kernel/include/linux/damon.h, branch linux-6.17.y

mm/damon/core: introduce damon_call_control->dealloc_on_cancel

2025-09-13T20:05:36Z

Patch series "mm/damon/sysfs: fix refresh_ms control overwriting on multi-kdamonds usages". Automatic esssential DAMON/DAMOS status update feature of DAMON sysfs interface (refresh_ms) is broken [1] for multiple DAMON contexts (kdamonds) use case, since it uses a global single damon_call_control object for all created DAMON contexts. The fields of the object, particularly the list field is over-written for the contexts and it makes unexpected results including user-space hangup and kernel crashes [2]. Fix it by extending damon_call_control for the use case and updating the usage on DAMON sysfs interface to use per-context dynamically allocated damon_call_control object. This patch (of 2): When damon_call_control->repeat is set, damon_call() is executed asynchronously, and is eventually canceled when kdamond finishes. If the damon_call_control object is dynamically allocated, finding the place to deallocate the object is difficult. Introduce a new damon_call_control field, namely dealloc_on_cancel, to ask the kdamond deallocates those dynamically allocated objects when those are canceled. Link: https://lkml.kernel.org/r/20250908201513.60802-3-sj@kernel.org Link: https://lkml.kernel.org/r/20250908201513.60802-2-sj@kernel.org Fixes: d809a7c64ba8 ("mm/damon/sysfs: implement refresh_ms file internal work") Signed-off-by: SeongJae Park Cc: Yunjeong Mun Signed-off-by: Andrew Morton

mm/damon/core: remove damon_callback

2025-07-20T01:59:57Z

All damon_callback usages are replicated by damon_call() and damos_walk(). Time to say goodbye. Remove damon_callback. Link: https://lkml.kernel.org/r/20250712195016.151108-15-sj@kernel.org Signed-off-by: SeongJae Park Signed-off-by: Andrew Morton

mm/damon/core: add cleanup_target() ops callback

2025-07-20T01:59:56Z

Some DAMON operation sets may need additional cleanup per target. For example, [f]vaddr need to put pids of each target. Each user and core logic is doing that redundantly. Add another DAMON ops callback that will be used for doing such cleanups in operations set layer. [sj@kernel.org: add kernel-doc comment for damon_operations->cleanup_target] Link: https://lkml.kernel.org/r/20250715185239.89152-2-sj@kernel.org [sj@kernel.org: remove damon_ctx->callback kernel-doc comment] Link: https://lkml.kernel.org/r/20250715185239.89152-3-sj@kernel.org Link: https://lkml.kernel.org/r/20250712195016.151108-10-sj@kernel.org Signed-off-by: SeongJae Park Signed-off-by: Andrew Morton

mm/damon/core: introduce repeat mode damon_call()

2025-07-20T01:59:54Z

damon_call() can be useful for reading or writing DAMON internal data for one time. A common pattern of DAMON core usage from DAMON modules is doing such reads and writes repeatedly, for example, to periodically update the DAMOS stats. To do that with damon_call(), callers should call damon_call() repeatedly, with their own delay loop. Each caller doing that is repetitive. Introduce a repeat mode damon_call(). Callers can use the mode by setting a new field in damon_call_control. If the mode is turned on, damon_call() returns success immediately, and DAMON repeats invoking the callback function inside the kdamond main loop. Link: https://lkml.kernel.org/r/20250712195016.151108-3-sj@kernel.org Signed-off-by: SeongJae Park Signed-off-by: Andrew Morton

mm/damon: accept parallel damon_call() requests

2025-07-20T01:59:54Z

Patch series "mm/damon: remove damon_callback". damon_callback was the only way for communicating with DAMON for contexts running on its worker thread. The interface is flexible and simple. But as DAMON evolves with more features, damon_callback has become somewhat too old. With runtime parameters update, for example, its lack of synchronization support was found to be inconvenient. Arguably it is also not easy to use correctly since the callers should understand when each callback is called, and implication of the return values from the callbacks. To replace it, damon_call() and damos_walk() are introduced. And those replaced a few damon_callback use cases. Some use cases of damon_callback such as parallel or repetitive DAMON internal data reading and additional cleanups cannot simply be replaced by damon_call() and damos_walk(), though. To allow those replaceable, extend damon_call() for parallel and/or repeated callbacks and modify the core/ops layers for additional resources cleanup. With the updates, replace the remaining damon_callback usages and finally say goodbye to damon_callback. This patch (of 14): Calling damon_call() while it is serving for another parallel thread immediately fails with -EBUSY. The caller should call it again, later. Each caller implementing such retry logic would be redundant. Accept parallel damon_call() requests and do the wait instead of the caller. Link: https://lkml.kernel.org/r/20250712195016.151108-1-sj@kernel.org Link: https://lkml.kernel.org/r/20250712195016.151108-2-sj@kernel.org Signed-off-by: SeongJae Park Signed-off-by: Andrew Morton

