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![T.J. Alumbaugh](/assets/img/avatar_default.png)
Move memcg LRU code into a dedicated section. Improve the design doc to outline its architecture. Link: https://lkml.kernel.org/r/20230118001827.1040870-5-talumbau@google.com Signed-off-by: T.J. Alumbaugh <talumbau@google.com> Cc: Yu Zhao <yuzhao@google.com> Signed-off-by: Andrew Morton <akpm@linux-foundation.org>
235 lines
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ReStructuredText
235 lines
10 KiB
ReStructuredText
.. SPDX-License-Identifier: GPL-2.0
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=============
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Multi-Gen LRU
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=============
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The multi-gen LRU is an alternative LRU implementation that optimizes
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page reclaim and improves performance under memory pressure. Page
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reclaim decides the kernel's caching policy and ability to overcommit
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memory. It directly impacts the kswapd CPU usage and RAM efficiency.
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Design overview
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===============
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Objectives
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----------
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The design objectives are:
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* Good representation of access recency
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* Try to profit from spatial locality
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* Fast paths to make obvious choices
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* Simple self-correcting heuristics
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The representation of access recency is at the core of all LRU
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implementations. In the multi-gen LRU, each generation represents a
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group of pages with similar access recency. Generations establish a
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(time-based) common frame of reference and therefore help make better
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choices, e.g., between different memcgs on a computer or different
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computers in a data center (for job scheduling).
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Exploiting spatial locality improves efficiency when gathering the
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accessed bit. A rmap walk targets a single page and does not try to
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profit from discovering a young PTE. A page table walk can sweep all
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the young PTEs in an address space, but the address space can be too
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sparse to make a profit. The key is to optimize both methods and use
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them in combination.
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Fast paths reduce code complexity and runtime overhead. Unmapped pages
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do not require TLB flushes; clean pages do not require writeback.
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These facts are only helpful when other conditions, e.g., access
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recency, are similar. With generations as a common frame of reference,
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additional factors stand out. But obvious choices might not be good
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choices; thus self-correction is necessary.
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The benefits of simple self-correcting heuristics are self-evident.
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Again, with generations as a common frame of reference, this becomes
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attainable. Specifically, pages in the same generation can be
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categorized based on additional factors, and a feedback loop can
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statistically compare the refault percentages across those categories
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and infer which of them are better choices.
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Assumptions
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-----------
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The protection of hot pages and the selection of cold pages are based
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on page access channels and patterns. There are two access channels:
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* Accesses through page tables
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* Accesses through file descriptors
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The protection of the former channel is by design stronger because:
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1. The uncertainty in determining the access patterns of the former
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channel is higher due to the approximation of the accessed bit.
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2. The cost of evicting the former channel is higher due to the TLB
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flushes required and the likelihood of encountering the dirty bit.
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3. The penalty of underprotecting the former channel is higher because
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applications usually do not prepare themselves for major page
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faults like they do for blocked I/O. E.g., GUI applications
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commonly use dedicated I/O threads to avoid blocking rendering
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threads.
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There are also two access patterns:
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* Accesses exhibiting temporal locality
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* Accesses not exhibiting temporal locality
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For the reasons listed above, the former channel is assumed to follow
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the former pattern unless ``VM_SEQ_READ`` or ``VM_RAND_READ`` is
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present, and the latter channel is assumed to follow the latter
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pattern unless outlying refaults have been observed.
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Workflow overview
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=================
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Evictable pages are divided into multiple generations for each
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``lruvec``. The youngest generation number is stored in
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``lrugen->max_seq`` for both anon and file types as they are aged on
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an equal footing. The oldest generation numbers are stored in
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``lrugen->min_seq[]`` separately for anon and file types as clean file
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pages can be evicted regardless of swap constraints. These three
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variables are monotonically increasing.
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Generation numbers are truncated into ``order_base_2(MAX_NR_GENS+1)``
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bits in order to fit into the gen counter in ``folio->flags``. Each
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truncated generation number is an index to ``lrugen->folios[]``. The
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sliding window technique is used to track at least ``MIN_NR_GENS`` and
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at most ``MAX_NR_GENS`` generations. The gen counter stores a value
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within ``[1, MAX_NR_GENS]`` while a page is on one of
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``lrugen->folios[]``; otherwise it stores zero.
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Each generation is divided into multiple tiers. A page accessed ``N``
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times through file descriptors is in tier ``order_base_2(N)``. Unlike
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generations, tiers do not have dedicated ``lrugen->folios[]``. In
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contrast to moving across generations, which requires the LRU lock,
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moving across tiers only involves atomic operations on
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``folio->flags`` and therefore has a negligible cost. A feedback loop
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modeled after the PID controller monitors refaults over all the tiers
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from anon and file types and decides which tiers from which types to
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evict or protect.
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There are two conceptually independent procedures: the aging and the
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eviction. They form a closed-loop system, i.e., the page reclaim.
