[PATCH v29 10/13] Documentation: Add documents for DAMON
From: SeongJae Park
Date: Thu May 20 2021 - 03:57:37 EST
From: SeongJae Park <sjpark@xxxxxxxxx>
This commit adds documents for DAMON under
`Documentation/admin-guide/mm/damon/` and `Documentation/vm/damon/`.
Signed-off-by: SeongJae Park <sjpark@xxxxxxxxx>
---
Documentation/admin-guide/mm/damon/guide.rst | 158 +++++++++++++
Documentation/admin-guide/mm/damon/index.rst | 15 ++
Documentation/admin-guide/mm/damon/plans.rst | 29 +++
Documentation/admin-guide/mm/damon/start.rst | 114 +++++++++
Documentation/admin-guide/mm/damon/usage.rst | 112 +++++++++
Documentation/admin-guide/mm/index.rst | 1 +
Documentation/vm/damon/api.rst | 20 ++
Documentation/vm/damon/design.rst | 166 +++++++++++++
Documentation/vm/damon/eval.rst | 232 +++++++++++++++++++
Documentation/vm/damon/faq.rst | 58 +++++
Documentation/vm/damon/index.rst | 31 +++
Documentation/vm/index.rst | 1 +
12 files changed, 937 insertions(+)
create mode 100644 Documentation/admin-guide/mm/damon/guide.rst
create mode 100644 Documentation/admin-guide/mm/damon/index.rst
create mode 100644 Documentation/admin-guide/mm/damon/plans.rst
create mode 100644 Documentation/admin-guide/mm/damon/start.rst
create mode 100644 Documentation/admin-guide/mm/damon/usage.rst
create mode 100644 Documentation/vm/damon/api.rst
create mode 100644 Documentation/vm/damon/design.rst
create mode 100644 Documentation/vm/damon/eval.rst
create mode 100644 Documentation/vm/damon/faq.rst
create mode 100644 Documentation/vm/damon/index.rst
diff --git a/Documentation/admin-guide/mm/damon/guide.rst b/Documentation/admin-guide/mm/damon/guide.rst
new file mode 100644
index 000000000000..f52dc1669bb1
--- /dev/null
+++ b/Documentation/admin-guide/mm/damon/guide.rst
@@ -0,0 +1,158 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+==================
+Optimization Guide
+==================
+
+This document helps you estimating the amount of benefit that you could get
+from DAMON-based optimizations, and describes how you could achieve it. You
+are assumed to already read :doc:`start`.
+
+
+Check The Signs
+===============
+
+No optimization can provide same extent of benefit to every case. Therefore
+you should first guess how much improvements you could get using DAMON. If
+some of below conditions match your situation, you could consider using DAMON.
+
+- *Low IPC and High Cache Miss Ratios.* Low IPC means most of the CPU time is
+ spent waiting for the completion of time-consuming operations such as memory
+ access, while high cache miss ratios mean the caches don't help it well.
+ DAMON is not for cache level optimization, but DRAM level. However,
+ improving DRAM management will also help this case by reducing the memory
+ operation latency.
+- *Memory Over-commitment and Unknown Users.* If you are doing memory
+ overcommitment and you cannot control every user of your system, a memory
+ bank run could happen at any time. You can estimate when it will happen
+ based on DAMON's monitoring results and act earlier to avoid or deal better
+ with the crisis.
+- *Frequent Memory Pressure.* Frequent memory pressure means your system has
+ wrong configurations or memory hogs. DAMON will help you find the right
+ configuration and/or the criminals.
+- *Heterogeneous Memory System.* If your system is utilizing memory devices
+ that placed between DRAM and traditional hard disks, such as non-volatile
+ memory or fast SSDs, DAMON could help you utilizing the devices more
+ efficiently.
+
+
+Profile
+=======
+
+If you found some positive signals, you could start by profiling your workloads
+using DAMON. Find major workloads on your systems and analyze their data
+access pattern to find something wrong or can be improved. The DAMON user
+space tool (``damo``) will be useful for this. You can get ``damo`` from
+https://github.com/awslabs/damo.
+
+We recommend you to start from working set size distribution check using ``damo
+report wss``. If the distribution is ununiform or quite different from what
+you estimated, you could consider `Memory Configuration`_ optimization.
+
+Then, review the overall access pattern in heatmap form using ``damo report
+heats``. If it shows a simple pattern consists of a small number of memory
+regions having high contrast of access temperature, you could consider manual
+`Program Modification`_.
+
+If you still want to absorb more benefits, you should develop `Personalized
+DAMON Application`_ for your special case.
+
+You don't need to take only one approach among the above plans, but you could
+use multiple of the above approaches to maximize the benefit.
+
+
+Optimize
+========
+
+If the profiling result also says it's worth trying some optimization, you
+could consider below approaches. Note that some of the below approaches assume
+that your systems are configured with swap devices or other types of auxiliary
+memory so that you don't strictly required to accommodate the whole working set
+in the main memory. Most of the detailed optimization should be made on your
+concrete understanding of your memory devices.
+
+
+Memory Configuration
+--------------------
+
+No more no less, DRAM should be large enough to accommodate only important
+working sets, because DRAM is highly performance critical but expensive and
+heavily consumes the power. However, knowing the size of the real important
+working sets is difficult. As a consequence, people usually equips
+unnecessarily large or too small DRAM. Many problems stem from such wrong
+configurations.
+
+Using the working set size distribution report provided by ``damo report wss``,
+you can know the appropriate DRAM size for you. For example, roughly speaking,
+if you worry about only 95 percentile latency, you don't need to equip DRAM of
+a size larger than 95 percentile working set size.
+
+Let's see a real example. This `page
+<https://damonitor.github.io/doc/html/v17/admin-guide/mm/damon/guide.html#memory-configuration>`_
+shows the heatmap and the working set size distributions/changes of
+``freqmine`` workload in PARSEC3 benchmark suite. The working set size spikes
+up to 180 MiB, but keeps smaller than 50 MiB for more than 95% of the time.
+Even though you give only 50 MiB of memory space to the workload, it will work
+well for 95% of the time. Meanwhile, you can save the 130 MiB of memory space.
+
+
+Program Modification
+--------------------
+
+If the data access pattern heatmap plotted by ``damo report heats`` is quite
+simple so that you can understand how the things are going in the workload with
+your human eye, you could manually optimize the memory management.
+
+For example, suppose that the workload has two big memory object but only one
+object is frequently accessed while the other one is only occasionally
+accessed. Then, you could modify the program source code to keep the hot
+object in the main memory by invoking ``mlock()`` or ``madvise()`` with
+``MADV_WILLNEED``. Or, you could proactively evict the cold object using
+``madvise()`` with ``MADV_COLD`` or ``MADV_PAGEOUT``. Using both together
+would be also worthy.
