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>

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>

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>