and more.
+Omniperf offers comprehensive profiling based on all available hardware counters
+for the target accelerator. It delivers advanced performance analysis features,
+such as system speed-of-light (SOL) and hardware block-level SOL evaluations.
+Additionally, Omniperf provides in-depth memory chart analysis, roofline
+analysis, baseline comparisons, and more, ensuring a thorough understanding of
+system performance.
 
 Omniperf supports both command line analysis and GUI analysis.
 
-Detailed feature list:
-
-- MI100 support
-- MI200 support
-- MI300 support
-- Standalone GUI Analyzer
-- Grafana/MongoDB GUI Analyzer
-- Dispatch Filtering
-- Kernel Filtering
-- GPU ID Filtering
-- Baseline Comparison
-- Multi-Normalizations
-- System Info Panel
-- System Speed-of-Light Panel
-- Kernel Statistic Panel
-- Memory Chart Analysis Panel
-- Roofline Analysis Panel (*Supported on MI200 only, Ubuntu 20.04, SLES 15 SP3 or RHEL8*)
-- Command Processor (CP) Panel
-- Workgroup Manager (SPI) Panel
-- Wavefront Launch Panel
-- Compute Unit - Instruction Mix Panel
-- Compute Unit - Pipeline Panel
-- Local Data Share (LDS) Panel
-- Instruction Cache Panel
-- Scalar L1D Cache Panel
-- L1 Address Processing Unit, a.k.a. Texture Addresser (TA) / L1 Backend Data Processing Unit, a.k.a. Texture Data (TD)
-  panel(s)
-- Vector L1D Cache Panel
-- L2 Cache Panel
-- L2 Cache (per-Channel) Panel
-
-Compatible SoCs
-===============
-
-.. list-table::
-    :header-rows: 1
-
-    * - Platform
-      - Status
-
-    * - Vega 20 (MI50/60)
-      - No support
-
-    * - MI100
-      - Supported
-
-    * - MI200
-      - Supported
+Detailed feature list
+---------------------
+
+* :doc:`Support for MI300, MI200, and MI100 <reference/compatible-accelerators>`
+* Standalone GUI analyzer
+* GUI analyzer via Grafana and MongoDB
+* Dispatch filtering
+* Kernel filtering
+* GPU ID filtering
+* Baseline comparison
+* Multiple normalizations
+* *System info* panel
+* *System Speed-of-Light* panel
+* *Kernel Statistic* panel
+* *Memory Chart Analysis* panel
+* *Roofline Analysis* panel (*Supported on MI200 only, Ubuntu 20.04, SLES 15 SP3 or RHEL8*)
+* *Command Processor (CP)* panel
+* *Workgroup Manager (SPI)* panel
+* *Wavefront Launch* Panel
+* *Compute Unit - Instruction Mix* panel
+* *Compute Unit - Pipeline* panel
+* *Local Data Share (LDS)* panel
+* *Instruction Cache* panel
+* *Scalar L1D Cache* panel
+* *L1 Address Processing Unit*, or, *Texture Addresser (TA)* and
+ *L1 Backend Data Processing Unit*, or, *Texture Data (TD)* panels
+* *Vector L1D Cache* panel
+* *L2 Cache* panel
+* *L2 Cache (per-channel)* panel
 
-    * - MI300
-      - Supported