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Message-ID: <20241118222540.27495-1-yabinc@google.com>
Date: Mon, 18 Nov 2024 14:25:40 -0800
From: Yabin Cui <yabinc@...gle.com>
To: Rong Xu <xur@...gle.com>, Han Shen <shenhan@...gle.com>, Jonathan Corbet <corbet@....net>,
Catalin Marinas <catalin.marinas@....com>, Will Deacon <will@...nel.org>,
Masahiro Yamada <masahiroy@...nel.org>, Kees Cook <kees@...nel.org>,
Nick Desaulniers <ndesaulniers@...gle.com>, workflows@...r.kernel.org,
linux-doc@...r.kernel.org, linux-kernel@...r.kernel.org,
linux-arm-kernel@...ts.infradead.org
Cc: Yabin Cui <yabinc@...gle.com>
Subject: [PATCH v2] arm64: Allow CONFIG_AUTOFDO_CLANG to be selected
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@...gle.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/@..._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
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