mm/damon/core: add damos->migrate_dests field

2025-07-20T01:59:48Z

Add a new field to 'struct damos', namely migrate_dests, to allow DAMON API callers specify multiple migration destination nodes and their weights. Also update 'struct damos' creation and destruction functions accordingly to initialize the new field and free up the API caller-allocated buffers on those, respectively. Link: https://lkml.kernel.org/r/20250709005952.17776-3-bijan311@gmail.com Signed-off-by: SeongJae Park Signed-off-by: Bijan Tabatabai Reviewed-by: SeongJae Park Cc: Jonathan Corbet Cc: Ravi Shankar Jonnalagadda Signed-off-by: Andrew Morton

mm/damon: add struct damos_migrate_dests

2025-07-20T01:59:48Z

Patch series "mm/damon/vaddr: Allow interleaving in migrate_{hot,cold} actions", v4. A recent patchset automatically sets the interleave weight for each node according to the node's maximum bandwidth [1]. In another thread, the patch set's author, Joshua Hahn, wondered if/how thes weights should be changed if the bandwidth utilization of the system changes [2]. This patch set adds the mechanism for dynamically changing how application data is interleaved across nodes while leaving the policy of what the interleave weights should be to userspace. It does this by having the migrate_{hot,cold} operating schemes interleave application data according to the list of migration nodes and weights passed in via the DAMON sysfs interface. This functionality can be used to dynamically adjust how folios are interleaved by having a userspace process adjust those weights. If no specific destination nodes or weights are provided, the migrate_{hot,cold} actions will only migrate folios to damos->target_nid as before. The algorithm used to interleave the folios is similar to the one used for the weighted interleave mempolicy [3]. It uses the offset from which a folio is mapped into a VMA to determine the node the folio should be placed in. This method is convenient because for a given set of interleave weights, a folio has only one valid node it can be placed in, limitng the amount of unnecessary data movement. However, finding out how a folio is mapped inside of a VMA requires a costly rmap walk when using a paddr scheme. As such, we have decided that this functionality makes more sense as a vaddr scheme [4]. To this end, this patch set also adds vaddr versions of the migrate_{hot,cold}. Motivation ========== There have been prior discussions about how changing the interleave weights in response to the system's bandwidth utilization can be beneficial [2]. However, currently the interleave weights only are applied when data is allocated. Migrating already allocated pages according to the dynamically changing weights will better help balance the bandwidth utilization across nodes. As a toy example, imagine some application that uses 75% of the local bandwidth. Assuming sufficient capacity, when running alone, we want to keep that application's data in local memory. However, if a second instance of that application begins, using the same amount of bandwidth, it would be best to interleave the data of both processes to alleviate the bandwidth pressure from the local node. Likewise, when one of the processes ends, the data should be moves back to local memory. We imagine there would be a userspace application that would monitor system performance characteristics, such as bandwidth utilization or memory access latency, and uses that information to tune the interleave weights. Others seem to have come to a similar conclusion in previous discussions [5]. We are currently working on a userspace program that does this, but it is not quite ready to be published yet. After the userspace application tunes the interleave weights, there must be some mechanism that actually migrates pages to be consistent with those weights. This patchset is what provides this mechanism. We believe DAMON is the correct venue for the interleaving mechanism for a few reasons. First, we noticed that we don't have to migrate all of the application's pages to improve performance. we just need to migrate the frequently accessed pages. DAMON's existing hotness traching is very useful for this. Second, DAMON's quota system can be used to ensure we are not using too much bandwidth for migrations. Finally, as Ying pointed out [6], a complete solution must also handle when a memory node is at capacity. The existing migrate_cold action can be used in conjunction with the functionality added in this patch set to provide that complete solution. Functionality Test ================== Below is an example of this new functionality in use to confirm that these patches behave as intended. In this example, the user starts an application, alloc_data, which allocates 1GB using the default memory policy (i.e. allocate to local memory) then sleeps. Afterwards, we start DAMON to interleave the data at a 1:1 ratio. Using numastat, we show that DAMON has migrated the application's data to match the new interleave ratio. For this example, I modified