Link to StatProfileHTML in Profile docs (#32650)

* Link to StatProfileHTML

* Update doc/src/manual/profile.md
Update doc/src/manual/profile.md

Co-Authored-By: Tim Holy <[email protected]>
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Co-Authored-By: Tim Holy <[email protected]>
Update doc/src/manual/profile.md

Co-Authored-By: Tim Holy <[email protected]>

Co-authored-by: Tim Holy <[email protected]>

Author: oxinabox

doc/src/manual/profile.md

@@ -57,8 +57,17 @@ julia> using Profile
 julia> @profile myfunc()
 ```
 
-To see the profiling results, there is a [graphical browser](https://github.com/timholy/ProfileView.jl)
-available, but here we'll use the text-based display that comes with the standard library:
+To see the profiling results, there are several graphical browsers.
+One "family" of visualizers is based on [FlameGraphs.jl](https://github.com/timholy/FlameGraphs.jl), with each family member providing a different user interface:
+- [Juno](https://junolab.org/) is a full IDE with built-in support for profile visualization
+- [ProfileView.jl](https://github.com/timholy/ProfileView.jl) is a stand-alone visualizer based on GTK
+- [ProfileVega.jl](https://github.com/davidanthoff/ProfileVega.jl) uses VegaLight and integrates well with Jupyter notebooks
+- [StatProfilerHTML](https://github.com/tkluck/StatProfilerHTML.jl) produces HTML and presents some additional summaries, and also integrates well with Jupyter notebooks
+- [ProfileSVG](https://github.com/timholy/ProfileSVG.jl) renders SVG
+
+An entirely independent approach to profile visualization is [PProf.jl](https://github.com/vchuravy/PProf.jl), which uses the external `pprof` tool.
+
+Here, though, we'll use the text-based display that comes with the standard library:
 
 ```julia-repl
 julia> Profile.print()