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: ################################################################################ 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>`_. _______________________________________________ cfe-commits mailing list cfe-commits@lists.llvm.org https://lists.llvm.org/cgi-bin/mailman/listinfo/cfe-commits
