[PATCH v7 00/12] Multigenerational LRU Framework
Oleksandr Natalenko
oleksandr at natalenko.name
Tue Feb 8 02:11:02 PST 2022
Hello.
On úterý 8. února 2022 9:18:50 CET Yu Zhao wrote:
> 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
Thanks for the new spin.
Is the patch submission broken for everyone, or for me only? I see raw emails cluttered with some garbage like =2D, and hence I cannot apply those neither from my email client nor from lore.
Probably, you've got a git repo where things can be pulled from so that we do not depend on mailing systems and/or tools breaking plaintext?
Thanks.
--
Oleksandr Natalenko (post-factum)
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