the userspace damo tool [8] to write to the migration_dest sysfs files. I plan to upstream these changes when these patches are merged. $ # Allocate the data initially $ ./alloc_data 1G & [1] 6587 $ numastat -c -p alloc_data Per-node process memory usage (in MBs) for PID 6587 (alloc_data) Node 0 Node 1 Total ------ ------ ----- Huge 0 0 0 Heap 0 0 0 Stack 0 0 0 Private 1027 0 1027 ------- ------ ------ ----- Total 1027 0 1027 $ # Start DAMON to interleave data at a 1:1 ratio $ cat ./interleave_vaddr.yaml kdamonds: - contexts: - ops: vaddr addr_unit: null targets: - pid: 6587 regions: [] intervals: sample_us: 500 ms aggr_us: 5 s ops_update_us: 20 s intervals_goal: access_bp: 0 % aggrs: '0' min_sample_us: 0 ns max_sample_us: 0 ns nr_regions: min: '20' max: '50' schemes: - action: migrate_hot dests: - nid: 0 weight: 1 - nid: 1 weight: 1 access_pattern: sz_bytes: min: 0 B max: max nr_accesses: min: 0 % max: 100 % age: min: 0 ns max: max $ sudo ./damo/damo interleave_vaddr.yaml $ # Verify that DAMON has migrated data to match the 1:1 ratio $ numastat -c -p alloc_data Per-node process memory usage (in MBs) for PID 6587 (alloc_data) Node 0 Node 1 Total ------ ------ ----- Huge 0 0 0 Heap 0 0 0 Stack 0 0 0 Private 514 514 1027 ------- ------ ------ ----- Total 514 514 1027 Performance Test ================ Below is a simple example showing that interleaving application data using these patches can improve application performance. To do this, we run a bandwidth intensive embedding reduction application [7]. This workload is useful for this test because it reports the time it takes each iteration to run and each iteration reuses the same allocation, allowing us to see the benefits of the migration. We evaluate this on a 128 core/256 thread AMD CPU with 72GB/s of local DDR bandwidth and 26 GB/s of CXL bandwidth. Before we start the workload, the system bandwidth utilization is low, so we start with the interleave weights of 1:0, i.e. allocating all data to local memory. When the workload beings, it saturates the local bandwidth, making the page placement suboptimal. To alleviate this, we modify the interleave weights, triggering DAMON to migrate the workload's data. We use the same interleave_vaddr.yaml file to setup DAMON, except we configure it to begin with a 1:0 interleave ratio, and attach it to the shell and its children processes. $ sudo ./damo/damo start interleave_vaddr.yaml --include_child_tasks & $ /eval_baseline -d amazon_All -c 255 -r 100 Eval Phase 3: Running Baseline... REPEAT # 0 Baseline Total time : 7323.54 ms REPEAT # 1 Baseline Total time : 7624.56 ms REPEAT # 2 Baseline Total time : 7619.61 ms REPEAT # 3 Baseline Total time : 7617.12 ms REPEAT # 4 Baseline Total time : 7638.64 ms REPEAT # 5 Baseline Total time : 7611.27 ms REPEAT # 6 Baseline Total time : 7629.32 ms REPEAT # 7 Baseline Total time : 7695.63 ms # Interleave weights set to 3:1 REPEAT # 8 Baseline Total time : 7077.5 ms REPEAT # 9 Baseline Total time : 5633.23 ms REPEAT # 10 Baseline Total time : 5644.6 ms REPEAT # 11 Baseline Total time : 5627.66 ms REPEAT # 12 Baseline Total time : 5629.76 ms REPEAT # 13 Baseline Total time : 5633.05 ms REPEAT # 14 Baseline Total time : 5641.24 ms REPEAT # 15 Baseline Total time : 5631.18 ms REPEAT # 16 Baseline Total time : 5631.33 ms Updating the interleave weights and having DAMON migrate the workload data according to the weights resulted in an approximarely 25% speedup. Patches Sequence ================ Patches 1-7 extend the DAMON API to specify multiple destination nodes and weights for the migrate_{hot,cold} actions. These patches are from SJ'S RFC [8]. Patches 8-10 add a vaddr implementation of the migrate_{hot,cold} schemes. Patch 11 modifies the vaddr migrate_{hot,cold} schemes to interleave data according to the weights provided by damos->migrate_dest. Patches 12-13 allow the vaddr migrate_{hot,cold} implementation to filter out folios like the paddr version. This patch (of 13): Introduce a new struct, namely damos_migrate_dests, for specifying multiple DAMOS' migration destination nodes and their weights. Link: https://lkml.kernel.org/r/20250709005952.17776-1-bijan311@gmail.com Link: https://lkml.kernel.org/r/20250709005952.17776-2-bijan311@gmail.com Link: https://lore.kernel.org/linux-mm/20250520141236.2987309-1-joshua.hahnjy@gmail.com/ [1] Link: https://lore.kernel.org/linux-mm/20250313155705.1943522-1-joshua.hahnjy@gmail.com/ [2] Link: https://elixir.bootlin.com/linux/v6.15.4/source/mm/mempolicy.c#L2015 [3] Link: https://lore.kernel.org/damon/20250624223310.55786-1-sj@kernel.org/ [4] Link: https://lore.kernel.org/linux-mm/20250314151137.892379-1-joshua.hahnjy@gmail.com/ [5] Link: https://lore.kernel.org/linux-mm/87frjfx6u4.fsf@DESKTOP-5N7EMDA/ [6] Link: https://github.com/SNU-ARC/MERCI [7] Link: https://lore.kernel.org/damon/20250702051558.54138-1-sj@kernel.org/ [8] Signed-off-by: SeongJae Park Signed-off-by: Bijan Tabatabai Reviewed-by: SeongJae Park Cc: Jonathan Corbet Cc: Ravi Shankar Jonnalagadda Signed-off-by: Andrew Morton

