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    kbuild: Add AutoFDO support for Clang build · 315ad878
    Rong Xu authored
    Add the build support for using Clang's AutoFDO. Building the kernel
    with AutoFDO does not reduce the optimization level from the
    compiler. AutoFDO uses hardware sampling to gather information about
    the frequency of execution of different code paths within a binary.
    This information is then used to guide the compiler's optimization
    decisions, resulting in a more efficient binary. Experiments
    showed that the kernel can improve up to 10% in latency.
    
    The support requires a Clang compiler after LLVM 17. This submission
    is limited to x86 platforms that support PMU features like LBR on
    Intel machines and AMD Zen3 BRS. Support for SPE on ARM 1,
     and BRBE on ARM 1 is part of planned future work.
    
    Here is an example workflow for AutoFDO kernel:
    
    1) Build the kernel on the host machine with LLVM enabled, for example,
           $ make menuconfig LLVM=1
        Turn on AutoFDO build config:
          CONFIG_AUTOFDO_CLANG=y
        With a configuration that has LLVM enabled, use the following
        command:
           scripts/config -e AUTOFDO_CLANG
        After getting the config, build with
          $ make LLVM=1
    
    2) Install the kernel on the test machine.
    
    3) Run the load tests. The '-c' option in perf specifies the sample
       event period. We suggest     using a suitable prime number,
       like 500009, for this purpose.
       For Intel platforms:
          $ perf record -e BR_INST_RETIRED.NEAR_TAKEN:k -a -N -b -c <count> \
            -o <perf_file> -- <loadtest>
       For AMD platforms:
          The supported system are: Zen3 with BRS, or Zen4 with amd_lbr_v2
         For Zen3:
          $ cat proc/cpuinfo | grep " brs"
          For Zen4:
          $ cat proc/cpuinfo | grep amd_lbr_v2
          $ perf record --pfm-events RETIRED_TAKEN_BRANCH_INSTRUCTIONS:k -a \
            -N -b -c <count> -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:
       create_llvm_prof and llvm_profgen. The create_llvm_prof tool is part
       of the AutoFDO project and can be found on GitHub
       (https://github.com/google/autofdo
    
    ), version v0.30.1 or later. The
       llvm_profgen tool is included in the LLVM compiler itself. It's
       important to note that the version of llvm_profgen doesn't need to
       match the version of Clang. It needs to be the LLVM 19 release or
       later, or from the LLVM trunk.
          $ llvm-profgen --kernel --binary=<vmlinux> --perfdata=<perf_file> \
            -o <profile_file>
       or
          $ create_llvm_prof --binary=<vmlinux> --profile=<perf_file> \
            --format=extbinary --out=<profile_file>
    
       Note that multiple AutoFDO profile files can be merged into one via:
          $ llvm-profdata merge -o <profile_file>  <profile_1> ... <profile_n>
    
    6) Rebuild the kernel using the AutoFDO profile file with the same config
       as step 1, (Note CONFIG_AUTOFDO_CLANG needs to be enabled):
          $ make LLVM=1 CLANG_AUTOFDO_PROFILE=<profile_file>
    
    Co-developed-by: default avatarHan Shen <shenhan@google.com>
    Signed-off-by: default avatarHan Shen <shenhan@google.com>
    Signed-off-by: default avatarRong Xu <xur@google.com>
    Suggested-by: default avatarSriraman Tallam <tmsriram@google.com>
    Suggested-by: default avatarKrzysztof Pszeniczny <kpszeniczny@google.com>
    Suggested-by: default avatarNick Desaulniers <ndesaulniers@google.com>
    Suggested-by: default avatarStephane Eranian <eranian@google.com>
    Tested-by: default avatarYonghong Song <yonghong.song@linux.dev>
    Tested-by: default avatarYabin Cui <yabinc@google.com>
    Tested-by: default avatarNathan Chancellor <nathan@kernel.org>
    Reviewed-by: default avatarKees Cook <kees@kernel.org>
    Tested-by: default avatarPeter Jung <ptr1337@cachyos.org>
    Signed-off-by: default avatarMasahiro Yamada <masahiroy@kernel.org>
    315ad878