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    mm: add /proc/pid/smaps_rollup · 493b0e9d
    Daniel Colascione authored
    /proc/pid/smaps_rollup is a new proc file that improves the performance
    of user programs that determine aggregate memory statistics (e.g., total
    PSS) of a process.
    
    Android regularly "samples" the memory usage of various processes in
    order to balance its memory pool sizes.  This sampling process involves
    opening /proc/pid/smaps and summing certain fields.  For very large
    processes, sampling memory use this way can take several hundred
    milliseconds, due mostly to the overhead of the seq_printf calls in
    task_mmu.c.
    
    smaps_rollup improves the situation.  It contains most of the fields of
    /proc/pid/smaps, but instead of a set of fields for each VMA,
    smaps_rollup instead contains one synthetic smaps-format entry
    representing the whole process.  In the single smaps_rollup synthetic
    entry, each field is the summation of the corresponding field in all of
    the real-smaps VMAs.  Using a common format for smaps_rollup and smaps
    allows userspace parsers to repurpose parsers meant for use with
    non-rollup smaps for smaps_rollup, and it allows userspace to switch
    between smaps_rollup and smaps at runtime (say, based on the
    availability of smaps_rollup in a given kernel) with minimal fuss.
    
    By using smaps_rollup instead of smaps, a caller can avoid the
    significant overhead of formatting, reading, and parsing each of a large
    process's potentially very numerous memory mappings.  For sampling
    system_server's PSS in Android, we measured a 12x speedup, representing
    a savings of several hundred milliseconds.
    
    One alternative to a new per-process proc file would have been including
    PSS information in /proc/pid/status.  We considered this option but
    thought that PSS would be too expensive (by a few orders of magnitude)
    to collect relative to what's already emitted as part of
    /proc/pid/status, and slowing every user of /proc/pid/status for the
    sake of readers that happen to want PSS feels wrong.
    
    The code itself works by reusing the existing VMA-walking framework we
    use for regular smaps generation and keeping the mem_size_stats
    structure around between VMA walks instead of using a fresh one for each
    VMA.  In this way, summation happens automatically.  We let seq_file
    walk over the VMAs just as it does for regular smaps and just emit
    nothing to the seq_file until we hit the last VMA.
    
    Benchmarks:
    
        using smaps:
        iterations:1000 pid:1163 pss:220023808
        0m29.46s real 0m08.28s user 0m20.98s system
    
        using smaps_rollup:
        iterations:1000 pid:1163 pss:220702720
        0m04.39s real 0m00.03s user 0m04.31s system
    
    We're using the PSS samples we collect asynchronously for
    system-management tasks like fine-tuning oom_adj_score, memory use
    tracking for debugging, application-level memory-use attribution, and
    deciding whether we want to kill large processes during system idle
    maintenance windows.  Android has been using PSS for these purposes for
    a long time; as the average process VMA count has increased and and
    devices become more efficiency-conscious, PSS-collection inefficiency
    has started to matter more.  IMHO, it'd be a lot safer to optimize the
    existing PSS-collection model, which has been fine-tuned over the years,
    instead of changing the memory tracking approach entirely to work around
    smaps-generation inefficiency.
    
    Tim said:
    
    : There are two main reasons why Android gathers PSS information:
    :
    : 1. Android devices can show the user the amount of memory used per
    :    application via the settings app.  This is a less important use case.
    :
    : 2. We log PSS to help identify leaks in applications.  We have found
    :    an enormous number of bugs (in the Android platform, in Google's own
    :    apps, and in third-party applications) using this data.
    :
    : To do this, system_server (the main process in Android userspace) will
    : sample the PSS of a process three seconds after it changes state (for
    : example, app is launched and becomes the foreground application) and about
    : every ten minutes after that.  The net result is that PSS collection is
    : regularly running on at least one process in the system (usually a few
    : times a minute while the screen is on, less when screen is off due to
    : suspend).  PSS of a process is an incredibly useful stat to track, and we
    : aren't going to get rid of it.  We've looked at some very hacky approaches
    : using RSS ("take the RSS of the target process, subtract the RSS of the
    : zygote process that is the parent of all Android apps") to reduce the
    : accounting time, but it regularly overestimated the memory used by 20+
    : percent.  Accordingly, I don't think that there's a good alternative to
    : using PSS.
    :
    : We started looking into PSS collection performance after we noticed random
    : frequency spikes while a phone's screen was off; occasionally, one of the
    : CPU clusters would ramp to a high frequency because there was 200-300ms of
    : constant CPU work from a single thread in the main Android userspace
    : process.  The work causing the spike (which is reasonable governor
    : behavior given the amount of CPU time needed) was always PSS collection.
    : As a result, Android is burning more power than we should be on PSS
    : collection.
    :
    : The other issue (and why I'm less sure about improving smaps as a
    : long-term solution) is that the number of VMAs per process has increased
    : significantly from release to release.  After trying to figure out why we
    : were seeing these 200-300ms PSS collection times on Android O but had not
    : noticed it in previous versions, we found that the number of VMAs in the
    : main system process increased by 50% from Android N to Android O (from
    : ~1800 to ~2700) and varying increases in every userspace process.  Android
    : M to N also had an increase in the number of VMAs, although not as much.
    : I'm not sure why this is increasing so much over time, but thinking about
    : ASLR and ways to make ASLR better, I expect that this will continue to
    : increase going forward.  I would not be surprised if we hit 5000 VMAs on
    : the main Android process (system_server) by 2020.
    :
    : If we assume that the number of VMAs is going to increase over time, then
    : doing anything we can do to reduce the overhead of each VMA during PSS
    : collection seems like the right way to go, and that means outputting an
    : aggregate statistic (to avoid whatever overhead there is per line in
    : writing smaps and in reading each line from userspace).
    
    Link: http://lkml.kernel.org/r/20170812022148.178293-1-dancol@google.com
    
    
    Signed-off-by: default avatarDaniel Colascione <dancol@google.com>
    Cc: Tim Murray <timmurray@google.com>
    Cc: Joel Fernandes <joelaf@google.com>
    Cc: Al Viro <viro@zeniv.linux.org.uk>
    Cc: Randy Dunlap <rdunlap@infradead.org>
    Cc: Minchan Kim <minchan@kernel.org>
    Cc: Michal Hocko <mhocko@kernel.org>
    Cc: Sonny Rao <sonnyrao@chromium.org>
    Signed-off-by: default avatarAndrew Morton <akpm@linux-foundation.org>
    Signed-off-by: default avatarLinus Torvalds <torvalds@linux-foundation.org>
    493b0e9d