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 | 159 ++++++++++ Documentation/admin-guide/mm/damon/index.rst | 15 + Documentation/admin-guide/mm/damon/plans.rst | 29 ++ Documentation/admin-guide/mm/damon/start.rst | 97 ++++++ Documentation/admin-guide/mm/damon/usage.rst | 304 +++++++++++++++++++ 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, 1113 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..49da40bc4ba9 --- /dev/null +++ b/Documentation/admin-guide/mm/damon/guide.rst @@ -0,0 +1,159 @@ +.. 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 +``tools/damon/`` directory in the DAMON development tree (``damon/master`` +branch of https://github.com/sjp38/linux.git). + +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..69bac6782624 --- /dev/null +++ b/Documentation/admin-guide/mm/damon/start.rst @@ -0,0 +1,97 @@ +.. 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 5 commands to monitor and visualize the access pattern of your +workload. :: + + $ git clone https://github.com/sjp38/linux -b damon/master + /* build the kernel with CONFIG_DAMON=y, install, reboot */ + $ mount -t debugfs none /sys/kernel/debug/ + $ cd linux/tools/damon + $ ./damo record $(pidof <your workload>) + $ ./damo report heats --heatmap access_pattern.png + + +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 located at ``tools/damon/damo`` of the +DAMON development kernel source tree (``damon/master`` branch of +https://github.com/sjp38/linux). 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..32436cf853c7 --- /dev/null +++ b/Documentation/admin-guide/mm/damon/usage.rst @@ -0,0 +1,304 @@ +.. 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. + +This document does not describe the kernel space programming interface in +detail. For that, please refer to the :doc:`/vm/damon/api`. + + +DAMON User Space Tool +===================== + +There is a reference implementation of the DAMON user space tools, namely +``damo``, which provides a convenient user interface. You can get it from +``tools/damon/`` directory in the DAMON development kernel source tree +(``damon/next`` branch of https://github.com/sjp38/linux.git). + +The tool provides a subcommands based interface. Every subcommand provides +``-h`` option, which provides the minimal usage of it. Currently, the tool +supports two subcommands, ``record`` and ``report``. + +Below example commands assume you set ``$PATH`` to point ``tools/damon/`` of +the development tree for brevity. It is not mandatory for use of ``damo``, +though. + + +Recording Data Access Pattern +----------------------------- + +The ``record`` subcommand records the data access pattern of target workloads +in a file (``./damon.data`` by default). You can specify the target with 1) +the command for execution of the monitoring target process, or 2) pid of +running target process. Below example shows a command target usage:: + + # cd <kernel>/tools/damon/ + # damo record "sleep 5" + +The tool will execute ``sleep 5`` by itself and record the data access patterns +of the process. Below example shows a pid target usage:: + + # sleep 5 & + # damo record `pidof sleep` + +The location of the recorded file can be explicitly set using ``-o`` option. +You can further tune this by setting the monitoring attributes. To know about +the monitoring attributes in detail, please refer to the +:doc:`/vm/damon/design`. + + +Analyzing Data Access Pattern +----------------------------- + +The ``report`` subcommand reads a data access pattern record file (if not +explicitly specified using ``-i`` option, reads ``./damon.data`` file by +default) and generates human-readable reports. You can specify what type of +report you want using a sub-subcommand to ``report`` subcommand. ``raw``, +``heats``, and ``wss`` report types are supported for now. + + +raw +~~~ + +``raw`` sub-subcommand simply transforms the binary record into a +human-readable text. For example:: + + $ damo report raw + start_time: 193485829398 + rel time: 0 + nr_tasks: 1 + target_id: 1348 + nr_regions: 4 + 560189609000-56018abce000( 22827008): 0 + 7fbdff59a000-7fbdffaf1a00( 5601792): 0 + 7fbdffaf1a00-7fbdffbb5000( 800256): 1 + 7ffea0dc0000-7ffea0dfd000( 249856): 0 + + rel time: 100000731 + nr_tasks: 1 + target_id: 1348 + nr_regions: 6 + 560189609000-56018abce000( 22827008): 0 + 7fbdff59a000-7fbdff8ce933( 3361075): 0 + 7fbdff8ce933-7fbdffaf1a00( 2240717): 1 + 7fbdffaf1a00-7fbdffb66d99( 480153): 0 + 7fbdffb66d99-7fbdffbb5000( 320103): 1 + 7ffea0dc0000-7ffea0dfd000( 249856): 0 + +The first line shows the recording started timestamp (nanosecond). Records of +data access patterns follows. Each record is separated by a blank line. Each +record first specifies the recorded time (``rel time``) in relative to the +start time, the number of monitored tasks in this record (``nr_tasks``). +Recorded data access patterns of each task follow. Each data access pattern +for each task shows the target's pid (``target_id``) and a number of monitored +address regions in this access pattern (``nr_regions``) first. After