mm/damon/sysfs: use DAMON core API damon_is_running()

2025-07-20T01:59:44Z

DAMON core implements a static function to see if a given DAMON context is running. DAMON sysfs interface is implementing the same one on its own. Make the core function non-static and reuse it from the DAMON sysfs interface. Link: https://lkml.kernel.org/r/20250705175000.56259-5-sj@kernel.org Signed-off-by: SeongJae Park Signed-off-by: Andrew Morton

mm/damon: fix minor typos in damon header

2025-07-10T05:42:14Z

Fix typos in include/linux/damon.h. Link: https://lkml.kernel.org/r/20250618163331.54910-1-sj@kernel.org Signed-off-by: Nathan Gao Reviewed-by: SeongJae Park Signed-off-by: Andrew Morton

mm/damon/core: introduce damos quota goal metrics for memory node utilization

2025-05-13T06:50:29Z

Patch series "mm/damon: auto-tune DAMOS for NUMA setups including tiered memory". Utilizing DAMON for memory tiering usually requires manual tuning and/or tedious controls. Let it self-tune hotness and coldness thresholds for promotion and demotion aiming high utilization of high memory tiers, by introducing new DAMOS quota goal metrics representing the used and the free memory ratios of specific NUMA nodes. And introduce a sample DAMON module that demonstrates how the new feature can be used for memory tiering use cases. Backgrounds =========== A type of tiered memory system exposes the memory tiers as NUMA nodes. A straightforward pages placement strategy for such systems is placing access-hot and cold pages on upper and lower tiers, reespectively, pursuing higher utilization of upper tiers. Since access temperature can be dynamic, periodically finding and migrating hot pages and cold pages to proper tiers (promoting and demoting) is also required. Linux kernel provides several features for such dynamic and transparent pages placement. Page Faults and LRU ------------------- One widely known way is using NUMA balancing in tiering mode (a.k.a NUMAB-2) and reclaim-based demotion features. In the setup, NUMAB-2 finds hot pages using access check-purpose page faults (a.k.a prot_none) and promote those inside each process' context, until there is no more pages to promote, or the upper tier is filled up and memory pressure happens. In the latter case, LRU-based reclaim logic wakes up as a response to the memory pressure and demotes cold pages to lower tiers in asynchronous (kswapd) and/or synchronous ways (direct reclaim). DAMON ----- Yet another available solution is using DAMOS with migrate_hot and migrate_cold DAMOS actions for promotions and demotions, respectively. To make it optimum, users need to specify aggressiveness and access temperature thresholds for promotions and demotions in a good balance that results in high utilization of upper tiers. The number of parameters is not small, and optimum parameter values depend on characteristics of the underlying hardware and the workload. As a result, it often requires manual, time consuming and repetitive tuning of the DAMOS schemes for given workloads and systems combinations. Self-tuned DAMON-based Memory Tiering ===================================== To solve such manual tuning problems, DAMOS provides aim-oriented feedback-driven quotas self-tuning. Using the feature, we design a self-tuned DAMON-based memory tiering for general multi-tier memory systems. For each memory tier node, if it has a lower tier, run a DAMOS scheme that demotes cold pages of the node, auto-tuning the aggressiveness aiming an amount of free space of the node. The free space is for keeping the headroom that avoids significant memory pressure during upper tier memory usage spike, and promoting hot pages from the lower tier. For each memory tier node, if it has an upper tier, run a DAMOS scheme that promotes hot pages of the current node to the upper tier, auto-tuning the aggressiveness aiming a high utilization ratio of the upper tier. The target ratio is to ensure higher tiers are utilized as much as possible. It should match with the headroom for demotion scheme, but have slight overlap, to ensure promotion and demotion are not entirely stopped. The aim-oriented aggressiveness auto-tuning of DAMOS is already available. Hence, to make such tiering solution implementation, only new quota goal metrics for