+
+A research work [1]_ using the ``mlock()`` achieved up to 2.55x performance
+speedup.
+
+Let's see another realistic example access pattern for this kind of
+optimizations. This `page
+<https://damonitor.github.io/doc/html/v17/admin-guide/mm/damon/guide.html#program-modification>`_
+shows the visualized access patterns of streamcluster workload in PARSEC3
+benchmark suite. We can easily identify the 100 MiB sized hot object.
+
+
+Personalized DAMON Application
+------------------------------
+
+Above approaches will work well for many general cases, but would not enough
+for some special cases.
+
+If this is the case, it might be the time to forget the comfortable use of the
+user space tool and dive into the debugfs interface (refer to :doc:`usage` for
+the detail) of DAMON. Using the interface, you can control the DAMON more
+flexibly. Therefore, you can write your personalized DAMON application that
+controls the monitoring via the debugfs interface, analyzes the result, and
+applies complex optimizations itself. Using this, you can make more creative
+and wise optimizations.
+
+If you are a kernel space programmer, writing kernel space DAMON applications
+using the API (refer to the :doc:`/vm/damon/api` for more detail) would be an
+option.
+
+
+Reference Practices
+===================
+
+Referencing previously done successful practices could help you getting the
+sense for this kind of optimizations. There is an academic paper [1]_
+reporting the visualized access pattern and manual `Program
+Modification`_ results for a number of realistic workloads. You can also get
+the visualized access patterns [3]_ [4]_ [5]_ and automated DAMON-based memory
+operations results for other realistic workloads that collected with latest
+version of DAMON [2]_ .
+
+.. [1] https://dl.acm.org/doi/10.1145/3366626.3368125
+.. [2] https://damonitor.github.io/test/result/perf/latest/html/
+.. [3] https://damonitor.github.io/test/result/visual/latest/rec.heatmap.1.png.html
+.. [4] https://damonitor.github.io/test/result/visual/latest/rec.wss_sz.png.html
+.. [5] https://damonitor.github.io/test/result/visual/latest/rec.wss_time.png.html
diff --git a/Documentation/admin-guide/mm/damon/index.rst b/Documentation/admin-guide/mm/damon/index.rst
new file mode 100644
index 000000000000..0baae7a5402b
--- /dev/null
+++ b/Documentation/admin-guide/mm/damon/index.rst
@@ -0,0 +1,15 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+========================
+Monitoring Data Accesses
+========================
+
+:doc:`DAMON </vm/damon/index>` allows light-weight data access monitoring.
+Using this, users can analyze and optimize their systems.
+
+.. toctree::
+ :maxdepth: 2
+
+ start
+ guide
+ usage
diff --git a/Documentation/admin-guide/mm/damon/plans.rst b/Documentation/admin-guide/mm/damon/plans.rst
new file mode 100644
index 000000000000..e3aa5ab96c29
--- /dev/null
+++ b/Documentation/admin-guide/mm/damon/plans.rst
@@ -0,0 +1,29 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+============
+Future Plans
+============
+
+DAMON is still on its first stage. Below plans are still under development.
+
+
+Automate Data Access Monitoring-based Memory Operation Schemes Execution
+========================================================================
+
+The ultimate goal of DAMON is to be used as a building block for the data
+access pattern aware kernel memory management optimization. It will make
+system just works efficiently. However, some users having very special
+workloads will want to further do their own optimization. DAMON will automate
+most of the tasks for such manual optimizations in near future. Users will be
+required to only describe what kind of data access pattern-based operation
+schemes they want in a simple form.
+
+By applying a very simple scheme for THP promotion/demotion with a prototype
+implementation, DAMON reduced 60% of THP memory footprint overhead while
+preserving 50% of the THP performance benefit. The detailed results can be
+seen on an external web page [1]_.
+
+Several RFC patchsets for this plan are available [2]_.
+
+.. [1] https://damonitor.github.io/test/result/perf/latest/html/
+.. [2] https://lore.kernel.org/linux-mm/20200616073828.16509-1-sjpark@xxxxxxxxxx/
diff --git a/Documentation/admin-guide/mm/damon/start.rst b/Documentation/admin-guide/mm/damon/start.rst
new file mode 100644
index 000000000000..f5bbf1e36836
--- /dev/null
+++ b/Documentation/admin-guide/mm/damon/start.rst
@@ -0,0 +1,114 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+===============
+Getting Started
+===============
+
+This document briefly describes how you can use DAMON by demonstrating its
+default user space tool. Please note that this document describes only a part
+of its features for brevity. Please refer to :doc:`usage` for more details.
+
+
+TL; DR
+======
+
+Follow below commands to monitor and visualize the access pattern of your
+workload. ::
+
+ # # build the kernel with CONFIG_DAMON_*=y, install it, and reboot
+ # mount -t debugfs none /sys/kernel/debug/
+ # git clone https://github.com/awslabs/damo
+ # ./damo/damo record $(pidof <your workload>)
+ # ./damo/damo report heat --plot_ascii
+
+The final command draws the access heatmap of ``<your workload>``, heatmap,
+which shows when (y-axis) what memory region (x-axis) is how frequently
+accessed (number). ::
+
+ 111111111111111111111111111111111111111111111111111111110000
+ 111121111111111111111111111111211111111111111111111111110000
+ 000000000000000000000000000000000000000000000000001555552000
+ 000000000000000000000000000000000000000000000222223555552000
+ 000000000000000000000000000000000000000011111677775000000000
+ 000000000000000000000000000000000000000488888000000000000000
+ 000000000000000000000000000000000177888400000000000000000000
+ 000000000000000000000000000046666522222100000000000000000000
+ 000000000000000000000014444344444300000000000000000000000000
+ 000000000000000002222245555510000000000000000000000000000000
+ # access_frequency: 0 1 2 3 4 5 6 7 8 9
+ # x-axis: space (140286319947776-140286426374096: 101.496 MiB)
+ # y-axis: time (605442256436361-605479951866441: 37.695430s)
+ # resolution: 60x10 (1.692 MiB and 3.770s for each character)
+
+
+Prerequisites
+=============
+
+Kernel
+------
+
+You should first ensure your system is running on a kernel built with
+``CONFIG_DAMON_*=y``.
+
+
+User Space Tool
+---------------
+
+For the demonstration, we will use the default user space tool for DAMON,
+called DAMON Operator (DAMO). It is available at
+https://github.com/awslabs/damo. For brevity, below examples assume you set
+``$PATH`` to point it. It's not mandatory, though.
