| Message ID | 20241118222540.27495-1-yabinc@google.com (mailing list archive) |
|---|---|
| State | New |
| Headers | show |
| Series | [v2] arm64: Allow CONFIG_AUTOFDO_CLANG to be selected | expand |
This patch looks good to me. I assume the profile format change in the Android doc will be submitted soon. Since "extbinary" is a superset of "binary", using the "extbinary" format profile in Android shouldn't cause any compatibility issues. Reviewed-by: Rong Xu <xur.google.com> -Rong On Mon, Nov 18, 2024 at 2:25 PM Yabin Cui <yabinc@google.com> wrote: > > 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 >
Add George from ChromeOS. On Mon, Nov 18, 2024 at 3:49 PM Rong Xu <xur@google.com> wrote: > > This patch looks good to me. > > I assume the profile format change in the Android doc will be submitted soon. > Since "extbinary" is a superset of "binary", using the "extbinary" > format profile > in Android shouldn't cause any compatibility issues. > > Reviewed-by: Rong Xu <xur.google.com> > > -Rong > > On Mon, Nov 18, 2024 at 2:25 PM Yabin Cui <yabinc@google.com> wrote: > > > > 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 > >
We've used ETM in ChromeOS for a while now. Hardware requirements make it unfortunately less ubiquitous than LBR, but: - we first launched it on 5.15, - it's still humming along nicely today on 6.6, so: Tested-by: George Burgess IV <gbiv@google.com> IIRC, with a baseline of "using x86_64 AFDO profiles on ARM kernels," we saw a perf win on the order of a few (3? 4?) percentage points when we made the switch. On Tue, Nov 19, 2024 at 5:04 PM Yabin Cui <yabinc@google.com> wrote: > > Add George from ChromeOS. > > On Mon, Nov 18, 2024 at 3:49 PM Rong Xu <xur@google.com> wrote: > > > > This patch looks good to me. > > > > I assume the profile format change in the Android doc will be submitted soon. > > Since "extbinary" is a superset of "binary", using the "extbinary" > > format profile > > in Android shouldn't cause any compatibility issues. > > > > Reviewed-by: Rong Xu <xur.google.com> > > > > -Rong > > > > On Mon, Nov 18, 2024 at 2:25 PM Yabin Cui <yabinc@google.com> wrote: > > > > > > 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> FWIW, CrOS spells the event 'cs_etm/autofdo/u'. I'm not familiar enough with perf event syntax (or downstream patches that CrOS has to its kernel) to say whether that should motivate a change here. Happy to find out more if there's interest. > > > + $ 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 > > >
On Mon, Nov 18, 2024 at 02:25:40PM -0800, Yabin Cui wrote: > 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> This looks trivial enough to enable. ;) I expect this could go via the kbuild tree (Masahiro) with an arm64 maintainer Ack. FWIW: Reviewed-by: Kees Cook <kees@kernel.org>
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
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(-)