utilization and free space ratio of specific NUMA node need to be developed. Discussions =========== The design imposes below discussion points. Expected Behaviors ------------------ The system will let upper tier memory node accommodates as many hot data as possible. If total amount of the data is less than the top tier memory's promotion/demotion target utilization, entire data will be just placed on the top tier. Promotion scheme will do nothing since there is no data to promote. Demotion scheme will also do nothing since the free space ratio of the top tier is higher than the goal. Only if the amount of data is larger than the top tier's utilization ratio, demotion scheme will demote cold pages and ensure the headroom free space. Since the promotion and demotion schemes for a single node has small overlap at their target utilization and free space goals, promotions and demotions will continue working with a moderate aggressiveness level. It will keep all data is placed on access hotness under dynamic access pattern, while minimizing the migration overhead. In any case, each node will keep headroom free space and as many upper tiers are utilized as possible. Ease of Use ----------- Users still need to set the target utilization and free space ratio, but it will be easier to set. We argue 99.7 % utilization and 0.5 % free space ratios can be good default values. It can be easily adjusted based on desired headroom size of given use case. Users are also still required to answer the minimum coldness and hotness thresholds. Together with monitoring intervals auto-tuning[2], DAMON will always show meaningful amount of hot and cold memory. And DAMOS quota's prioritization mechanism will make good decision as long as the source information is that colorful. Hence, users can very naively set the minimum criterias. We believe any access observation and no access observation within last one aggregation interval is enough for minimum hot and cold regions criterias. General Tiered Memory Setup Applicability ----------------------------------------- The design can be applied to any number of tiers having any performance characteristics, as long as they can be hierarchical. Hence, applying the system to different tiered memory system will be straightforward. Note that this assumes only single CPU NUMA node case. Because today's DAMON is not aware of which CPU made each access, applying this on systems having multiple CPU NUMA nodes can be complicated. We are planning to extend DAMON for the use case, but that's out of the scope of this patch series. How To Use ---------- Users can implement the auto-tuned DAMON-based memory tiering using DAMON sysfs interface. It can be easily done using DAMON user-space tool like user-space tool. Below evaluation results section shows an example DAMON user-space tool command for that. For wider and simpler deployment, having a kernel module that sets up and run the DAMOS schemes via DAMON kernel API can be useful. The module can enable the memory tiering at boot time via kernel command line parameter or at run time with single command. This patch series implements a sample DAMON kernel module that shows how such module can be implemented. Comparison To Page Faults and LRU-based Approaches -------------------------------------------------- The existing page faults based promotion (NUMAB-2) does hot pages detection and migration in the process context. When there are many pages to promote, it can block the progress of the application's real works. DAMOS works in asynchronous worker thread, so it doesn't block the real works. NUMAB-2 doesn't provide a way to control aggressiveness of promotion other than the maximum amount of pages to promote per given time widnow. If hot pages are found, promotions can happen in the upper-bound speed, regardless of upper tier's memory pressure. If the maximum speed is not well set for the given workload, it can result in slow promotion or unnecessary memory pressure. Self-tuned DAMON-based memory tiering alleviates the problem by adjusting the speed based on current utilization of the upper tier. LRU-based demotion can be triggered in both asynchronous (kswapd) and synchronous (direct reclaim) ways. Other than the way of finding cold pages, asynchronous