[clang] 6fe8543 - [analyzer][docs] Mention perfetto for visualizing trace JSONs (#145500)

[via cfe-commits]

Author: Balázs Benics
Date: 2025-06-24T14:49:43+02:00
New Revision: 6fe8543a2a15a2dc793790605b56d865b70c64ea

URL: https://github.com/llvm/llvm-project/commit/6fe8543a2a15a2dc793790605b56d865b70c64ea
DIFF: https://github.com/llvm/llvm-project/commit/6fe8543a2a15a2dc793790605b56d865b70c64ea.diff

LOG: [analyzer][docs] Mention perfetto for visualizing trace JSONs (#145500)

Added: 
    

Modified: 
    clang/docs/analyzer/developer-docs/PerformanceInvestigation.rst

Removed: 
    


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diff  --git a/clang/docs/analyzer/developer-docs/PerformanceInvestigation.rst b/clang/docs/analyzer/developer-docs/PerformanceInvestigation.rst
index ca3a56828209b..5d662cfb65be2 100644
--- a/clang/docs/analyzer/developer-docs/PerformanceInvestigation.rst
+++ b/clang/docs/analyzer/developer-docs/PerformanceInvestigation.rst
@@ -10,7 +10,7 @@ Performance analysis using ``-ftime-trace``
 
 You can add the ``-ftime-trace=file.json`` option to break down the analysis time into individual entry points and steps within each entry point.
 You can explore the generated JSON file in a Chromium browser using the ``chrome://tracing`` URL,
-or using `speedscope <https://speedscope.app>`_.
+or using `perfetto <https://ui.perfetto.dev>`_ or `speedscope <https://speedscope.app>`_.
 Once you narrow down to specific analysis steps you are interested in, you can more effectively employ heavier profilers,
 such as `Perf <https://perfwiki.github.io/main/>`_ and `Callgrind <https://valgrind.org/docs/manual/cl-manual.html>`_.