edit pass for standalone gui analysis

Signed-off-by: Karl W. Schulz <karl.schulz@amd.com>


[ROCm/rocprofiler-compute commit: 50e46453b7]

projects/rocprofiler-compute/src/docs/standalone_gui_analyzer.md

@@ -7,21 +7,31 @@
 ```
 
 ## Features
-Omniperf's standalone GUI analyzer is a lightweight web page that can be generated straight from the command-line. This option is great for users who want immediate access to graphical results without the server-side overhead of the Omniperf's detailed [Grafana interface](https://amdresearch.github.io/omniperf/grafana_analyzer.html#)
 
-The standalone GUI analyzer is a simple Flask web application that uses port forwarding (DEFAULT: 8050) to allow users to view results from their web browser.
+Omniperf's standalone GUI analyzer is a lightweight web page that can
+be generated directly from the command-line. This option is provided
+as an alternative for users wanting to explore profiling results
+graphically, but without the additional setup requirements or
+server-side overhead of Omniperf's detailed [Grafana
+interface](https://amdresearch.github.io/omniperf/grafana_analyzer.html#)
+option.  The standalone GUI analyzer is provided as simple
+[Flask](https://flask.palletsprojects.com/en/2.2.x/) application
+allowing users to view results from within a web browser.
 
-> Because the standalone GUI analyzer uses port forwarding we reccomend users who profile on shared clusters **scp** their results to their personal workstation for analysis.
+```{admonition} Port forwarding
 
-## Useage
-
-To launch the standalone GUI, users will include the `--gui` flag in their analysis command.
-
-```{tip}
-To launch the web application on a port other than 8050 (default)
-use --gui <desired port>
+Note that the standalone GUI analyzer publishes a web interface on port 8050 by default.
+On production HPC systems where profiling jobs run
+under the auspices of a resource manager, additional ssh tunneling
+between the desired web browser host (e.g. login node or remote workstation) and compute host may be
+required. Alternatively, users may find it more convenient to download
+profiled workloads to perform analysis on their local system.
 ```
 
+## Usage
+
+To launch the standalone GUI, include the `--gui` flag with your desired analysis command. For example:
+
 ```bash
 $ omniperf analyze -p workloads/vcopy/mi200/ --gui
 
@@ -42,19 +52,34 @@ Dash is running on http://0.0.0.0:8050/
  * Running on http://10.228.32.139:8050 (Press CTRL+C to quit)
 ```
 
-Users can then lauch their web browser of choice and go to http://localhost:8050/ (substituting port if overridden).
+At this point, users can then launch their web browser of choice and
+go to http://localhost:8050/ to see an analysis page.
+
+
 
 ![Standalone GUI Homepage](images/standalone_gui.png)
 
-When no filters are applied users will see 5 basic section derived from their application's profiling data:
+```{tip}
+To launch the web application on a port other than 8050, include an optional port argument:  
+`--gui <desired port>`
+```
+
+When no filters are applied, users will see five basic sections derived from their application's profiling data:
 
 1. Memory Chart Analysis
 2. Empirical Roofline Analysis
-3. Top Stats (Top Kernal Statistics)
+3. Top Stats (Top Kernel Statistics)
 4. System Info
 5. System Speed-of-Light
 
-To dive deeper, use the top drop down menus to isolate a particular kernel(s) or dispatch(s). You'll then see the webpage updates with metrics specific to the filter you've applied.
+To dive deeper, use the top drop down menus to isolate particular
+kernel(s) or dispatch(s). You will then see the web page update with
+metrics specific to the filter you've applied.
+
+Once you have applied a filter, you will also see several additional
+sections become available with detailed metrics specific to that area
+of AMD hardware. These detailed sections mirror the data displayed in
+Omniperf's [Grafana
+interface](https://amdresearch.github.io/omniperf/grafana_analyzer.html#).
 
-Once you've applied a filter you'll also see several additional sections become availible with detailed metrics specific to that area of AMD hardware. These detailed sections mirror the data we display in Omniperf's [Grafana interface](https://amdresearch.github.io/omniperf/grafana_analyzer.html#)