+
+Because DAMO is using the debugfs interface (refer to :doc:`usage` for the
+detail) of DAMON, you should ensure debugfs is mounted. Mount it manually as
+below::
+
+ # mount -t debugfs none /sys/kernel/debug/
+
+or append below line to your ``/etc/fstab`` file so that your system can
+automatically mount debugfs from next booting::
+
+ debugfs /sys/kernel/debug debugfs defaults 0 0
+
+
+Recording Data Access Patterns
+==============================
+
+Below commands record memory access pattern of a program and save the
+monitoring results in a file. ::
+
+ $ git clone https://github.com/sjp38/masim
+ $ cd masim; make; ./masim ./configs/zigzag.cfg &
+ $ sudo damo record -o damon.data $(pidof masim)
+
+The first two lines of the commands get an artificial memory access generator
+program and runs it in the background. It will repeatedly access two 100 MiB
+sized memory regions one by one. You can substitute this with your real
+workload. The last line asks ``damo`` to record the access pattern in
+``damon.data`` file.
+
+
+Visualizing Recorded Patterns
+=============================
+
+Below three commands visualize the recorded access patterns into three
+image files. ::
+
+ $ damo report heats --heatmap access_pattern_heatmap.png
+ $ damo report wss --range 0 101 1 --plot wss_dist.png
+ $ damo report wss --range 0 101 1 --sortby time --plot wss_chron_change.png
+
+- ``access_pattern_heatmap.png`` will show the data access pattern in a
+ heatmap, which shows when (x-axis) what memory region (y-axis) is how
+ frequently accessed (color).
+- ``wss_dist.png`` will show the distribution of the working set size.
+- ``wss_chron_change.png`` will show how the working set size has
+ chronologically changed.
+
+You can show the images in a web page [1]_ . Those made with other realistic
+workloads are also available [2]_ [3]_ [4]_.
+
+.. [1] https://damonitor.github.io/doc/html/v17/admin-guide/mm/damon/start.html#visualizing-recorded-patterns
+.. [2] https://damonitor.github.io/test/result/visual/latest/rec.heatmap.1.png.html
+.. [3] https://damonitor.github.io/test/result/visual/latest/rec.wss_sz.png.html
+.. [4] https://damonitor.github.io/test/result/visual/latest/rec.wss_time.png.html
diff --git a/Documentation/admin-guide/mm/damon/usage.rst b/Documentation/admin-guide/mm/damon/usage.rst
new file mode 100644
index 000000000000..ea3fa6e55f8b
--- /dev/null
+++ b/Documentation/admin-guide/mm/damon/usage.rst
@@ -0,0 +1,112 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+===============
+Detailed Usages
+===============
+
+DAMON provides below three interfaces for different users.
+
+- *DAMON user space tool.*
+ This is for privileged people such as system administrators who want a
+ just-working human-friendly interface. Using this, users can use the DAMON’s
+ major features in a human-friendly way. It may not be highly tuned for
+ special cases, though. It supports only virtual address spaces monitoring.
+- *debugfs interface.*
+ This is for privileged user space programmers who want more optimized use of
+ DAMON. Using this, users can use DAMON’s major features by reading
+ from and writing to special debugfs files. Therefore, you can write and use
+ your personalized DAMON debugfs wrapper programs that reads/writes the
+ debugfs files instead of you. The DAMON user space tool is also a reference
+ implementation of such programs. It supports only virtual address spaces
+ monitoring.
+- *Kernel Space Programming Interface.*
+ This is for kernel space programmers. Using this, users can utilize every
+ feature of DAMON most flexibly and efficiently by writing kernel space
+ DAMON application programs for you. You can even extend DAMON for various
+ address spaces.
+
+Nevertheless, you could write your own user space tool using the debugfs
+interface. A reference implementation is available at
+https://github.com/awslabs/damo. If you are a kernel programmer, you could
+refer to :doc:`/vm/damon/api` for the kernel space programming interface. For
+the reason, this document describes only the debugfs interface
+
+debugfs Interface
+=================
+
+DAMON exports three files, ``attrs``, ``target_ids``, and ``monitor_on`` under
+its debugfs directory, ``<debugfs>/damon/``.
+
+
+Attributes
+----------
+
+Users can get and set the ``sampling interval``, ``aggregation interval``,
+``regions update interval``, and min/max number of monitoring target regions by
+reading from and writing to the ``attrs`` file. To know about the monitoring
+attributes in detail, please refer to the :doc:`/vm/damon/design`. For
+example, below commands set those values to 5 ms, 100 ms, 1,000 ms, 10 and
+1000, and then check it again::
+
+ # cd <debugfs>/damon
+ # echo 5000 100000 1000000 10 1000 > attrs
+ # cat attrs
+ 5000 100000 1000000 10 1000
+
+
+Target IDs
+----------
+
+Some types of address spaces supports multiple monitoring target. For example,
+the virtual memory address spaces monitoring can have multiple processes as the
+monitoring targets. Users can set the targets by writing relevant id values of
+the targets to, and get the ids of the current targets by reading from the
+``target_ids`` file. In case of the virtual address spaces monitoring, the
+values should be pids of the monitoring target processes. For example, below
+commands set processes having pids 42 and 4242 as the monitoring targets and
+check it again::
+
+ # cd <debugfs>/damon
+ # echo 42 4242 > target_ids
+ # cat target_ids
+ 42 4242
+
+Note that setting the target ids doesn't start the monitoring.
+
+
+Turning On/Off
+--------------
+
+Setting the files as described above doesn't incur effect unless you explicitly
+start the monitoring. You can start, stop, and check the current status of the
+monitoring by writing to and reading from the ``monitor_on`` file. Writing
+``on`` to the file starts the monitoring of the targets with the attributes.
+Writing ``off`` to the file stops those. DAMON also stops if every target
+process is terminated. Below example commands turn on, off, and check the
+status of DAMON::
+
+ # cd <debugfs>/damon
+ # echo on > monitor_on
+ # echo off > monitor_on
+ # cat monitor_on
+ off
+
+Please note that you cannot write to the above-mentioned debugfs files while
+the monitoring is turned on. If you write to the files while DAMON is running,
+an error code such as ``-EBUSY`` will be returned.
