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authorDaniel Colascione <dancol@google.com>2017-09-07 02:25:08 +0300
committerLinus Torvalds <torvalds@linux-foundation.org>2017-09-07 03:27:30 +0300
commit493b0e9d945fa9dfe96be93ae41b4ca4b6fdb317 (patch)
treec994839f490d27e9bff0715b90a5c8a124b331ad /Documentation/ABI
parentc79b57e462b5d2f47afa5f175cf1828f16e18612 (diff)
downloadlinux-493b0e9d945fa9dfe96be93ae41b4ca4b6fdb317.tar.xz
mm: add /proc/pid/smaps_rollup
/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: Daniel 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: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
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+What: /proc/pid/smaps_rollup
+Date: August 2017
+Contact: Daniel Colascione <dancol@google.com>
+Description:
+ This file provides pre-summed memory information for a
+ process. The format is identical to /proc/pid/smaps,
+ except instead of an entry for each VMA in a process,
+ smaps_rollup has a single entry (tagged "[rollup]")
+ for which each field is the sum of the corresponding
+ fields from all the maps in /proc/pid/smaps.
+ For more details, see the procfs man page.
+
+ Typical output looks like this:
+
+ 00100000-ff709000 ---p 00000000 00:00 0 [rollup]
+ Rss: 884 kB
+ Pss: 385 kB
+ Shared_Clean: 696 kB
+ Shared_Dirty: 0 kB
+ Private_Clean: 120 kB
+ Private_Dirty: 68 kB
+ Referenced: 884 kB
+ Anonymous: 68 kB
+ LazyFree: 0 kB
+ AnonHugePages: 0 kB
+ ShmemPmdMapped: 0 kB
+ Shared_Hugetlb: 0 kB
+ Private_Hugetlb: 0 kB
+ Swap: 0 kB
+ SwapPss: 0 kB
+ Locked: 385 kB