LRU-based demotion and DAMON-based demotion has no big difference. DAMON-based demotion can make a better balancing with DAMON-based promotion, though. The LRU-based demotion can do better than DAMON-based demotion when the tier is having significant memory pressure. It would be wise to use DAMON-based demotion as a proactive and primary one, but utilizing LRU-based demotions together as a fast backup solution. Evaluation ========== In short, under a setup that requires fast and frequent promotions, self-tuned DAMON-based memory tiering's hot pages promotion improves performance about 4.42 %. We believe this shows self-tuned DAMON-based promotion's effectiveness. Meanwhile, NUMAB-2's hot pages promotion degrades the performance about 7.34 %. We suspect the degradation is mostly due to NUMAB-2's synchronous nature that can block the application's progress, which highlights the advantage of DAMON-based solution's asynchronous nature. Note that the test was done with the RFC version of this patch series. We don't run it again since this patch series got no meaningful change after the RFC, while the test takes pretty long time. Setup ----- Hardware. Use a machine that equips 250 GiB DRAM memory tier and 50 GiB CXL memory tier. The tiers are exposed as NUMA nodes 0 and 1, respectively. Kernel. Use Linux kernel v6.13 that modified as following. Add all DAMON patches that available on mm tree of 2025-03-15, and this patch series. Also modify it to ignore mempolicy() system calls, to avoid bad effects from application's traditional NUMA systems assumed optimizations. Workload. Use a modified version of Taobench benchmark[3] that available on DCPerf benchmark suite. It represents an in-memory caching workload. We set its 'memsize', 'warmup_time', and 'test_time' parameter as 340 GiB, 2,500 seconds and 1,440 seconds. The parameters are chosen to ensure the workload uses more than DRAM memory tier. Its RSS under the parameter grows to 270 GiB within the warmup time. It turned out the workload has a very static access pattrn. Only about 13 % of the RSS is frequently accessed from the beginning to end. Hence promotion shows no meaningful performance difference regardless of different design and implementations. We therefore modify the kernel to periodically demote up to 10 GiB hot pages and promote up to 10 GiB cold pages once per minute. The intention is to simulate periodic access pattern changes. The hotness and coldness threshold is very naively set so that it is more like random access pattern change rather than strict hot/cold pages exchange. This is why we call the workload as "modified". It is implemented as two DAMOS schemes each running on an asynchronous thread. It can be reproduced with DAMON user-space tool like below. # ./damo start \ --ops paddr --numa_node 0 --monitoring_intervals 10s 200s 200s \ --damos_action migrate_hot 1 \ --damos_quota_interval 60s --damos_quota_space 10G \ --ops paddr --numa_node 1 --monitoring_intervals 10s 200s 200s \ --damos_action migrate_cold 0 \ --damos_quota_interval 60s --damos_quota_space 10G \ --nr_schemes 1 1 --nr_targets 1 1 --nr_ctxs 1 1 System configurations. Use below variant system configurations. - Baseline. No memory tiering features are turned on. - Numab_tiering. On the baseline, enable NUMAB-2 and relcaim-based demotion. In detail, following command is executed: echo 2 > /proc/sys/kernel/numa_balancing; echo 1 > /sys/kernel/mm/numa/demotion_enabled; echo 7 > /proc/sys/vm/zone_reclaim_mode - DAMON_tiering. On the baseline, utilize self-tuned DAMON-based memory tiering implementation via DAMON user-space tool. It utilizes two kernel threads, namely promotion thread and demotion thread. Demotion thread monitors access pattern of DRAM node using DAMON with auto-tuned monitoring intervals aiming 4% DAMON-observed access ratio, and demote coldest pages up to 200 MiB per second aiming 0.5% free space of DRAM node. Promotion thread monitors CXL node using same intervals auto-tuning, and promote hot pages in same way but aiming for 99.7% utilization of DRAM node. Because DAMON provides only best-effort accuracy, add young page DAMOS filters to allow only and reject all young pages at promoting and demoting, respectively. It can be reproduced with DAMON