+
+
+Tracepoint for Monitoring Results
+=================================
+
+DAMON provides the monitoring results via a tracepoint,
+``damon:damon_aggregated``. While the monitoring is turned on, you could
+record the tracepoint events and show results using tracepoint supporting tools
+like ``perf``. For example::
+
+ # echo on > monitor_on
+ # perf record damon:damon_aggregated &
+ # sleep 5
+ # kill 9 $(pidof perf)
+ # echo off > monitor_on
+ # perf script
diff --git a/Documentation/admin-guide/mm/index.rst b/Documentation/admin-guide/mm/index.rst
index 4b14d8b50e9e..cbd19d5e625f 100644
--- a/Documentation/admin-guide/mm/index.rst
+++ b/Documentation/admin-guide/mm/index.rst
@@ -27,6 +27,7 @@ the Linux memory management.
concepts
cma_debugfs
+ damon/index
hugetlbpage
idle_page_tracking
ksm
diff --git a/Documentation/vm/damon/api.rst b/Documentation/vm/damon/api.rst
new file mode 100644
index 000000000000..08f34df45523
--- /dev/null
+++ b/Documentation/vm/damon/api.rst
@@ -0,0 +1,20 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+=============
+API Reference
+=============
+
+Kernel space programs can use every feature of DAMON using below APIs. All you
+need to do is including ``damon.h``, which is located in ``include/linux/`` of
+the source tree.
+
+Structures
+==========
+
+.. kernel-doc:: include/linux/damon.h
+
+
+Functions
+=========
+
+.. kernel-doc:: mm/damon/core.c
diff --git a/Documentation/vm/damon/design.rst b/Documentation/vm/damon/design.rst
new file mode 100644
index 000000000000..727d72093f8f
--- /dev/null
+++ b/Documentation/vm/damon/design.rst
@@ -0,0 +1,166 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+======
+Design
+======
+
+Configurable Layers
+===================
+
+DAMON provides data access monitoring functionality while making the accuracy
+and the overhead controllable. The fundamental access monitorings require
+primitives that dependent on and optimized for the target address space. On
+the other hand, the accuracy and overhead tradeoff mechanism, which is the core
+of DAMON, is in the pure logic space. DAMON separates the two parts in
+different layers and defines its interface to allow various low level
+primitives implementations configurable with the core logic.
+
+Due to this separated design and the configurable interface, users can extend
+DAMON for any address space by configuring the core logics with appropriate low
+level primitive implementations. If appropriate one is not provided, users can
+implement the primitives on their own.
+
+For example, physical memory, virtual memory, swap space, those for specific
+processes, NUMA nodes, files, and backing memory devices would be supportable.
+Also, if some architectures or devices support special optimized access check
+primitives, those will be easily configurable.
+
+
+Reference Implementations of Address Space Specific Primitives
+==============================================================
+
+The low level primitives for the fundamental access monitoring are defined in
+two parts:
+
+1. Identification of the monitoring target address range for the address space.
+2. Access check of specific address range in the target space.
+
+DAMON currently provides the implementation of the primitives for only the
+virtual address spaces. Below two subsections describe how it works.
+
+
+PTE Accessed-bit Based Access Check
+-----------------------------------
+
+The implementation for the virtual address space uses PTE Accessed-bit for
+basic access checks. It finds the relevant PTE Accessed bit from the address
+by walking the page table for the target task of the address. In this way, the
+implementation finds and clears the bit for next sampling target address and
+checks whether the bit set again after one sampling period. This could disturb
+other kernel subsystems using the Accessed bits, namely Idle page tracking and
+the reclaim logic. To avoid such disturbances, DAMON makes it mutually
+exclusive with Idle page tracking and uses ``PG_idle`` and ``PG_young`` page
+flags to solve the conflict with the reclaim logic, as Idle page tracking does.
+
+
+VMA-based Target Address Range Construction
+-------------------------------------------
+
+Only small parts in the super-huge virtual address space of the processes are
+mapped to the physical memory and accessed. Thus, tracking the unmapped
+address regions is just wasteful. However, because DAMON can deal with some
+level of noise using the adaptive regions adjustment mechanism, tracking every
+mapping is not strictly required but could even incur a high overhead in some
+cases. That said, too huge unmapped areas inside the monitoring target should
+be removed to not take the time for the adaptive mechanism.
+
+For the reason, this implementation converts the complex mappings to three
+distinct regions that cover every mapped area of the address space. The two
+gaps between the three regions are the two biggest unmapped areas in the given
+address space. The two biggest unmapped areas would be the gap between the
+heap and the uppermost mmap()-ed region, and the gap between the lowermost
+mmap()-ed region and the stack in most of the cases. Because these gaps are
+exceptionally huge in usual address spaces, excluding these will be sufficient
+to make a reasonable trade-off. Below shows this in detail::
+
+ <heap>
+ <BIG UNMAPPED REGION 1>
+ <uppermost mmap()-ed region>
+ (small mmap()-ed regions and munmap()-ed regions)
+ <lowermost mmap()-ed region>
+ <BIG UNMAPPED REGION 2>
+ <stack>
+
+
+Address Space Independent Core Mechanisms
+=========================================
+
+Below four sections describe each of the DAMON core mechanisms and the five
+monitoring attributes, ``sampling interval``, ``aggregation interval``,
+``regions update interval``, ``minimum number of regions``, and ``maximum
+number of regions``.
+
+
+Access Frequency Monitoring
+---------------------------
+
+The output of DAMON says what pages are how frequently accessed for a given
+duration. The resolution of the access frequency is controlled by setting
+``sampling interval`` and ``aggregation interval``. In detail, DAMON checks
+access to each page per ``sampling interval`` and aggregates the results. In
+other words, counts the number of the accesses to each page. After each
+``aggregation interval`` passes, DAMON calls callback functions that previously
+registered by users so that users can read the aggregated results and then
+clears the results. This can be described in below simple pseudo-code::
+
+ while monitoring_on:
+ for page in monitoring_target:
+ if accessed(page):
+ nr_accesses[page] += 1
+ if time() % aggregation_interval == 0:
+ for callback in user_registered_callbacks:
+ callback(monitoring_target, nr_accesses)
+ for page in monitoring_target:
+ nr_accesses[page] = 0
+ sleep(sampling interval)
+
+The monitoring overhead of this mechanism will arbitrarily increase as the
+size of the target workload grows.
+
+
+Region Based Sampling
+---------------------
+
+To avoid the unbounded increase of the overhead, DAMON groups adjacent pages
+that assumed to have the same access frequencies into a region. As long as the
+assumption (pages in a region have the same access frequencies) is kept, only
+one page in the region is required to be checked. Thus, for each ``sampling
+interval``, DAMON randomly picks one page in each region, waits for one
+``sampling interval``, checks whether the page is accessed meanwhile, and
+increases the access frequency of the region if so. Therefore, the monitoring
+overhead is controllable by setting the number of regions. DAMON allows users
+to set the minimum and the maximum number of regions for the trade-off.
+
+This scheme, however, cannot preserve the quality of the output if the
+assumption is not guaranteed.
