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authorDenis Benato <denis.benato@linux.dev>2025-12-29 16:07:55 +0100
committerIlpo Järvinen <ilpo.jarvinen@linux.intel.com>2025-12-29 17:41:21 +0200
commit6a02651c4c4b710ecbaf798eb4feb57c97f2bc14 (patch)
tree1321a8deff839b2771b241ea53334de7204355e0 /tools/lib/python/kdoc/python_version.py
parent66e245db16f0175af656cd812b6dc1a5e1f7b80a (diff)
downloadkernel-6a02651c4c4b710ecbaf798eb4feb57c97f2bc14.tar.gz
platform/x86: asus-armoury: fix ppt data for FA507R
PPT data for FA507R was reported to be wrong by a user: change limits to make them equal to Armoury Crate limits. Fixes: 39ae6c50e599 ("platform/x86: asus-armoury: add ppt_* and nv_* tuning knobs") Signed-off-by: Denis Benato <denis.benato@linux.dev> Link: https://patch.msgid.link/20251229150755.1351495-1-denis.benato@linux.dev Reviewed-by: Ilpo Järvinen <ilpo.jarvinen@linux.intel.com> Signed-off-by: Ilpo Järvinen <ilpo.jarvinen@linux.intel.com>
Diffstat (limited to 'tools/lib/python/kdoc/python_version.py')
0 files changed, 0 insertions, 0 deletions
generated by cgit v1.2.3 (git 2.46.0) at 2026-08-22 01:18:19 +0000
ride the default scope and "affinity_scope" sysfs file to configure it per workqueue. wq_dump.py and documentations are updated accordingly. This enables significant flexibility in configuring how unbound workqueues behave. If affinity scope is set to "cpu", it'll behave close to a per-cpu workqueue. On the other hand, "system" removes all locality boundaries. Many modern machines have multiple L3 caches often while being mostly uniform in terms of memory access. Thus, workqueue's previous behavior of spreading work items in each NUMA node had negative performance implications from unncessarily crossing L3 boundaries between issue and execution. However, picking a finer grained affinity scope also has a downside in that an issuer in one group can't utilize CPUs in other groups. While dependent on the specifics of workload, there's usually a noticeable penalty in crossing L3 boundaries, so let's default to CACHE. This issue will be further addressed and documented with examples in future patches. Signed-off-by: Tejun Heo <tj@kernel.org> 2023-08-07workqueue: Add tools/workqueue/wq_dump.py which prints out workqueue ↵Tejun Heo configuration Lack of visibility has always been a pain point for workqueues. While the recently added wq_monitor.py improved the situation, it's still difficult to understand what worker pools are active in the system, how workqueues map to them and why. The lack of visibility into how workqueues are configured is going to become more noticeable as workqueue improves locality awareness and provides more mechanisms to customize locality related behaviors. Now that the basic framework for more flexible locality support is in place, this is a good time to improve the situation. This patch adds tools/workqueues/wq_dump.py which prints out the topology configuration, worker pools and how workqueues are mapped to pools. Read the command's help message for more details. Signed-off-by: Tejun Heo <tj@kernel.org> 2023-05-17workqueue: Track and monitor per-workqueue CPU time usageTejun Heo Now that wq_worker_tick() is there, we can easily track the rough CPU time consumption of each workqueue by charging the whole tick whenever a tick hits an active workqueue. While not super accurate, it provides reasonable visibility into the workqueues that consume a lot of CPU cycles. wq_monitor.py is updated to report the per-workqueue CPU times. v2: wq_monitor.py was using "cputime" as the key when outputting in json format. Use "cpu_time" instead for consistency with other fields. Signed-off-by: Tejun Heo <tj@kernel.org> 2023-05-17workqueue: Automatically mark CPU-hogging work items CPU_INTENSIVETejun Heo If a per-cpu work item hogs the CPU, it can prevent other work items from starting through concurrency management. A per-cpu workqueue which intends to host such CPU-hogging work items can choose to not participate in concurrency management by setting %WQ_CPU_INTENSIVE; however, this can be error-prone and difficult to debug when missed. This patch adds an automatic CPU usage based detection. If a concurrency-managed work item consumes more CPU time than the threshold (10ms by default) continuously without intervening sleeps, wq_worker_tick() which is called from scheduler_tick() will detect the condition and automatically mark it CPU_INTENSIVE. The mechanism isn't foolproof: * Detection depends on tick hitting the work item. Getting preempted at the right timings may allow a violating work item to evade detection at least temporarily. * nohz_full CPUs may not be running ticks and thus can fail detection. * Even when detection is working, the 10ms detection delays can add up if many CPU-hogging work items are queued at the same time. However, in vast majority of cases, this should be able to detect violations reliably and provide reasonable protection with a small increase in code complexity. If some work items trigger this condition repeatedly, the bigger problem likely is the CPU being saturated with such per-cpu work items and the solution would be making them UNBOUND. The next patch will add a debug mechanism to help spot such cases. v4: Documentation for workqueue.cpu_intensive_thresh_us added to kernel-parameters.txt. v3: Switch to use wq_worker_tick() instead of hooking into preemptions as suggested by Peter. v2: Lai pointed out that wq_worker_stopping() also needs to be called from preemption and rtlock paths and an earlier patch was updated accordingly. This patch adds a comment describing the risk of infinte recursions and how they're avoided. Signed-off-by: Tejun Heo <tj@kernel.org> Acked-by: Peter Zijlstra <peterz@infradead.org> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Lai Jiangshan <jiangshanlai@gmail.com> 2023-05-17workqueue: Add pwq->stats[] and a monitoring scriptTejun Heo Currently, the only way to peer into workqueue operations is through tracing. While possible, it isn't easy or convenient to monitor per-workqueue behaviors over time this way. Let's add pwq->stats[] that track relevant events and a drgn monitoring script - tools/workqueue/wq_monitor.py. It's arguable whether this needs to be configurable. However, it currently only has several counters and the runtime overhead shouldn't be noticeable given that they're on pwq's which are per-cpu on per-cpu workqueues and per-numa-node on unbound ones. Let's keep it simple for the time being. v2: Patch reordered to earlier with fewer fields. Field will be added back gradually. Help message improved. Signed-off-by: Tejun Heo <tj@kernel.org> Cc: Lai Jiangshan <jiangshanlai@gmail.com>