[PATCH v2] arm64: Allow CONFIG_AUTOFDO_CLANG to be selected

[Yabin Cui <yabinc@google.com>]

Select ARCH_SUPPORTS_AUTOFDO_CLANG to allow AUTOFDO_CLANG to be
selected.

On ARM64, ETM traces can be recorded and converted to AutoFDO profiles.
Experiments on Android show 4% improvement in cold app startup time
and 13% improvement in binder benchmarks.

Signed-off-by: Yabin Cui <yabinc@google.com>
---

Change-Logs in V2:

1. Use "For ARM platforms with ETM trace" in autofdo.rst.
2. Create an issue and a change to use extbinary format in instructions:
   https://github.com/Linaro/OpenCSD/issues/65
   https://android-review.googlesource.com/c/platform/system/extras/+/3362107

 Documentation/dev-tools/autofdo.rst | 18 +++++++++++++++++-
 arch/arm64/Kconfig                  |  1 +
 2 files changed, 18 insertions(+), 1 deletion(-)

diff --git a/Documentation/dev-tools/autofdo.rst b/Documentation/dev-tools/autofdo.rst
index 1f0a451e9ccd..a890e84a2fdd 100644
--- a/Documentation/dev-tools/autofdo.rst
+++ b/Documentation/dev-tools/autofdo.rst
@@ -55,7 +55,7 @@ process consists of the following steps:
    workload to gather execution frequency data. This data is
    collected using hardware sampling, via perf. AutoFDO is most
    effective on platforms supporting advanced PMU features like
-   LBR on Intel machines.
+   LBR on Intel machines, ETM traces on ARM machines.
 
 #. AutoFDO profile generation: Perf output file is converted to
    the AutoFDO profile via offline tools.
@@ -141,6 +141,22 @@ Here is an example workflow for AutoFDO kernel:
 
       $ perf record --pfm-events RETIRED_TAKEN_BRANCH_INSTRUCTIONS:k -a -N -b -c <count> -o <perf_file> -- <loadtest>
 
+   - For ARM platforms with ETM trace:
+
+     Follow the instructions in the `Linaro OpenCSD document
+     https://github.com/Linaro/OpenCSD/blob/master/decoder/tests/auto-fdo/autofdo.md`_
+     to record ETM traces for AutoFDO::
+
+      $ perf record -e cs_etm/@tmc_etr0/k -a -o <etm_perf_file> -- <loadtest>
+      $ perf inject -i <etm_perf_file> -o <perf_file> --itrace=i500009il
+
+     For ARM platforms running Android, follow the instructions in the
+     `Android simpleperf document
+     <https://android.googlesource.com/platform/system/extras/+/main/simpleperf/doc/collect_etm_data_for_autofdo.md>`_
+     to record ETM traces for AutoFDO::
+
+      $ simpleperf record -e cs-etm:k -a -o <perf_file> -- <loadtest>
+
 4) (Optional) Download the raw perf file to the host machine.
 
 5) To generate an AutoFDO profile, two offline tools are available:
diff --git a/arch/arm64/Kconfig b/arch/arm64/Kconfig
index fd9df6dcc593..c3814df5e391 100644
--- a/arch/arm64/Kconfig
+++ b/arch/arm64/Kconfig
@@ -103,6 +103,7 @@ config ARM64
 	select ARCH_SUPPORTS_PER_VMA_LOCK
 	select ARCH_SUPPORTS_HUGE_PFNMAP if TRANSPARENT_HUGEPAGE
 	select ARCH_SUPPORTS_RT
+	select ARCH_SUPPORTS_AUTOFDO_CLANG
 	select ARCH_WANT_BATCHED_UNMAP_TLB_FLUSH
 	select ARCH_WANT_COMPAT_IPC_PARSE_VERSION if COMPAT
 	select ARCH_WANT_DEFAULT_BPF_JIT
-- 
2.47.0.338.g60cca15819-goog