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pgo.md

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Generating PGO Profiles

Normally devs don't need to worry about this and can use the default profile for official builds. The default profile can be fetched by adding "checkout_pgo_profiles": True to custom_vars in the gclient config and running gclient runhooks.

To produce an executable built with a custom PGO profile:

  • Produce the instrumented executable using the following gn args:

    chrome_pgo_phase = 1
enable_resource_allowlist_generation = false
is_official_build = true
symbol_level = 0
use_goma = true

  • Run representative benchmarks to produce profiles

    • vpython3 tools/perf/run_benchmark system_health.common_desktop --assert-gpu-compositing --run-abridged-story-set --browser=exact --browser-executable=out/path/to/chrome
    • vpython3 tools/perf/run_benchmark speedometer2 --assert-gpu-compositing --browser=exact --browser-executable=out/path/to/chrome
    • This will produce *.profraw files in the current working directory

    If this fails with ServiceException: 401 Anonymous caller does not have storage.objects.get access to the Google Cloud Storage object., then run download_from_google_storage --config (with your @google address; enter 0 as project-id).

  • Merge the profiling data

    • Get the llvm-profdata tool by adding "checkout_clang_coverage_tools": True, to custom_vars in the gclient config and running gclient runhooks.
    • Run third_party/llvm-build/Release+Asserts/bin/llvm-profdata merge *.profraw -o chrome.profdata

  • Produce the final PGO'd executable with the following gn args:

    enable_resource_allowlist_generation = false
is_official_build = true
symbol_level = 0
use_goma = true
pgo_data_path = {path-to-the-profile}