+
+
+Adaptive Regions Adjustment
+---------------------------
+
+Even somehow the initial monitoring target regions are well constructed to
+fulfill the assumption (pages in same region have similar access frequencies),
+the data access pattern can be dynamically changed. This will result in low
+monitoring quality. To keep the assumption as much as possible, DAMON
+adaptively merges and splits each region based on their access frequency.
+
+For each ``aggregation interval``, it compares the access frequencies of
+adjacent regions and merges those if the frequency difference is small. Then,
+after it reports and clears the aggregated access frequency of each region, it
+splits each region into two or three regions if the total number of regions
+will not exceed the user-specified maximum number of regions after the split.
+
+In this way, DAMON provides its best-effort quality and minimal overhead while
+keeping the bounds users set for their trade-off.
+
+
+Dynamic Target Space Updates Handling
+-------------------------------------
+
+The monitoring target address range could dynamically changed. For example,
+virtual memory could be dynamically mapped and unmapped. Physical memory could
+be hot-plugged.
+
+As the changes could be quite frequent in some cases, DAMON checks the dynamic
+memory mapping changes and applies it to the abstracted target area only for
+each of a user-specified time interval (``regions update interval``).
diff --git a/Documentation/vm/damon/eval.rst b/Documentation/vm/damon/eval.rst
new file mode 100644
index 000000000000..4ce1a6d86036
--- /dev/null
+++ b/Documentation/vm/damon/eval.rst
@@ -0,0 +1,232 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+==========
+Evaluation
+==========
+
+DAMON is lightweight. It increases system memory usage by 0.39% and slows
+target workloads down by 1.16%.
+
+DAMON is accurate and useful for memory management optimizations. An
+experimental DAMON-based operation scheme for THP, namely 'ethp', removes
+76.15% of THP memory overheads while preserving 51.25% of THP speedup. Another
+experimental DAMON-based 'proactive reclamation' implementation, namely 'prcl',
+reduces 93.38% of residential sets and 23.63% of system memory footprint while
+incurring only 1.22% runtime overhead in the best case (parsec3/freqmine).
+
+
+Setup
+=====
+
+On QEMU/KVM based virtual machines utilizing 130GB of RAM and 36 vCPUs hosted
+by AWS EC2 i3.metal instances that running a kernel that v24 DAMON patchset is
+applied, I measure runtime and consumed system memory while running various
+realistic workloads with several configurations. From each of PARSEC3 [3]_ and
+SPLASH-2X [4]_ benchmark suites I pick 12 workloads, so I use 24 workloads in
+total. I use another wrapper scripts [5]_ for convenient setup and run of the
+workloads.
+
+
+Measurement
+-----------
+
+For the measurement of the amount of consumed memory in system global scope, I
+drop caches before starting each of the workloads and monitor 'MemFree' in the
+'/proc/meminfo' file. To make results more stable, I repeat the runs 5 times
+and average results.
+
+
+Configurations
+--------------
+
+The configurations I use are as below.
+
+- orig: Linux v5.10 with 'madvise' THP policy
+- rec: 'orig' plus DAMON running with virtual memory access recording
+- prec: 'orig' plus DAMON running with physical memory access recording
+- thp: same with 'orig', but use 'always' THP policy
+- ethp: 'orig' plus a DAMON operation scheme, 'efficient THP'
+- prcl: 'orig' plus a DAMON operation scheme, 'proactive reclaim [6]_'
+
+I use 'rec' for measurement of DAMON overheads to target workloads and system
+memory. 'prec' is for physical memory monitroing and recording. It monitors
+17GB sized 'System RAM' region. The remaining configs including 'thp', 'ethp',
+and 'prcl' are for measurement of DAMON monitoring accuracy.
+
+'ethp' and 'prcl' are simple DAMON-based operation schemes developed for
+proof of concepts of DAMON. 'ethp' reduces memory space waste of THP by using
+DAMON for the decision of promotions and demotion for huge pages, while 'prcl'
+is as similar as the original work. For example, those can be implemented as
+below::
+
+ # format: <min/max size> <min/max frequency (0-100)> <min/max age> <action>
+ # ethp: Use huge pages if a region shows >=5% access rate, use regular
+ # pages if a region >=2MB shows 0 access rate for >=7 seconds
+ min max 5 max min max hugepage
+ 2M max min min 7s max nohugepage
+
+ # prcl: If a region >=4KB shows 0 access rate for >=5 seconds, page out.
+ 4K max 0 0 5s max pageout
+
+Note that these examples are designed with my only straightforward intuition
+because those are for only proof of concepts and monitoring accuracy of DAMON.
+In other words, those are not for production. For production use, those should
+be more tuned. For automation of such tuning, you can use a user space tool
+called DAMOOS [8]_. For the evaluation, we use 'ethp' as same to above
+example, but we use DAMOOS-tuned 'prcl' for each workload.
+
+The evaluation is done using the tests package for DAMON, ``damon-tests`` [7]_.
+Using it, you can do the evaluation and generate a report on your own.
