Re: [PATCH v4 0/6] Add AutoFDO and Propeller support for Clang build

[Masahiro Yamada <masahiroy@kernel.org>]

On Sun, Oct 20, 2024 at 12:31 PM Nathan Chancellor <nathan@kernel.org> wrote:
>
> Hi Masahiro and Andrew,
>
> Top posting only for visibility. Would it make more sense to have this
> land via the Kbuild tree or -mm? The core of the series really touches
> Kbuild and I think the x86 stuff can just land with Acks, unless the
> -tip folks feel differently. I would like Rong to have a relatively
> clear path forward to mainline once the requisite review and testing has
> accomplished, which requires a shepherd :)


I think I can pick it up if 2/6 gains Ack from an objtool maintainer.






> Cheers,
> Nathan
>
> On Mon, Oct 14, 2024 at 02:33:34PM -0700, Rong Xu wrote:
> > Hi,
> >
> > This patch series is to integrate AutoFDO and Propeller support into
> > the Linux kernel. AutoFDO is a profile-guided optimization technique
> > that leverages hardware sampling to enhance binary performance.
> > Unlike Instrumentation-based FDO (iFDO), AutoFDO offers a user-friendly
> > and straightforward application process. While iFDO generally yields
> > superior profile quality and performance, our findings reveal that
> > AutoFDO achieves remarkable effectiveness, bringing performance close
> > to iFDO for benchmark applications.
> >
> > Propeller is a profile-guided, post-link optimizer that improves
> > the performance of large-scale applications compiled with LLVM. It
> > operates by relinking the binary based on an additional round of runtime
> > profiles, enabling precise optimizations that are not possible at
> > compile time.  Similar to AutoFDO, Propeller too utilizes hardware
> > sampling to collect profiles and apply post-link optimizations to improve
> > the benchmark’s performance over and above AutoFDO.
> >
> > Our empirical data demonstrates significant performance improvements
> > with AutoFDO and Propeller, up to 10% on microbenchmarks and up to 5%
> > on large warehouse-scale benchmarks. This makes a strong case for their
> > inclusion as supported features in the upstream kernel.
> >
> > Background
> >
> > A significant fraction of fleet processing cycles (excluding idle time)
> > from data center workloads are attributable to the kernel. Ware-house
> > scale workloads maximize performance by optimizing the production kernel
> > using iFDO (a.k.a instrumented PGO, Profile Guided Optimization).
> >
> > iFDO can significantly enhance application performance but its use
> > within the kernel has raised concerns. AutoFDO is a variant of FDO that
> > uses the hardware’s Performance Monitoring Unit (PMU) to collect
> > profiling data. While AutoFDO typically yields smaller performance
> > gains than iFDO, it presents unique benefits for optimizing kernels.
> >
> > AutoFDO eliminates the need for instrumented kernels, allowing a single
> > optimized kernel to serve both execution and profile collection. It also
> > minimizes slowdown during profile collection, potentially yielding
> > higher-fidelity profiling, especially for time-sensitive code, compared
> > to iFDO. Additionally, AutoFDO profiles can be obtained from production
> > environments via the hardware’s PMU whereas iFDO profiles require
> > carefully curated load tests that are representative of real-world
> > traffic.
> >
> > AutoFDO facilitates profile collection across diverse targets.
> > Preliminary studies indicate significant variation in kernel hot spots
> > within Google’s infrastructure, suggesting potential performance gains
> > through target-specific kernel customization.
> >
> > Furthermore, other advanced compiler optimization techniques, including
> > ThinLTO and Propeller can be stacked on top of AutoFDO, similar to iFDO.
> > ThinLTO achieves better runtime performance through whole-program
> > analysis and cross module optimizations. The main difference between
> > traditional LTO and ThinLTO is that the latter is scalable in time and
> > memory.
> >
> > This patch series adds AutoFDO and Propeller support to the kernel. The
> > actual solution comes in six parts:
> >
> > [P 1] Add the build support for using AutoFDO in Clang
> >
> >       Add the basic support for AutoFDO build and provide the
> >       instructions for using AutoFDO.
