From patchwork Sun Jul 28 20:29:53 2024 Content-Type: text/plain; charset="utf-8" MIME-Version: 1.0 Content-Transfer-Encoding: 8bit X-Patchwork-Submitter: Rong Xu X-Patchwork-Id: 814905 Received: from mail-yb1-f201.google.com (mail-yb1-f201.google.com [209.85.219.201]) (using TLSv1.2 with cipher ECDHE-RSA-AES128-GCM-SHA256 (128/128 bits)) (No client certificate requested) by smtp.subspace.kernel.org (Postfix) with ESMTPS id 07ACE6F312 for ; Sun, 28 Jul 2024 20:30:42 +0000 (UTC) Authentication-Results: smtp.subspace.kernel.org; arc=none smtp.client-ip=209.85.219.201 ARC-Seal: i=1; a=rsa-sha256; d=subspace.kernel.org; s=arc-20240116; t=1722198645; cv=none; b=ckOmol9imqU5ztaCAROo5CS0cz/qIOkaYgLRUPtOGHH2KoVHw9xJDMQxcLHqRAvGh0KjsY0puATWAzW3FRoMbcRG3HMD3DZSmMlmHGH/T51HLWS0uL2AhD75RI7YQrY9bifNq0pAxYfv+6gjOziGC3qg16DKK7YgGzE32sxWIfU= ARC-Message-Signature: i=1; a=rsa-sha256; d=subspace.kernel.org; s=arc-20240116; t=1722198645; c=relaxed/simple; bh=ncQAehrbiYUFhpYdfsf1Rwz5h+YNqrVSI2J3upkP1mE=; h=Date:Mime-Version:Message-ID:Subject:From:To:Cc:Content-Type; b=dalY45fMP6ubMI2AQ295R+zj8g1IluVSYR9jkpThHOFXSkHjaotLghkpdGlt4fixx2ks4HW9/nFn97QW09dVp8c1pTYOvuNkc2o1Sn2Jbyy5JH7kz5etk+kDKGGj107amUkMJhp0qY/VI84JXzajCK0gN0R1HvY3yUuJVW5AVCE= ARC-Authentication-Results: i=1; smtp.subspace.kernel.org; dmarc=pass (p=reject dis=none) header.from=google.com; spf=pass smtp.mailfrom=flex--xur.bounces.google.com; dkim=pass (2048-bit key) header.d=google.com header.i=@google.com header.b=NBT4Q/EF; arc=none smtp.client-ip=209.85.219.201 Authentication-Results: smtp.subspace.kernel.org; dmarc=pass (p=reject dis=none) header.from=google.com Authentication-Results: smtp.subspace.kernel.org; spf=pass smtp.mailfrom=flex--xur.bounces.google.com Authentication-Results: smtp.subspace.kernel.org; dkim=pass (2048-bit key) header.d=google.com header.i=@google.com header.b="NBT4Q/EF" Received: by mail-yb1-f201.google.com with SMTP id 3f1490d57ef6-e0b365efb6cso3149160276.3 for ; Sun, 28 Jul 2024 13:30:42 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20230601; t=1722198642; x=1722803442; darn=vger.kernel.org; h=content-transfer-encoding:cc:to:from:subject:message-id :mime-version:date:from:to:cc:subject:date:message-id:reply-to; bh=vU7GP/dv7Frutc0dmFAU8Vflj8kpPiaVIIi3HMkG8Ic=; b=NBT4Q/EFD4FWT3wQIH/70dZvdVu6x2Npq9vMoEs/e2FhdxO/+IuVrkjH/Vb3pEGxYU 2nedUABoS5iDdjgEKAMiDXg5jy5gzydOj4GVdyDEFaeavarwJb+jcNOeTGKdex/KguU7 LW+ROkJnKxg85oMapcINT8QZk7VrKhBFP004W1K5llYUBd6aF2K90Axi9ovx4OG80K7+ PrXfITNN1Gc0Q3nbX/A6KaATev5B67vSmaJyXnPmPgr8/mEuY1d54588iYyzehmJgB65 tHDLFBBKBobxXIS5C8WYTp0M4BQ1Km2wEBXnYU02hJ4KqTDtnv0Mrl1foyk6/TYIUC49 mSSw== X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1e100.net; s=20230601; t=1722198642; x=1722803442; h=content-transfer-encoding:cc:to:from:subject:message-id :mime-version:date:x-gm-message-state:from:to:cc:subject:date :message-id:reply-to; bh=vU7GP/dv7Frutc0dmFAU8Vflj8kpPiaVIIi3HMkG8Ic=; b=rSOObqVhgw2WHhqLpyDkQROa7Pnn1LGaF+we2FDrcTIRnzDhbX431Zd+2fV0fqfyc1 ZKKW/zWriKXz5Y20H3N9FRoHh/yIWkYlJ3OhZEvtKWkTc8bfNhGhgB6vudpBe4N1Bt9I