From patchwork Tue Feb 8 08:18:50 2022 Content-Type: text/plain; charset="utf-8" MIME-Version: 1.0 Content-Transfer-Encoding: 7bit X-Patchwork-Submitter: Yu Zhao X-Patchwork-Id: 12738297 Return-Path: X-Spam-Checker-Version: SpamAssassin 3.4.0 (2014-02-07) on aws-us-west-2-korg-lkml-1.web.codeaurora.org Received: from kanga.kvack.org (kanga.kvack.org [205.233.56.17]) by smtp.lore.kernel.org (Postfix) with ESMTP id 8C176C433EF for ; Tue, 8 Feb 2022 08:19:28 +0000 (UTC) Received: by kanga.kvack.org (Postfix) id 201446B008A; Tue, 8 Feb 2022 03:19:28 -0500 (EST) Received: by kanga.kvack.org (Postfix, from userid 40) id 1B1646B008C; Tue, 8 Feb 2022 03:19:28 -0500 (EST) X-Delivered-To: int-list-linux-mm@kvack.org Received: by kanga.kvack.org (Postfix, from userid 63042) id 09F986B0092; Tue, 8 Feb 2022 03:19:28 -0500 (EST) X-Delivered-To: linux-mm@kvack.org Received: from forelay.hostedemail.com (smtprelay0213.hostedemail.com [216.40.44.213]) by kanga.kvack.org (Postfix) with ESMTP id F06B56B008A for ; Tue, 8 Feb 2022 03:19:27 -0500 (EST) Received: from smtpin13.hostedemail.com (10.5.19.251.rfc1918.com [10.5.19.251]) by forelay04.hostedemail.com (Postfix) with ESMTP id AF4BA95AEC for ; Tue, 8 Feb 2022 08:19:27 +0000 (UTC) X-FDA: 79118913174.13.1D823C2 Received: from mail-io1-f73.google.com (mail-io1-f73.google.com [209.85.166.73]) by imf30.hostedemail.com (Postfix) with ESMTP id 47BFB80004 for ; Tue, 8 Feb 2022 08:19:27 +0000 (UTC) Received: by mail-io1-f73.google.com with SMTP id g16-20020a05660226d000b00638d8e1828bso722688ioo.13 for ; Tue, 08 Feb 2022 00:19:27 -0800 (PST) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=google.com; s=20210112; h=date:message-id:mime-version:subject:from:to:cc; bh=CtSEcwwHnFIi4ZeyTyvxpEAgxW/JhSRSL0Dk6q/C1m4=; b=nHxc5M/BKlu2xNwc3dEj94/nTSmwuUbGMp2gKTTlBqdd5VKBwo+Ezpw0SZEr9PuwOY 3ADoj9qDMD2q+i32fRp55g3Rqg2bRQtXK80VOXAK6/+5k2QGu7NPYWIyXNAF0yJ0lF6L hT/Sk8gxycUbomS0lOdgx/Eg+OoWva/E2nfQBqlghy658jbNu4/LqZfbsUo/3Rtn4vUu n7bUsJmeQzIA72z19MnIhDegklwwYnpSMX7LTflS+ZnuEvKml1yXNeuxPv3PSs11cbd2 xAURk+W3F+5k1YrfU6merjtzHYhuel3uoTFSd9DPQhUVNprDpn7c1DdeQnUNG3T+2tFH 19yQ== X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1e100.net; s=20210112; h=x-gm-message-state:date:message-id:mime-version:subject:from:to:cc; bh=CtSEcwwHnFIi4ZeyTyvxpEAgxW/JhSRSL0Dk6q/C1m4=; b=J0aUAnS88zgBppDelH91GmLYlmXuiOMOjtg0QtVjuDFkPz6ajv1UoIgOg4Sj3X/FRc Dw/nnHOpJvSvpMIHNk1LMT2lwmt4Pfj4886VZnQf5poLtGZnR133BFh+Wsrk3yuLtwRG ljJ2Skz3pfkV5vwepi2wUgjVFjLbbDGqqDIIhw4GRdPkYQG6x0rsNsGsPAoDUwABGdcw C5ou5CcT6qbwXmdpc6XjWMv9UCPVQkrqpS3RlBM5Al+1H02rAien74bOQQF6818dRSGL wdCXwiIo777/ikkd+RefZoqPuwwdwo9Pw9d7yZG+4T2lnfVOehvL5qlM3v39C3W1Pa3I zw0Q== X-Gm-Message-State: AOAM530qT7dRHlzdZZO97tyiXC2aoJcV2uIClD7YLb3AV9mZ2rNUandS nxnB9RsBvCf9TMxwNZbeFEEb1Jnt6bM= X-Google-Smtp-Source: ABdhPJxu+5NU4t2KarfhxBSYpIP9Abr9gYxZEgT9m4UKtdOuteaDKhwjFTcY0nZqkbr4/Q2LROD98odB/iA= X-Received: from yuzhao.bld.corp.google.com ([2620:15c:183:200:5f31:19c3:21f5:7300]) (user=yuzhao job=sendgmr) by 2002:a05:6e02:12e6:: with SMTP id l6mr1692122iln.251.1644308366542; Tue, 08 Feb 2022 00:19:26 -0800 (PST) Date: Tue, 8 Feb 2022 01:18:50 -0700 Message-Id: <20220208081902.3550911-1-yuzhao@google.com> Mime-Version: 1.0 X-Mailer: git-send-email 2.35.0.263.gb82422642f-goog Subject: [PATCH v7 00/12] Multigenerational LRU Framework From: Yu Zhao To: Andrew Morton , Johannes Weiner , Mel Gorman , Michal Hocko Cc: Andi Kleen , Aneesh Kumar , Barry Song <21cnbao@gmail.com>, Catalin Marinas , Dave Hansen , Hillf Danton , Jens Axboe , Jesse Barnes , Jonathan Corbet , Linus Torvalds , Matthew Wilcox , Michael Larabel , Mike Rapoport , Rik van Riel , Vlastimil Babka , Will Deacon , Ying Huang , linux-arm-kernel@lists.infradead.org, linux-doc@vger.kernel.org, linux-kernel@vger.kernel.org, linux-mm@kvack.org, page-reclaim@google.com, x86@kernel.org, Yu Zhao Authentication-Results: imf30.hostedemail.com; dkim=pass header.d=google.com header.s=20210112 header.b="nHxc5M/B"; spf=pass (imf30.hostedemail.com: domain of 3jicCYgYKCPs1x2kdrjrrjoh.frpolqx0-ppnydfn.ruj@flex--yuzhao.bounces.google.com designates 209.85.166.73 as permitted sender) smtp.mailfrom=3jicCYgYKCPs1x2kdrjrrjoh.frpolqx0-ppnydfn.ruj@flex--yuzhao.bounces.google.com; dmarc=pass (policy=reject) header.from=google.com X-Stat-Signature: 4ea3itmn89abozyi6rjwo4wzoko57fqr X-Rspamd-Server: rspam12 X-Rspamd-Queue-Id: 47BFB80004 X-Rspam-User: X-HE-Tag: 1644308367-139867 X-Bogosity: Ham, tests=bogofilter, spamicity=0.000000, version=1.2.4 Sender: owner-linux-mm@kvack.org Precedence: bulk X-Loop: owner-majordomo@kvack.org List-ID: What's new ========== 1) Addressed all the comments received on the mailing list and in the meeting with the stakeholders (will note on individual patches). 2) Measured the performance improvements for each patch between 5-8 (reported in the commit messages). TLDR ==== The current page reclaim is too expensive in terms of CPU usage and it often makes poor choices about what to evict. This patchset offers an alternative solution that is performant, versatile and straightforward. Patchset overview ================= The design and implementation overview was moved to patch 12 so that people can finish reading this cover letter. 1. mm: x86, arm64: add arch_has_hw_pte_young() 2. mm: x86: add CONFIG_ARCH_HAS_NONLEAF_PMD_YOUNG Using hardware optimizations when trying to clear the accessed bit in many PTEs. 3. mm/vmscan.c: refactor shrink_node() A minor refactor. 4. mm: multigenerational LRU: groundwork Adding the basic data structure and the functions that insert/remove pages to/from the multigenerational LRU (MGLRU) lists. 5. mm: multigenerational LRU: minimal implementation A minimal (functional) implementation without any optimizations. 6. mm: multigenerational LRU: exploit locality in rmap Improving the efficiency when using the rmap. 7. mm: multigenerational LRU: support page table walks Adding the (optional) page table scanning. 8. mm: multigenerational LRU: optimize multiple memcgs Optimizing the overall performance for multiple memcgs running mixed types of workloads. 9. mm: multigenerational LRU: runtime switch Adding a runtime switch to enable or disable MGLRU. 10. mm: multigenerational LRU: thrashing prevention 11. mm: multigenerational LRU: debugfs interface Providing userspace with additional features like thrashing prevention, working set estimation and proactive reclaim. 