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authorTejun Heo <tj@kernel.org>2023-05-17 17:02:09 -1000
committerTejun Heo <tj@kernel.org>2023-05-17 17:02:09 -1000
commit8a1dd1e547c1a037692e7a6da6a76108108c72b1 (patch)
tree8441f7c4e566a76ecc0bb4d94091d0997f05f8f4 /kernel
parent6363845005202148b8409ec3082e80845c19d309 (diff)
workqueue: Track and monitor per-workqueue CPU time usage
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>
Diffstat (limited to 'kernel')
-rw-r--r--kernel/workqueue.c3
1 files changed, 3 insertions, 0 deletions
diff --git a/kernel/workqueue.c b/kernel/workqueue.c
index 4ca66384d288..ee16ddb0647c 100644
--- a/kernel/workqueue.c
+++ b/kernel/workqueue.c
@@ -212,6 +212,7 @@ struct worker_pool {
enum pool_workqueue_stats {
PWQ_STAT_STARTED, /* work items started execution */
PWQ_STAT_COMPLETED, /* work items completed execution */
+ PWQ_STAT_CPU_TIME, /* total CPU time consumed */
PWQ_STAT_CPU_INTENSIVE, /* wq_cpu_intensive_thresh_us violations */
PWQ_STAT_CM_WAKEUP, /* concurrency-management worker wakeups */
PWQ_STAT_MAYDAY, /* maydays to rescuer */
@@ -1136,6 +1137,8 @@ void wq_worker_tick(struct task_struct *task)
if (!pwq)
return;
+ pwq->stats[PWQ_STAT_CPU_TIME] += TICK_USEC;
+
/*
* If the current worker is concurrency managed and hogged the CPU for
* longer than wq_cpu_intensive_thresh_us, it's automatically marked