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2023-05-18workqueue: Track and monitor per-workqueue CPU time usageTejun Heo1-1/+8
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>
2023-05-18workqueue: Automatically mark CPU-hogging work items CPU_INTENSIVETejun Heo1-1/+12
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>
2023-05-18workqueue: Add pwq->stats[] and a monitoring scriptTejun Heo1-0/+150
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>