user-space tool like below. # ./damo start \ --numa_node 0 --monitoring_intervals_goal 4% 3 5ms 10s \ --damos_action migrate_cold 1 --damos_access_rate 0% 0% \ --damos_apply_interval 1s \ --damos_quota_interval 1s --damos_quota_space 200MB \ --damos_quota_goal node_mem_free_bp 0.5% 0 \ --damos_filter reject young \ --numa_node 1 --monitoring_intervals_goal 4% 3 5ms 10s \ --damos_action migrate_hot 0 --damos_access_rate 5% max \ --damos_apply_interval 1s \ --damos_quota_interval 1s --damos_quota_space 200MB \ --damos_quota_goal node_mem_used_bp 99.7% 0 \ --damos_filter allow young \ --damos_nr_quota_goals 1 1 --damos_nr_filters 1 1 \ --nr_targets 1 1 --nr_schemes 1 1 --nr_ctxs 1 1 Measurment Results ------------------ On each system configuration, run the modified version of Taobench and collect 'score'. 'score' is a metric that calculated and provided by Taobench to represents the performance of the run on the system. To handle the measurement errors, repeat the measurement five times. The results are as below. Config Score Stdev (%) Normalized Baseline 1.6165 0.0319 1.9764 1.0000 Numab_tiering 1.4976 0.0452 3.0209 0.9264 DAMON_tiering 1.6881 0.0249 1.4767 1.0443 'Config' column shows the system config of the measurement. 'Score' column shows the 'score' measurement in average of the five runs on the system config. 'Stdev' column shows the standsard deviation of the five measurements of the scores. '(%)' column shows the 'Stdev' to 'Score' ratio in percentage. Finally, 'Normalized' column shows the averaged score values of the configs that normalized to that of 'Baseline'. The periodic hot pages demotion and cold pages promotion that was conducted to simulate dynamic access pattern was started from the beginning of the workload. It resulted in the DRAM tier utilization always under the watermark, and hence no real demotion was happened for all test runs. This means the above results show no difference between LRU-based and DAMON-based demotions. Only difference between NUMAB-2 and DAMON-based promotions are represented on the results. Numab_tiering config degraded the performance about 7.36 %. We suspect this happened because NUMAB-2's synchronous promotion was blocking the Taobench's real work progress. DAMON_tiering config improved the performance about 4.43 %. We believe this shows effectiveness of DAMON-based promotion that didn't block Taobench's real work progress due to its asynchronous nature. Also this means DAMON's monitoring results are accurate enough to provide visible amount of improvement. Evaluation Limitations ---------------------- As mentioned above, this evaluation shows only comparison of promotion mechanisms. DAMON-based tiering is recommended to be used together with reclaim-based demotion as a faster backup under significant memory pressure, though. From some perspective, the modified version of Taobench may seems making the picture distorted too much. It would be better to evaluate with more realistic workload, or more finely tuned micro benchmarks. Patch Sequence ============== The first patch (patch 1) implements two new quota goal metrics on core layer and expose it to DAMON core kernel API. The second and third ones (patches 2 and 3) further link it to DAMON sysfs interface. Three following patches (patches 4-6) document the new feature and sysfs file on design, usage, and ABI documents. The final one (patch 7) implements a working version of a self-tuned DAMON-based memory tiering solution in an incomplete but easy to understand form as a kernel module under samples/damon/ directory. References ========== [1] https://lore.kernel.org/20231112195602.61525-1-sj@kernel.org/ [2] https://lore.kernel.org/20250303221726.484227-1-sj@kernel.org [3] https://github.com/facebookresearch/DCPerf/blob/main/packages/tao_bench/README.md This patch (of 7): Used and free space ratios for specific NUMA nodes can be useful inputs for NUMA-specific DAMOS schemes' aggressiveness self-tuning feedback loop. Implement DAMOS quota goal metrics for such self-tuned schemes. Link: https://lkml.kernel.org/r/20250420194030.75838-1-sj@kernel.org Link: https://lkml.kernel.org/r/20250420194030.75838-2-sj@kernel.org Signed-off-by: SeongJae Park Cc: Yunjeong Mun Cc: Jonathan Corbet Signed-off-by: Andrew Morton