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This commit adds documents for DAMON under `Documentation/admin-guide/mm/damon/` and `Documentation/vm/damon/`. Link: https://lkml.kernel.org/r/20210716081449.22187-11-sj38.park@gmail.com Signed-off-by: SeongJae Park <sjpark@amazon.de> Reviewed-by: Fernand Sieber <sieberf@amazon.com> Reviewed-by: Markus Boehme <markubo@amazon.de> Cc: Alexander Shishkin <alexander.shishkin@linux.intel.com> Cc: Amit Shah <amit@kernel.org> Cc: Benjamin Herrenschmidt <benh@kernel.crashing.org> Cc: Brendan Higgins <brendanhiggins@google.com> Cc: David Hildenbrand <david@redhat.com> Cc: David Rientjes <rientjes@google.com> Cc: David Woodhouse <dwmw@amazon.com> Cc: Fan Du <fan.du@intel.com> Cc: Greg Kroah-Hartman <greg@kroah.com> Cc: Greg Thelen <gthelen@google.com> Cc: Ingo Molnar <mingo@redhat.com> Cc: Joe Perches <joe@perches.com> Cc: Jonathan Cameron <Jonathan.Cameron@huawei.com> Cc: Jonathan Corbet <corbet@lwn.net> Cc: Leonard Foerster <foersleo@amazon.de> Cc: Marco Elver <elver@google.com> Cc: Maximilian Heyne <mheyne@amazon.de> Cc: Mel Gorman <mgorman@suse.de> Cc: Minchan Kim <minchan@kernel.org> Cc: Namhyung Kim <namhyung@kernel.org> Cc: Peter Zijlstra <peterz@infradead.org> Cc: Rik van Riel <riel@surriel.com> Cc: Shakeel Butt <shakeelb@google.com> Cc: Shuah Khan <shuah@kernel.org> Cc: Steven Rostedt (VMware) <rostedt@goodmis.org> Cc: Vladimir Davydov <vdavydov.dev@gmail.com> Cc: Vlastimil Babka <vbabka@suse.cz> Signed-off-by: Andrew Morton <akpm@linux-foundation.org> Signed-off-by: Linus Torvalds <torvalds@linux-foundation.org>
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.. SPDX-License-Identifier: GPL-2.0
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==========================
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DAMON: Data Access MONitor
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==========================
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DAMON is a data access monitoring framework subsystem for the Linux kernel.
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The core mechanisms of DAMON (refer to :doc:`design` for the detail) make it
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- *accurate* (the monitoring output is useful enough for DRAM level memory
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management; It might not appropriate for CPU Cache levels, though),
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- *light-weight* (the monitoring overhead is low enough to be applied online),
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and
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- *scalable* (the upper-bound of the overhead is in constant range regardless
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of the size of target workloads).
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Using this framework, therefore, the kernel's memory management mechanisms can
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make advanced decisions. Experimental memory management optimization works
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that incurring high data accesses monitoring overhead could implemented again.
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In user space, meanwhile, users who have some special workloads can write
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personalized applications for better understanding and optimizations of their
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workloads and systems.
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.. toctree::
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:maxdepth: 2
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faq
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design
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api
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plans
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