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Aging
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-----
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The aging produces young generations. Given an ``lruvec``, it
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increments ``max_seq`` when ``max_seq-min_seq+1`` approaches
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``MIN_NR_GENS``. The aging promotes hot pages to the youngest
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generation when it finds them accessed through page tables; the
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demotion of cold pages happens consequently when it increments
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``max_seq``. The aging uses page table walks and rmap walks to find
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young PTEs. For the former, it iterates ``lruvec_memcg()->mm_list``
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and calls ``walk_page_range()`` with each ``mm_struct`` on this list
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to scan PTEs, and after each iteration, it increments ``max_seq``. For
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the latter, when the eviction walks the rmap and finds a young PTE,
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the aging scans the adjacent PTEs. For both, on finding a young PTE,
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the aging clears the accessed bit and updates the gen counter of the
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page mapped by this PTE to ``(max_seq%MAX_NR_GENS)+1``.
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Eviction
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--------
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The eviction consumes old generations. Given an ``lruvec``, it
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increments ``min_seq`` when ``lrugen->folios[]`` indexed by
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``min_seq%MAX_NR_GENS`` becomes empty. To select a type and a tier to
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evict from, it first compares ``min_seq[]`` to select the older type.
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If both types are equally old, it selects the one whose first tier has
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a lower refault percentage. The first tier contains single-use
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unmapped clean pages, which are the best bet. The eviction sorts a
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page according to its gen counter if the aging has found this page
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accessed through page tables and updated its gen counter. It also
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moves a page to the next generation, i.e., ``min_seq+1``, if this page
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was accessed multiple times through file descriptors and the feedback
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loop has detected outlying refaults from the tier this page is in. To
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this end, the feedback loop uses the first tier as the baseline, for
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the reason stated earlier.
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Working set protection
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----------------------
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Each generation is timestamped at birth. If ``lru_gen_min_ttl`` is
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set, an ``lruvec`` is protected from the eviction when its oldest
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generation was born within ``lru_gen_min_ttl`` milliseconds. In other
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words, it prevents the working set of ``lru_gen_min_ttl`` milliseconds
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from getting evicted. The OOM killer is triggered if this working set
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cannot be kept in memory.
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This time-based approach has the following advantages:
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1. It is easier to configure because it is agnostic to applications
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and memory sizes.
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2. It is more reliable because it is directly wired to the OOM killer.
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Rmap/PT walk feedback
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---------------------
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Searching the rmap for PTEs mapping each page on an LRU list (to test
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and clear the accessed bit) can be expensive because pages from
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different VMAs (PA space) are not cache friendly to the rmap (VA
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space). For workloads mostly using mapped pages, searching the rmap
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can incur the highest CPU cost in the reclaim path.
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``lru_gen_look_around()`` exploits spatial locality to reduce the
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trips into the rmap. It scans the adjacent PTEs of a young PTE and
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promotes hot pages. If the scan was done cacheline efficiently, it
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adds the PMD entry pointing to the PTE table to the Bloom filter. This
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forms a feedback loop between the eviction and the aging.
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Bloom Filters
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-------------
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Bloom filters are a space and memory efficient data structure for set
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membership test, i.e., test if an element is not in the set or may be
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in the set.
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In the eviction path, specifically, in ``lru_gen_look_around()``, if a
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PMD has a sufficient number of hot pages, its address is placed in the
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filter. In the aging path, set membership means that the PTE range
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will be scanned for young pages.
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Note that Bloom filters are probabilistic on set membership. If a test
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is false positive, the cost is an additional scan of a range of PTEs,
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which may yield hot pages anyway. Parameters of the filter itself can
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control the false positive rate in the limit.
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Memcg LRU
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---------
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An memcg LRU is a per-node LRU of memcgs. It is also an LRU of LRUs,
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since each node and memcg combination has an LRU of folios (see
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``mem_cgroup_lruvec()``). Its goal is to improve the scalability of
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global reclaim, which is critical to system-wide memory overcommit in
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data centers. Note that memcg LRU only applies to global reclaim.
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The basic structure of an memcg LRU can be understood by an analogy to
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the active/inactive LRU (of folios):
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1. It has the young and the old (generations), i.e., the counterparts
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to the active and the inactive;
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2. The increment of ``max_seq`` triggers promotion, i.e., the
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counterpart to activation;
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3. Other events trigger similar operations, e.g., offlining an memcg
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triggers demotion, i.e., the counterpart to deactivation.
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In terms of global reclaim, it has two distinct features:
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1. Sharding, which allows each thread to start at a random memcg (in
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the old generation) and improves parallelism;
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2. Eventual fairness, which allows direct reclaim to bail out at will
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and reduces latency without affecting fairness over some time.
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In terms of traversing memcgs during global reclaim, it improves the
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best-case complexity from O(n) to O(1) and does not affect the
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worst-case complexity O(n). Therefore, on average, it has a sublinear
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complexity.
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Summary
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-------
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The multi-gen LRU (of folios) can be disassembled into the following
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parts:
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* Generations
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* Rmap walks
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* Page table walks
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* Bloom filters
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* PID controller
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The aging and the eviction form a producer-consumer model;
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specifically, the latter drives the former by the sliding window over
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generations. Within the aging, rmap walks drive page table walks by
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inserting hot densely populated page tables to the Bloom filters.
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Within the eviction, the PID controller uses refaults as the feedback
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to select types to evict and tiers to protect.
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