+
+.. [1] "Redis latency problems troubleshooting", https://redis.io/topics/latency
+.. [2] "Disable Transparent Huge Pages (THP)",
+ https://docs.mongodb.com/manual/tutorial/transparent-huge-pages/
+.. [3] "The PARSEC Becnhmark Suite", https://parsec.cs.princeton.edu/index.htm
+.. [4] "SPLASH-2x", https://parsec.cs.princeton.edu/parsec3-doc.htm#splash2x
+.. [5] "parsec3_on_ubuntu", https://github.com/sjp38/parsec3_on_ubuntu
+.. [6] "Proactively reclaiming idle memory", https://lwn.net/Articles/787611/
+.. [7] "damon-tests", https://github.com/awslabs/damon-tests
+.. [8] "DAMOOS", https://github.com/awslabs/damoos
+
+
+Results
+=======
+
+Below two tables show the measurement results. The runtimes are in seconds
+while the memory usages are in KiB. Each configuration except 'orig' shows
+its overhead relative to 'orig' in percent within parenthesizes.::
+
+ runtime orig rec (overhead) prec (overhead) thp (overhead) ethp (overhead) prcl (overhead)
+ parsec3/blackscholes 139.658 140.168 (0.37) 139.385 (-0.20) 138.367 (-0.92) 139.279 (-0.27) 147.024 (5.27)
+ parsec3/bodytrack 123.788 124.622 (0.67) 123.636 (-0.12) 125.115 (1.07) 123.840 (0.04) 141.928 (14.65)
+ parsec3/canneal 207.491 210.318 (1.36) 217.927 (5.03) 174.287 (-16.00) 202.609 (-2.35) 225.483 (8.67)
+ parsec3/dedup 18.292 18.301 (0.05) 18.378 (0.47) 18.264 (-0.15) 18.298 (0.03) 20.541 (12.30)
+ parsec3/facesim 343.893 340.286 (-1.05) 338.217 (-1.65) 332.953 (-3.18) 333.840 (-2.92) 365.650 (6.33)
+ parsec3/fluidanimate 339.959 326.886 (-3.85) 330.286 (-2.85) 331.239 (-2.57) 326.011 (-4.10) 341.684 (0.51)
+ parsec3/freqmine 445.987 436.332 (-2.16) 435.946 (-2.25) 435.704 (-2.31) 437.595 (-1.88) 451.414 (1.22)
+ parsec3/raytrace 184.106 182.158 (-1.06) 182.056 (-1.11) 183.180 (-0.50) 183.545 (-0.30) 202.197 (9.83)
+ parsec3/streamcluster 599.990 674.091 (12.35) 617.314 (2.89) 521.864 (-13.02) 551.971 (-8.00) 696.127 (16.02)
+ parsec3/swaptions 220.462 222.637 (0.99) 220.449 (-0.01) 219.921 (-0.25) 221.607 (0.52) 223.956 (1.59)
+ parsec3/vips 87.767 88.700 (1.06) 87.461 (-0.35) 87.466 (-0.34) 87.875 (0.12) 91.768 (4.56)
+ parsec3/x264 110.843 117.856 (6.33) 113.023 (1.97) 108.665 (-1.97) 115.434 (4.14) 117.811 (6.29)
+ splash2x/barnes 131.441 129.275 (-1.65) 128.341 (-2.36) 119.317 (-9.22) 126.199 (-3.99) 147.602 (12.30)
+ splash2x/fft 59.705 58.382 (-2.22) 58.858 (-1.42) 45.949 (-23.04) 59.939 (0.39) 64.548 (8.11)
+ splash2x/lu_cb 132.552 131.604 (-0.72) 131.846 (-0.53) 132.320 (-0.18) 132.100 (-0.34) 140.289 (5.84)
+ splash2x/lu_ncb 150.215 149.670 (-0.36) 149.646 (-0.38) 148.823 (-0.93) 149.416 (-0.53) 152.338 (1.41)
+ splash2x/ocean_cp 84.033 76.405 (-9.08) 75.104 (-10.63) 73.487 (-12.55) 77.789 (-7.43) 77.380 (-7.92)
+ splash2x/ocean_ncp 153.833 154.247 (0.27) 156.227 (1.56) 106.619 (-30.69) 139.299 (-9.45) 165.030 (7.28)
+ splash2x/radiosity 143.566 143.654 (0.06) 142.426 (-0.79) 141.193 (-1.65) 141.740 (-1.27) 157.817 (9.93)
+ splash2x/radix 49.984 49.996 (0.02) 50.519 (1.07) 46.573 (-6.82) 50.724 (1.48) 50.695 (1.42)
+ splash2x/raytrace 133.238 134.337 (0.83) 134.389 (0.86) 134.833 (1.20) 131.073 (-1.62) 145.541 (9.23)
+ splash2x/volrend 121.700 120.652 (-0.86) 120.560 (-0.94) 120.629 (-0.88) 119.581 (-1.74) 129.422 (6.35)
+ splash2x/water_nsquared 370.771 375.236 (1.20) 376.829 (1.63) 355.592 (-4.09) 354.087 (-4.50) 419.606 (13.17)
+ splash2x/water_spatial 133.295 132.931 (-0.27) 132.762 (-0.40) 133.090 (-0.15) 133.809 (0.39) 153.647 (15.27)
+ total 4486.580 4538.750 (1.16) 4481.600 (-0.11) 4235.430 (-5.60) 4357.660 (-2.87) 4829.510 (7.64)
+
+
+ memused.avg orig rec (overhead) prec (overhead) thp (overhead) ethp (overhead) prcl (overhead)
+ parsec3/blackscholes 1828693.600 1834084.000 (0.29) 1823839.800 (-0.27) 1819296.600 (-0.51) 1830281.800 (0.09) 1603975.800 (-12.29)
+ parsec3/bodytrack 1424963.400 1440085.800 (1.06) 1438384.200 (0.94) 1421718.400 (-0.23) 1432834.600 (0.55) 1439283.000 (1.00)
+ parsec3/canneal 1036782.600 1052828.800 (1.55) 1050148.600 (1.29) 1035104.400 (-0.16) 1051145.400 (1.39) 1050019.400 (1.28)
+ parsec3/dedup 2511841.400 2507374.000 (-0.18) 2472450.600 (-1.57) 2523557.600 (0.47) 2508912.000 (-0.12) 2493347.200 (-0.74)
+ parsec3/facesim 537769.800 550740.800 (2.41) 548683.600 (2.03) 543547.800 (1.07) 560556.600 (4.24) 482782.600 (-10.23)
+ parsec3/fluidanimate 570268.600 585598.000 (2.69) 579837.800 (1.68) 571433.000 (0.20) 582112.800 (2.08) 470073.400 (-17.57)
+ parsec3/freqmine 982941.400 996253.200 (1.35) 993919.800 (1.12) 990531.800 (0.77) 1000994.400 (1.84) 750685.800 (-23.63)
+ parsec3/raytrace 1737446.000 1749908.800 (0.72) 1741183.800 (0.22) 1726674.800 (-0.62) 1748530.200 (0.64) 1552275.600 (-10.66)
+ parsec3/streamcluster 115857.000 155194.400 (33.95) 158272.800 (36.61) 122125.200 (5.41) 134545.600 (16.13) 133448.600 (15.18)
+ parsec3/swaptions 13694.200 28451.800 (107.76) 28464.600 (107.86) 12797.800 (-6.55) 25328.200 (84.96) 28138.400 (105.48)
+ parsec3/vips 2976126.400 3002408.600 (0.88) 3008218.800 (1.08) 2978258.600 (0.07) 2995428.600 (0.65) 2936338.600 (-1.34)
+ parsec3/x264 3233886.200 3258790.200 (0.77) 3248355.000 (0.45) 3232070.000 (-0.06) 3256360.200 (0.69) 3254707.400 (0.64)
+ splash2x/barnes 1210470.600 1211918.600 (0.12) 1204507.000 (-0.49) 1210892.800 (0.03) 1217414.800 (0.57) 944053.400 (-22.01)
+ splash2x/fft 9697440.000 9604535.600 (-0.96) 9210571.800 (-5.02) 9867368.000 (1.75) 9637571.800 (-0.62) 9804092.000 (1.10)
+ splash2x/lu_cb 510680.400 521792.600 (2.18) 517724.600 (1.38) 513500.800 (0.55) 519980.600 (1.82) 351787.000 (-31.11)
+ splash2x/lu_ncb 512896.200 529353.600 (3.21) 521248.600 (1.63) 513493.200 (0.12) 523793.400 (2.12) 418701.600 (-18.37)