that, +each line shows the start/end address, size, and the number of observed +accesses of each region. + + +heats +~~~~~ + +The ``raw`` output is very detailed but hard to manually read. ``heats`` +sub-subcommand plots the data in 3-dimensional form, which represents the time +in x-axis, address of regions in y-axis, and the access frequency in z-axis. +Users can set the resolution of the map (``--tres`` and ``--ares``) and +start/end point of each axis (``--tmin``, ``--tmax``, ``--amin``, and +``--amax``) via optional arguments. For example:: + + $ damo report heats --tres 3 --ares 3 + 0 0 0.0 + 0 7609002 0.0 + 0 15218004 0.0 + 66112620851 0 0.0 + 66112620851 7609002 0.0 + 66112620851 15218004 0.0 + 132225241702 0 0.0 + 132225241702 7609002 0.0 + 132225241702 15218004 0.0 + +This command shows a recorded access pattern in heatmap of 3x3 resolution. +Therefore it shows 9 data points in total. Each line shows each of the data +points. The three numbers in each line represent time in nanosecond, address, +and the observed access frequency. + +Users will be able to convert this text output into a heatmap image (represents +z-axis values with colors) or other 3D representations using various tools such +as 'gnuplot'. For more convenience, ``heats`` sub-subcommand provides the +'gnuplot' based heatmap image creation. For this, you can use ``--heatmap`` +option. Also, note that because it uses 'gnuplot' internally, it will fail if +'gnuplot' is not installed on your system. For example:: + + $ ./damo report heats --heatmap heatmap.png + +Creates the heatmap image in ``heatmap.png`` file. It supports ``pdf``, +``png``, ``jpeg``, and ``svg``. + +If the target address space is virtual memory address space and you plot the +entire address space, the huge unmapped regions will make the picture looks +only black. Therefore you should do proper zoom in / zoom out using the +resolution and axis boundary-setting arguments. To make this effort minimal, +you can use ``--guide`` option as below:: + + $ ./damo report heats --guide + target_id:1348 + time: 193485829398-198337863555 (4852034157) + region 0: 00000094564599762944-00000094564622589952 (22827008) + region 1: 00000140454009610240-00000140454016012288 (6402048) + region 2: 00000140731597193216-00000140731597443072 (249856) + +The output shows unions of monitored regions (start and end addresses in byte) +and the union of monitored time duration (start and end time in nanoseconds) of +each target task. Therefore, it would be wise to plot the data points in each +union. If no axis boundary option is given, it will automatically find the +biggest union in ``--guide`` output and set the boundary in it. + + +wss +~~~ + +The ``wss`` type extracts the distribution and chronological working set size +changes from the records. For example:: + + $ ./damo report wss + # <percentile> <wss> + # target_id 1348 + # avr: 66228 + 0 0 + 25 0 + 50 0 + 75 0 + 100 1920615 + +Without any option, it shows the distribution of the working set sizes as +above. It shows 0th, 25th, 50th, 75th, and 100th percentile and the average of +the measured working set sizes in the access pattern records. In this case, +the working set size was zero for 75th percentile but 1,920,615 bytes in max +and 66,228 bytes on average. + +By setting the sort key of the percentile using '--sortby', you can show how +the working set size has chronologically changed. For example:: + + $ ./damo report wss --sortby time + # <percentile> <wss> + # target_id 1348 + # avr: 66228 + 0 0 + 25 0 + 50 0 + 75 0 + 100 0 + +The average is still 66,228. And, because the access was spiked in very short +duration and this command plots only 4 data points, we cannot show when the +access spikes made. Users can specify the resolution of the distribution +(``--range``). By giving more fine resolution, the short duration spikes could +be found. + +Similar to that of ``heats --heatmap``, it also supports 'gnuplot' based simple +visualization of the distribution via ``--plot`` option. + + +debugfs Interface +================= + +DAMON exports four files, ``attrs``, ``target_ids``, ``record``, 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. + + +Record +------ + +This debugfs file allows you to record monitored access patterns in a regular +binary file. The recorded results are first written in an in-memory buffer and +flushed to a file in batch. Users can get and set the size of the buffer and +the path to the result file by reading from and writing to the ``record`` file. +For example, below commands set the buffer to be 4 KiB and the result to be +saved in ``/damon.data``. :: + + # cd <debugfs>/damon + # echo "4096 /damon.data" > record + # cat record + 4096 /damon.data + +The recording can be disabled by setting the buffer size zero. + + +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. diff --git a/Documentation/admin-guide/mm/index.rst b/Documentation/admin-guide/mm/index.rst index cd727cfc1b04..32c27fbf1913 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
