cb424d7448
verify-patch-sanity.py validates every active recipe .patch has internally- consistent hunk line counts — catching the 'malformed patch at line N' failure at commit/CI/preflight time instead of hours into a cook. This cycle hit that class three times (qtwaylandscanner, sddm, xwayland), each only discovered when cookbook tried to apply the patch. Running it across the repo found 29 latent malformed patches (validated against GNU patch: e.g. relibc/P3-sysv-ipc reproduces 'malformed patch at line 22'). They were harmless only because they sit in vendored recipes (baked, not re- applied) — but would fail on any version-bump re-derivation. --fix recounts the hunk headers (body untouched) and repaired all 29. Wired into build-preflight.sh (Phase 1.0D) and redbear-ci.yml, with a unit test (test-patch-sanity.sh). Skips archived/legacy trees and unvalidatable formats (empty placeholders, bare-@@ git hunks).
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75 lines
4.0 KiB
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===================
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Misexpect
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===================
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.. contents::
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.. toctree::
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:maxdepth: 1
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When developers use ``llvm.expect`` intrinsics, i.e., through use of
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``__builtin_expect(...)``, they are trying to communicate how their code is
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expected to behave at runtime to the optimizer. These annotations, however, can
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be incorrect for a variety of reasons: changes to the code base invalidate them
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silently, the developer mis-annotated them (e.g., using ``LIKELY`` instead of
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``UNLIKELY``), or perhaps they assumed something incorrectly when they wrote
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the annotation. Regardless of why, it is useful to detect these situations so
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that the optimizer can make more useful decisions about the code.
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MisExpect diagnostics are intended to help developers identify and address
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these situations, by comparing the branch weights added by the ``llvm.expect``
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intrinsic to those collected through profiling. Whenever these values are
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mismatched, a diagnostic is surfaced to the user. Details on how the checks
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operate in the LLVM backed can be found in LLVM's documentation.
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By default MisExpect checking is quite strict, because the use of the
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``llvm.expect`` intrinsic is designed for specialized cases, where the outcome
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of a condition is severely skewed. As a result, the optimizer can be extremely
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aggressive, which can result in performance degradation if the outcome is less
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predictable than the annotation suggests. Even when the annotation is correct
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90% of the time, it may be beneficial to either remove the annotation or to use
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a different intrinsic that can communicate the probability more directly.
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Because this may be too strict, MisExpect diagnostics are not enabled by
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default, and support an additional flag to tolerate some deviation from the
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exact thresholds. The ``-fdiagnostic-misexpect-tolerance=N`` accepts
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deviations when comparing branch weights within ``N%`` of the expected values.
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So passing ``-fdiagnostic-misexpect-tolerance=5`` will not report diagnostic messages
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if the branch weight from the profile is within 5% of the weight added by
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the ``llvm.expect`` intrinsic.
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MisExpect diagnostics are also available in the form of optimization remarks,
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which can be serialized and processed through the ``opt-viewer.py``
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scripts in LLVM.
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.. option:: -Rpass=misexpect
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Enables optimization remarks for misexpect when profiling data conflicts with
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use of ``llvm.expect`` intrinsics.
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.. option:: -Wmisexpect
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Enables misexpect warnings when profiling data conflicts with use of
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``llvm.expect`` intrinsics.
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.. option:: -fdiagnostic-misexpect-tolerance=N
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Relaxes misexpect checking to tolerate profiling values within N% of the
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expected branch weight. e.g., a value of ``N=5`` allows misexpect to check against
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``0.95 * Threshold``
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LLVM supports 4 types of profile formats: Frontend, IR, CS-IR, and
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Sampling. MisExpect Diagnostics are compatible with all Profiling formats.
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+----------------+--------------------------------------------------------------------------------------+
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| Profile Type | Description |
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+================+======================================================================================+
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| Frontend | Profiling instrumentation added during compilation by the frontend, i.e. ``clang`` |
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+----------------+--------------------------------------------------------------------------------------+
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| IR | Profiling instrumentation added during by the LLVM backend |
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+----------------+--------------------------------------------------------------------------------------+
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| CS-IR | Context Sensitive IR based profiles |
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+----------------+--------------------------------------------------------------------------------------+
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| Sampling | Profiles collected through sampling with external tools, such as ``perf`` on Linux |
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+----------------+--------------------------------------------------------------------------------------+
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