> >
> > [P 2] Fix objtool for bogus warnings when -ffunction-sections is enabled
> >
> > [P 3] Change the subsection ordering when -ffunction-sections is enabled
> >
> > [P 4] Enable –ffunction-sections for the AutoFDO build
> >
> > [P 5] Enable Machine Function Split (MFS) optimization for AutoFDO
> >
> > [P 6] Add Propeller configuration to the kernel build
> >
> > Patch 1 provides basic AutoFDO build support. Patches 2 to 5 further
> > enhance the performance of AutoFDO builds and are functionally dependent
> > on Patch 1. Patch 6 enables support for Propeller and is dependent on
> > patch 2 and patch 3.
> >
> > Caveats
> >
> > AutoFDO is compatible with both GCC and Clang, but the patches in this
> > series are exclusively applicable to LLVM 17 or newer for AutoFDO and
> > LLVM 19 or newer for Propeller. For profile conversion, two different
> > tools could be used, llvm_profgen or create_llvm_prof. llvm_profgen
> > needs to be the LLVM 19 or newer, or just the LLVM trunk. Alternatively,
> > create_llvm_prof v0.30.1 or newer can be used instead of llvm-profgen.
> >
> > Additionally, the build is only supported on x86 platforms equipped
> > with PMU capabilities, such as LBR on Intel machines. More
> > specifically:
> >  * Intel platforms: works on every platform that supports LBR;
> >    we have tested on Skylake.
> >  * AMD platforms: tested on AMD Zen3 with the BRS feature. The kernel
> >    needs to be configured with “CONFIG_PERF_EVENTS_AMD_BRS=y", To
> >    check, use
> >    $ cat /proc/cpuinfo | grep “ brs”
> >    For the AMD Zen4, AMD LBRV2 is supported, but we suspect a bug with
> >    AMD LBRv2 implementation in Genoa which blocks the usage.
> >
> > Experiments and Results
> >
> > Experiments were conducted to compare the performance of AutoFDO-optimized
> > kernel images (version 6.9.x) against default builds.. The evaluation
> > encompassed both open source microbenchmarks and real-world production
> > services from Google and Meta. The selected microbenchmarks included Neper,
> > a network subsystem benchmark, and UnixBench which is a comprehensive suite
> > for assessing various kernel operations.
> >
> > For Neper, AutoFDO optimization resulted in a 6.1% increase in throughput
> > and a 10.6% reduction in latency. Unixbench saw a 2.2% improvement in its
> > index score under low system load and a 2.6% improvement under high system
> > load.
> >
> > For further details on the improvements observed in Google and Meta's
> > production services, please refer to the LLVM discourse post:
> > https://discourse.llvm.org/t/optimizing-the-linux-kernel-with-autofdo-including-thinlto-and-propeller/79108
> ...
> > Rong Xu (6):
> >   Add AutoFDO support for Clang build
> >   objtool: Fix unreachable instruction warnings for weak funcitons
> >   Change the symbols order when --ffuntion-sections is enabled
> >   AutoFDO: Enable -ffunction-sections for the AutoFDO build
> >   AutoFDO: Enable machine function split optimization for AutoFDO
> >   Add Propeller configuration for kernel build.
> >
> >  Documentation/dev-tools/autofdo.rst   | 165 ++++++++++++++++++++++++++
> >  Documentation/dev-tools/index.rst     |   2 +
> >  Documentation/dev-tools/propeller.rst | 161 +++++++++++++++++++++++++
> >  MAINTAINERS                           |  14 +++
> >  Makefile                              |   2 +
> >  arch/Kconfig                          |  42 +++++++
> >  arch/x86/Kconfig                      |   2 +
> >  arch/x86/kernel/vmlinux.lds.S         |   4 +
> >  include/asm-generic/vmlinux.lds.h     |  54 +++++++--
> >  scripts/Makefile.autofdo              |  25 ++++
> >  scripts/Makefile.lib                  |  20 ++++
> >  scripts/Makefile.propeller            |  28 +++++
> >  tools/objtool/check.c                 |   2 +
> >  tools/objtool/elf.c                   |  15 ++-
> >  14 files changed, 524 insertions(+), 12 deletions(-)
> >  create mode 100644 Documentation/dev-tools/autofdo.rst
> >  create mode 100644 Documentation/dev-tools/propeller.rst
> >  create mode 100644 scripts/Makefile.autofdo
> >  create mode 100644 scripts/Makefile.propeller
> >
> >
> > base-commit: eb952c47d154ba2aac794b99c66c3c45eb4cc4ec
> > --
> > 2.47.0.rc1.288.g06298d1525-goog
> >



--
Best Regards
Masahiro Yamada