+ splash2x/ocean_cp 3320800.200 3313688.400 (-0.21) 3225585.000 (-2.87) 3359032.200 (1.15) 3316591.800 (-0.13) 3304702.200 (-0.48)
+ splash2x/ocean_ncp 3915132.400 3917401.000 (0.06) 3884086.400 (-0.79) 7050398.600 (80.08) 4532528.600 (15.77) 3920395.800 (0.13)
+ splash2x/radiosity 1456908.200 1467611.800 (0.73) 1453612.600 (-0.23) 1466695.400 (0.67) 1467495.600 (0.73) 421197.600 (-71.09)
+ splash2x/radix 2345874.600 2318202.200 (-1.18) 2261499.200 (-3.60) 2438228.400 (3.94) 2373697.800 (1.19) 2336605.600 (-0.40)
+ splash2x/raytrace 43258.800 57624.200 (33.21) 55164.600 (27.52) 46204.400 (6.81) 60475.000 (39.80) 48865.400 (12.96)
+ splash2x/volrend 149615.000 163809.400 (9.49) 162115.400 (8.36) 149119.600 (-0.33) 162747.800 (8.78) 157734.600 (5.43)
+ splash2x/water_nsquared 40384.400 54848.600 (35.82) 53796.600 (33.21) 41455.800 (2.65) 53226.400 (31.80) 58260.600 (44.27)
+ splash2x/water_spatial 670580.200 680444.200 (1.47) 670020.400 (-0.08) 668262.400 (-0.35) 678552.000 (1.19) 372931.000 (-44.39)
+ total 40844300.000 41002900.000 (0.39) 40311600.000 (-1.30) 44301900.000 (8.47) 41671052.000 (2.02) 38334431.000 (-6.14)
+
+
+DAMON Overheads
+---------------
+
+In total, DAMON virtual memory access recording feature ('rec') incurs 1.16%
+runtime overhead and 0.39% memory space overhead. Even though the size of the
+monitoring target region becomes much larger with the physical memory access
+recording ('prec'), it still shows only modest amount of overhead (-0.11% for
+runtime and -1.30% for memory footprint).
+
+For a convenient test run of 'rec' and 'prec', I use a Python wrapper. The
+wrapper constantly consumes about 10-15MB of memory. This becomes a high
+memory overhead if the target workload has a small memory footprint.
+Nonetheless, the overheads are not from DAMON, but from the wrapper, and thus
+should be ignored. This fake memory overhead continues in 'ethp' and 'prcl',
+as those configurations are also using the Python wrapper.
+
+
+Efficient THP
+-------------
+
+THP 'always' enabled policy achieves 5.60% speedup but incurs 8.47% memory
+overhead. It achieves 30.69% speedup in the best case, but 80.08% memory
+overhead in the worst case. Interestingly, both the best and worst-case are
+with 'splash2x/ocean_ncp').
+
+The 2-lines implementation of data access monitoring based THP version ('ethp')
+shows 2.87% speedup and 2.02% memory overhead. In other words, 'ethp' removes
+76.15% of THP memory waste while preserving 51.25% of THP speedup in total. In
+the case of the 'splash2x/ocean_ncp', 'ethp' removes 80.30% of THP memory waste
+while preserving 30.79% of THP speedup.
+
+
+Proactive Reclamation
+---------------------
+
+As similar to the original work, I use 4G 'zram' swap device for this
+configuration. Also note that we use DAMOOS-tuned ethp schemes for each
+workload.
+
+In total, our 1 line implementation of Proactive Reclamation, 'prcl', incurred
+7.64% runtime overhead in total while achieving 6.14% system memory footprint
+reduction. Even in the worst case, the runtime overhead was only 16.02%.
+
+Nonetheless, as the memory usage is calculated with 'MemFree' in
+'/proc/meminfo', it contains the SwapCached pages. As the swapcached pages can
+be easily evicted, I also measured the residential set size of the workloads::
+
+ rss.avg orig rec (overhead) prec (overhead) thp (overhead) ethp (overhead) prcl (overhead)
+ parsec3/blackscholes 587536.800 585720.000 (-0.31) 586233.400 (-0.22) 587045.400 (-0.08) 586753.400 (-0.13) 252207.400 (-57.07)
+ parsec3/bodytrack 32302.200 32290.600 (-0.04) 32261.800 (-0.13) 32215.800 (-0.27) 32173.000 (-0.40) 6798.800 (-78.95)
+ parsec3/canneal 842370.600 841443.400 (-0.11) 844012.400 (0.19) 838074.400 (-0.51) 841700.800 (-0.08) 840804.000 (-0.19)
+ parsec3/dedup 1180414.800 1164634.600 (-1.34) 1188886.200 (0.72) 1207821.000 (2.32) 1193896.200 (1.14) 572359.200 (-51.51)
+ parsec3/facesim 311848.400 311709.800 (-0.04) 311790.800 (-0.02) 317345.800 (1.76) 315443.400 (1.15) 188488.000 (-39.56)
+ parsec3/fluidanimate 531868.000 531885.600 (0.00) 531828.800 (-0.01) 532988.000 (0.21) 532959.600 (0.21) 415153.200 (-21.94)
+ parsec3/freqmine 552491.000 552718.600 (0.04) 552807.200 (0.06) 556574.200 (0.74) 554374.600 (0.34) 36573.400 (-93.38)
+ parsec3/raytrace 879683.400 880752.200 (0.12) 879907.000 (0.03) 870631.000 (-1.03) 880952.200 (0.14) 293119.200 (-66.68)
+ parsec3/streamcluster 110991.800 110937.200 (-0.05) 110964.600 (-0.02) 115606.800 (4.16) 116199.000 (4.69) 110108.200 (-0.80)
+ parsec3/swaptions 5665.000 5718.400 (0.94) 5720.600 (0.98) 5682.200 (0.30) 5628.600 (-0.64) 3613.800 (-36.21)
+ parsec3/vips 32143.600 31823.200 (-1.00) 31912.200 (-0.72) 33164.200 (3.18) 33925.800 (5.54) 27813.600 (-13.47)
+ parsec3/x264 81534.000 81811.000 (0.34) 81708.400 (0.21) 83052.400 (1.86) 83758.800 (2.73) 81691.800 (0.19)
+ splash2x/barnes 1220515.200 1218291.200 (-0.18) 1217699.600 (-0.23) 1228551.600 (0.66) 1220669.800 (0.01) 681096.000 (-44.20)
+ splash2x/fft 9915850.400 10036461.000 (1.22) 9881242.800 (-0.35) 10334603.600 (4.22) 10006993.200 (0.92) 8975181.200 (-9.49)
+ splash2x/lu_cb 511327.200 511679.000 (0.07) 511761.600 (0.08) 511971.600 (0.13) 511711.200 (0.08) 338005.000 (-33.90)
+ splash2x/lu_ncb 511505.000 506816.800 (-0.92) 511392.800 (-0.02) 496623.000 (-2.91) 511410.200 (-0.02) 404734.000 (-20.87)
+ splash2x/ocean_cp 3398834.000 3405017.800 (0.18) 3415287.800 (0.48) 3443604.600 (1.32) 3416264.200 (0.51) 3387134.000 (-0.34)
+ splash2x/ocean_ncp 3947092.800 3939805.400 (-0.18) 3952311.600 (0.13) 7165858.800 (81.55) 4610075.000 (16.80) 3944753.400 (-0.06)