12. mm: multigenerational LRU: documentation Adding a design doc and an admin guide. Benchmark results ================= Independent lab results ----------------------- Based on the popularity of searches [01] and the memory usage in Google's public cloud, the most popular open-source memory-hungry applications, in alphabetical order, are: Apache Cassandra Memcached Apache Hadoop MongoDB Apache Spark PostgreSQL MariaDB (MySQL) Redis An independent lab evaluated MGLRU with the most widely used benchmark suites for the above applications. They posted 960 data points along with kernel metrics and perf profiles collected over more than 500 hours of total benchmark time. Their final reports show that, with 95% confidence intervals (CIs), the above applications all performed significantly better for at least part of their benchmark matrices. On 5.14: 1. Apache Spark [02] took 95% CIs [9.28, 11.19]% and [12.20, 14.93]% less wall time to sort three billion random integers, respectively, under the medium- and the high-concurrency conditions, when overcommitting memory. There were no statistically significant changes in wall time for the rest of the benchmark matrix. 2. MariaDB [03] achieved 95% CIs [5.24, 10.71]% and [20.22, 25.97]% more transactions per minute (TPM), respectively, under the medium- and the high-concurrency conditions, when overcommitting memory. There were no statistically significant changes in TPM for the rest of the benchmark matrix. 3. Memcached [04] achieved 95% CIs [23.54, 32.25]%, [20.76, 41.61]% and [21.59, 30.02]% more operations per second (OPS), respectively, for sequential access, random access and Gaussian (distribution) access, when THP=always; 95% CIs [13.85, 15.97]% and [23.94, 29.92]% more OPS, respectively, for random access and Gaussian access, when THP=never. There were no statistically significant changes in OPS for the rest of the benchmark matrix. 4. MongoDB [05] achieved 95% CIs [2.23, 3.44]%, [6.97, 9.73]% and [2.16, 3.55]% more operations per second (OPS), respectively, for exponential (distribution) access, random access and Zipfian (distribution) access, when underutilizing memory; 95% CIs [8.83, 10.03]%, [21.12, 23.14]% and [5.53, 6.46]% more OPS, respectively, for exponential access, random access and Zipfian access, when overcommitting memory. On 5.15: 5. Apache Cassandra [06] achieved 95% CIs [1.06, 4.10]%, [1.94, 5.43]% and [4.11, 7.50]% more operations per second (OPS), respectively, for exponential (distribution) access, random access and Zipfian (distribution) access, when swap was off; 95% CIs [0.50, 2.60]%, [6.51, 8.77]% and [3.29, 6.75]% more OPS, respectively, for exponential access, random access and Zipfian access, when swap was on. 6. Apache Hadoop [07] took 95% CIs [5.31, 9.69]% and [2.02, 7.86]% less average wall time to finish twelve parallel TeraSort jobs, respectively, under the medium- and the high-concurrency conditions, when swap was on. There were no statistically significant changes in average wall time for the rest of the benchmark matrix. 7. PostgreSQL [08] achieved 95% CI [1.75, 6.42]% more transactions per minute (TPM) under the high-concurrency condition, when swap was off; 95% CIs [12.82, 18.69]% and [22.70, 46.86]% more TPM, respectively, under the medium- and the high-concurrency conditions, when swap was on. There were no statistically significant changes in TPM for the rest of the benchmark matrix. 8. Redis [09] achieved 95% CIs [0.58, 5.94]%, [6.55, 14.58]% and [11.47, 19.36]% more total operations per second (OPS), respectively, for sequential access, random access and Gaussian (distribution) access, when THP=always; 95% CIs [1.27, 3.54]%, [10.11, 14.81]% and [8.75, 13.64]% more total OPS, respectively, for sequential access, random access and Gaussian access, when THP=never. Our lab results --------------- To supplement the above results, we ran the following benchmark suites on 5.16-rc7 and found no regressions [10]. (These synthetic benchmarks are popular among MM developers, but we prefer large-scale A/B experiments to validate improvements.) fs_fio_bench_hdd_mq pft fs_lmbench pgsql-hammerdb fs_parallelio redis fs_postmark stream hackbench sysbenchthread kernbench tpcc_spark memcached unixbench multichase vm-scalability mutilate will-it-scale nginx [01] https://trends.google.com [02] https://lore.kernel.org/lkml/20211102002002.92051-1-bot@edi.works/ [03] https://lore.kernel.org/lkml/20211009054315.47073-1-bot@edi.works/ [04] https://lore.kernel.org/lkml/20211021194103.65648-1-bot@edi.works/ [05] https://lore.kernel.org/lkml/20211109021346.50266-1-bot@edi.works/ [06] https://lore.kernel.org/lkml/20211202062806.80365-1-bot@edi.works/ [07] https://lore.kernel.org/lkml/20211209072416.33606-1-bot@edi.works/ [08] https://lore.kernel.org/lkml/20211218071041.24077-1-bot@edi.works/ [09] https://lore.kernel.org/lkml/20211122053248.57311-1-bot@edi.works/ [10] https://lore.kernel.org/lkml/20220104202247.2903702-1-yuzhao@google.com/ Read-world applications ======================= Third-party testimonials ------------------------ Konstantin wrote [11]: I have Archlinux with 8G RAM + zswap + swap. While developing, I have lots of apps opened such as multiple LSP-servers for different langs, chats, two browsers, etc... Usually, my system gets quickly to a point of SWAP-storms, where I have to kill LSP-servers, restart browsers to free memory, etc, otherwise the system lags heavily and is barely usable. 1.5 day ago I migrated from 5.11.15 kernel to 5.12 + the LRU patchset, and I started up by opening lots of apps to create memory pressure, and worked for a day like this. Till now I had *not a single SWAP-storm*, and mind you I got 3.4G in SWAP. I was never getting to the point of 3G in SWAP before without a single SWAP-storm. An anonymous user wrote [12]: Using that v5 for some time and confirm that difference under heavy load and memory pressure is significant. Shuang wrote [13]: With the MGLRU, fio achieved 95% CIs [38.95, 40.26]%, [4.12, 6.64]% and [9.26, 10.36]% higher throughput, respectively, for random access, Zipfian (distribution) access and Gaussian (distribution) access, when the average number of jobs per CPU is 1; 95% CIs [42.32, 49.15]%, [9.44, 9.89]% and [20.99, 22.86]% higher throughput, respectively, for random access, Zipfian access and Gaussian access, when the average number of jobs per CPU is 2. Daniel wrote [14]: With memcached allocating ~100GB of byte-addressable Optante, performance improvement in terms of throughput (measured as queries per second) was about 10% for a series of workloads. Large-scale deployments ----------------------- The downstream kernels that have been using MGLRU include: 1. Android ARCVM [15] 2. Arch Linux Zen [16] 3. Chrome OS [17] 4. Liquorix [18] 5. post-factum [19] 6. XanMod [20] We've rolled out MGLRU to tens of millions of Chrome OS users and about a million Android users. Google's fleetwide profiling [21] shows an overall 40% decrease in kswapd CPU usage, in addition to improvements in other UX metrics, e.g., an 85% decrease in the number of low-memory kills at the 75th percentile and an 18% decrease in rendering latency at the 50th percentile. [11] https://lore.kernel.org/lkml/140226722f2032c86301fbd326d91baefe3d7d23.camel@yandex.ru/ [12] https://phoronix.com/forums/forum/software/general-linux-open-source/1301258-mglru-is-a-very-enticing-enhancement-for-linux-in-2022?p=1301275#post1301275 [13] https://lore.kernel.org/lkml/20220105024423.26409-1-szhai2@cs.rochester.edu/ [14] https://lore.kernel.org/linux-mm/CA+4-3vksGvKd18FgRinxhqHetBS1hQekJE2gwco8Ja-bJWKtFw@mail.gmail.com/ [15] https://chromium.googlesource.com/chromiumos/third_party/kernel [16] https://archlinux.org [17] https://chromium.org [18] https://liquorix.net [19] https://gitlab.com/post-factum/pf-kernel [20] https://xanmod.org [21] https://research.google/pubs/pub44271/ Summery ======= The facts are: 1. The independent lab results and the real-world applications indicate substantial improvements; there are no known regressions. 2. Thrashing prevention, working set estimation and proactive reclaim work out of the box; there are no equivalent solutions. 3. There is a lot of new code; nobody has demonstrated smaller changes with similar effects. Our options, accordingly, are: 1. Given the amount of evidence, the reported improvements will likely materialize for a wide range of workloads. 2. Gauging the interest from the past discussions [22][23][24], the new features will likely be put to use for both personal computers and data centers. 3. Based on Google's track record, the new code will likely be well maintained in the long term. It'd be more difficult if not impossible to achieve similar effects on top of the existing design. [22] https://lore.kernel.org/lkml/20201005081313.732745-1-andrea.righi@canonical.com/ [23] https://lore.kernel.org/lkml/20210716081449.22187-1-sj38.park@gmail.com/ [24] https://lore.kernel.org/lkml/20211130201652.2218636d@mail.inbox.lv/ Yu Zhao (12): mm: x86, arm64: add arch_has_hw_pte_young() mm: x86: add CONFIG_ARCH_HAS_NONLEAF_PMD_YOUNG mm/vmscan.c: refactor shrink_node() mm: multigenerational LRU: groundwork mm: multigenerational LRU: minimal implementation mm: multigenerational LRU: exploit locality in rmap mm: multigenerational LRU: support page table walks mm: multigenerational LRU: optimize multiple memcgs mm: multigenerational LRU: runtime switch mm: multigenerational LRU: thrashing prevention mm: multigenerational LRU: debugfs interface mm: multigenerational LRU: documentation Documentation/admin-guide/mm/index.rst | 1 + Documentation/admin-guide/mm/multigen_lru.rst | 121 + Documentation/vm/index.rst | 1 + Documentation/vm/multigen_lru.rst | 152 + arch/Kconfig | 9 + arch/arm64/include/asm/pgtable.h | 14 +- arch/x86/Kconfig | 1 + arch/x86/include/asm/pgtable.h | 9 +- arch/x86/mm/pgtable.c | 5 +- fs/exec.c | 2 + fs/fuse/dev.c | 3 +- include/linux/cgroup.h | 15 +- include/linux/memcontrol.h | 36 + include/linux/mm.h | 8 + include/linux/mm_inline.h | 214 ++ include/linux/mm_types.h | 78 + include/linux/mmzone.h | 182 ++ include/linux/nodemask.h | 1 + include/linux/page-flags-layout.h | 19 +- include/linux/page-flags.h | 4 +- include/linux/pgtable.h | 17 +- include/linux/sched.h | 4 + include/linux/swap.h | 5 + kernel/bounds.c | 3 + kernel/cgroup/cgroup-internal.h | 1 - kernel/exit.c | 1 + kernel/fork.c | 9 + kernel/sched/core.c | 1 + mm/Kconfig | 50 + mm/huge_memory.c | 3 +- mm/memcontrol.c | 27 + mm/memory.c | 39 +- mm/mm_init.c | 6 +- mm/page_alloc.c | 1 + mm/rmap.c | 7 + mm/swap.c | 55 +- mm/vmscan.c | 2831 ++++++++++++++++- mm/workingset.c | 119 +- 38 files changed, 3908 insertions(+), 146 deletions(-) create mode 100644 Documentation/admin-guide/mm/multigen_lru.rst create mode 100644 Documentation/vm/multigen_lru.rst Tested-by: Vaibhav Jain