hlXl7KEwHZMbTlwT2Pwcrqw4zajUXtU5g5y/LTSG+SoZpHtSB5yKVFlgChCJUcMa/Gh4 +GybCDfo0HOKyorjUkvaIY1gytsJsmk+HlSpSNpJKBrr2Bk3v5mL78hg2VYIDoolP0Ny L1WeXl+rLr1rY1Gnd1AD9BK/YIHn7hKHYCAf4n6D+JD50onX94LU86eRhuwl+xYOiY6t Clzw== X-Forwarded-Encrypted: i=1; AJvYcCWHnvrEvq1ivN9pJyjXN3qnELqER/NJwsVNXNeO0b6x882gNJrHtPMLUO5EoYS9zJt83KD28XyJuZ/iZaQB4X0ztCMkOxMCKpPU X-Gm-Message-State: AOJu0YxVVK91OOhclDgCvlUxr4TUPWHV269deS/4vZT8aM97U8M6s87E JZbxeaPjkh/dWRxOnwxHt3D0plRBbRuWCqVHkykckrOY45cQDmiV9Heq8OF/s7t03A== X-Google-Smtp-Source: AGHT+IHQ8sWksXB0JrDTbrpjN2gi6HWebCbj9TLI6Z66yiqxBHhG2zub4bqcDdxYdAB3wKdxtfEYXZU= X-Received: from xur.c.googlers.com ([fda3:e722:ac3:cc00:20:ed76:c0a8:2330]) (user=xur job=sendgmr) by 2002:a05:6902:18c1:b0:e05:6026:f741 with SMTP id 3f1490d57ef6-e0b5442a26bmr459566276.2.1722198641777; Sun, 28 Jul 2024 13:30:41 -0700 (PDT) Date: Sun, 28 Jul 2024 13:29:53 -0700 Precedence: bulk X-Mailing-List: linux-efi@vger.kernel.org List-Id: List-Subscribe: List-Unsubscribe: Mime-Version: 1.0 X-Mailer: git-send-email 2.46.0.rc1.232.g9752f9e123-goog Message-ID: <20240728203001.2551083-1-xur@google.com> Subject: [PATCH 0/6] Add AutoFDO and Propeller support for Clang build From: Rong Xu To: Rong Xu , Han Shen , Sriraman Tallam , David Li , Jonathan Corbet , Masahiro Yamada , Nathan Chancellor , Nicolas Schier , Thomas Gleixner , Ingo Molnar , Borislav Petkov , Dave Hansen , x86@kernel.org, "H . Peter Anvin" , Ard Biesheuvel , Arnd Bergmann , Josh Poimboeuf , Peter Zijlstra , Nick Desaulniers , Bill Wendling , Justin Stitt , Vegard Nossum , John Moon , Andrew Morton , Heiko Carstens , Luis Chamberlain , Samuel Holland , Mike Rapoport , "Paul E . McKenney" , Rafael Aquini , Petr Pavlu , Eric DeVolder , Bjorn Helgaas , Randy Dunlap , Benjamin Segall , Breno Leitao , Wei Yang , Brian Gerst , Juergen Gross , Palmer Dabbelt , Alexandre Ghiti , Kees Cook , Sami Tolvanen , Xiao Wang , Jan Kiszka Cc: linux-doc@vger.kernel.org, linux-kernel@vger.kernel.org, linux-kbuild@vger.kernel.org, linux-efi@vger.kernel.org, linux-arch@vger.kernel.org, llvm@lists.linux.dev 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. 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. 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. 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 Thanks, Rong Xu and Han Shen 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 | 203 ++++++++++++++++++++++++++ Documentation/dev-tools/index.rst | 2 + Documentation/dev-tools/propeller.rst | 188 ++++++++++++++++++++++++ MAINTAINERS | 14 ++ Makefile | 2 + arch/Kconfig | 42 ++++++ arch/x86/Kconfig | 2 + arch/x86/boot/compressed/Makefile | 3 + arch/x86/kernel/vmlinux.lds.S | 4 + arch/x86/platform/efi/Makefile | 1 + drivers/firmware/efi/libstub/Makefile | 2 + include/asm-generic/vmlinux.lds.h | 56 ++++++- scripts/Makefile.autofdo | 22 +++ scripts/Makefile.lib | 20 +++ scripts/Makefile.propeller | 25 ++++ tools/objtool/check.c | 2 + tools/objtool/elf.c | 13 +- 17 files changed, 588 insertions(+), 13 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: 9903efbddba0d14133b5a3c75088b558d2e34ac3