+ splash2x/radiosity 1475024.000 1474053.200 (-0.07) 1475032.400 (0.00) 1483718.800 (0.59) 1475919.600 (0.06) 99637.200 (-93.25)
+ splash2x/radix 2431302.200 2416928.600 (-0.59) 2455596.800 (1.00) 2568526.400 (5.64) 2479966.800 (2.00) 2437406.600 (0.25)
+ splash2x/raytrace 23274.400 23278.400 (0.02) 23287.200 (0.05) 28828.000 (23.86) 27800.200 (19.45) 5667.000 (-75.65)
+ splash2x/volrend 44106.800 44151.400 (0.10) 44186.000 (0.18) 45200.400 (2.48) 44751.200 (1.46) 16912.000 (-61.66)
+ splash2x/water_nsquared 29427.200 29425.600 (-0.01) 29402.400 (-0.08) 28055.400 (-4.66) 28572.400 (-2.90) 13207.800 (-55.12)
+ splash2x/water_spatial 664312.200 664095.600 (-0.03) 663025.200 (-0.19) 664100.600 (-0.03) 663597.400 (-0.11) 261214.200 (-60.68)
+ total 29321300.000 29401500.000 (0.27) 29338300.000 (0.06) 33179900.000 (13.16) 30175600.000 (2.91) 23393600.000 (-20.22)
+
+In total, 20.22% of residential sets were reduced.
+
+With parsec3/freqmine, 'prcl' reduced 93.38% of residential sets and 23.63% of
+system memory usage while incurring only 1.22% runtime overhead.
diff --git a/Documentation/vm/damon/faq.rst b/Documentation/vm/damon/faq.rst
new file mode 100644
index 000000000000..088128bbf22b
--- /dev/null
+++ b/Documentation/vm/damon/faq.rst
@@ -0,0 +1,58 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+==========================
+Frequently Asked Questions
+==========================
+
+Why a new subsystem, instead of extending perf or other user space tools?
+=========================================================================
+
+First, because it needs to be lightweight as much as possible so that it can be
+used online, any unnecessary overhead such as kernel - user space context
+switching cost should be avoided. Second, DAMON aims to be used by other
+programs including the kernel. Therefore, having a dependency on specific
+tools like perf is not desirable. These are the two biggest reasons why DAMON
+is implemented in the kernel space.
+
+
+Can 'idle pages tracking' or 'perf mem' substitute DAMON?
+=========================================================
+
+Idle page tracking is a low level primitive for access check of the physical
+address space. 'perf mem' is similar, though it can use sampling to minimize
+the overhead. On the other hand, DAMON is a higher-level framework for the
+monitoring of various address spaces. It is focused on memory management
+optimization and provides sophisticated accuracy/overhead handling mechanisms.
+Therefore, 'idle pages tracking' and 'perf mem' could provide a subset of
+DAMON's output, but cannot substitute DAMON.
+
+
+How can I optimize my system's memory management using DAMON?
+=============================================================
+
+Because there are several ways for the DAMON-based optimizations, we wrote a
+separate document, :doc:`/admin-guide/mm/damon/guide`. Please refer to that.
+
+
+Does DAMON support virtual memory only?
+=======================================
+
+No. The core of the DAMON is address space independent. The address space
+specific low level primitive parts including monitoring target regions
+constructions and actual access checks can be implemented and configured on the
+DAMON core by the users. In this way, DAMON users can monitor any address
+space with any access check technique.
+
+Nonetheless, DAMON provides vma tracking and PTE Accessed bit check based
+implementations of the address space dependent functions for the virtual memory
+by default, for a reference and convenient use. In near future, we will
+provide those for physical memory address space.
+
+
+Can I simply monitor page granularity?
+======================================
+
+Yes. You can do so by setting the ``min_nr_regions`` attribute higher than the
+working set size divided by the page size. Because the monitoring target
+regions size is forced to be ``>=page size``, the region split will make no
+effect.
diff --git a/Documentation/vm/damon/index.rst b/Documentation/vm/damon/index.rst
new file mode 100644
index 000000000000..17dca3c12aad
--- /dev/null
+++ b/Documentation/vm/damon/index.rst
@@ -0,0 +1,31 @@
+.. SPDX-License-Identifier: GPL-2.0
+
+==========================
+DAMON: Data Access MONitor
+==========================
+
+DAMON is a data access monitoring framework subsystem for the Linux kernel.
+The core mechanisms of DAMON (refer to :doc:`design` for the detail) make it
+
+ - *accurate* (the monitoring output is useful enough for DRAM level memory
+ management; It might not appropriate for CPU Cache levels, though),
+ - *light-weight* (the monitoring overhead is low enough to be applied online),
+ and
+ - *scalable* (the upper-bound of the overhead is in constant range regardless
+ of the size of target workloads).
+
+Using this framework, therefore, the kernel's memory management mechanisms can
+make advanced decisions. Experimental memory management optimization works
+that incurring high data accesses monitoring overhead could implemented again.
+In user space, meanwhile, users who have some special workloads can write
+personalized applications for better understanding and optimizations of their
+workloads and systems.
+
+.. toctree::
+ :maxdepth: 2
+
+ faq
+ design
+ eval
+ api
+ plans
diff --git a/Documentation/vm/index.rst b/Documentation/vm/index.rst
index eff5fbd492d0..b51f0d8992f8 100644
--- a/Documentation/vm/index.rst
+++ b/Documentation/vm/index.rst
@@ -32,6 +32,7 @@ descriptions of data structures and algorithms.
arch_pgtable_helpers
balance
cleancache
+ damon/index
free_page_reporting
frontswap
highmem
--
2.17.1