Dear Linux folks,Using `sleepgraph.py` [1][2] to profile the suspend to RAM (STR) times, shows that `ksys_enter` takes a noticeable amount of time.
13 ms on a TUXEDO Book BU1406 with the NVMe device *SAMSUNG MZVKW512HMJP-00000*, which is quite good, and over a 60 ms on ASRock E350M1 with an SSD SanDisk device.
Adding `devicefilter: ksys_sync` to `config/suspend-callgraph.cfg`, and running `sudo ./sleepgraph.py -config config/suspend-callgraph.cfg`, the attached HTML output shows, that `iterate_supers` takes 6 to 7 ms twice.
• `iterate_supers` (6.316 ms @ 388.944557) • `iterate_supers` (0.201 ms @ 388.950873) • `iterate_supers` (7.421 ms @ 388.951074)Normally, `sync_inodes_one_sb` only takes microseconds, but once in both cases it takes several milliseconds.
• sync_inodes_one_sb (0.001 ms @ 388.944660) • sync_inodes_one_sb (5.978 ms @ 388.944665) • sync_inodes_one_sb (0.001 ms @ 388.950645)Please find an excerpt from the call graph from ftrace below, and note the time increase between 388.944751 and 388.950636.
388.944700 | 0) sleepgr-11355 | | wb_wait_for_completion() {
388.944701 | 0) sleepgr-11355 | | _cond_resched() {
388.944701 | 0) sleepgr-11355 | 0.064 us | rcu_all_qs();
388.944702 | 0) sleepgr-11355 | 0.664 us | } /* _cond_resched */
388.944702 | 0) sleepgr-11355 | 0.067 us | init_wait_entry();
388.944703 | 0) sleepgr-11355 | | prepare_to_wait_event() {
388.944703 | 0) sleepgr-11355 | 0.080 us | _raw_spin_lock_irqsave();
388.944704 | 0) sleepgr-11355 | 0.073 us | _raw_spin_unlock_irqrestore();
388.944704 | 0) sleepgr-11355 | 1.388 us | } /* prepare_to_wait_event */
388.944705 | 0) sleepgr-11355 | | schedule() {
388.944705 | 0) sleepgr-11355 | 0.085 us | rcu_note_context_switch();
388.944706 | 0) sleepgr-11355 | 0.064 us | _raw_spin_lock();
388.944707 | 0) sleepgr-11355 | 0.093 us | update_rq_clock();
388.944708 | 0) sleepgr-11355 | | deactivate_task() {
388.944708 | 0) sleepgr-11355 | | dequeue_task_fair() {
388.944708 | 0) sleepgr-11355 | | dequeue_entity() {
388.944709 | 0) sleepgr-11355 | | update_curr() {
388.944709 | 0) sleepgr-11355 | 0.095 us | update_min_vruntime();
388.944710 | 0) sleepgr-11355 | 0.126 us | cpuacct_charge();
388.944710 | 0) sleepgr-11355 | | __cgroup_account_cputime() {
388.944711 | 0) sleepgr-11355 | 0.055 us | cgroup_rstat_updated();
388.944711 | 0) sleepgr-11355 | 0.675 us | } /* __cgroup_account_cputime */
388.944712 | 0) sleepgr-11355 | 2.779 us | } /* update_curr */
388.944712 | 0) sleepgr-11355 | 0.121 us | __update_load_avg_se();
388.944713 | 0) sleepgr-11355 | 0.118 us | __update_load_avg_cfs_rq();
388.944713 | 0) sleepgr-11355 | 0.056 us | clear_buddies();
388.944714 | 0) sleepgr-11355 | 0.066 us | account_entity_dequeue();
388.944714 | 0) sleepgr-11355 | 0.050 us | update_cfs_group();
388.944715 | 0) sleepgr-11355 | 6.127 us | } /* dequeue_entity */
388.944715 | 0) sleepgr-11355 | | dequeue_entity() {
388.944715 | 0) sleepgr-11355 | | update_curr() {
388.944716 | 0) sleepgr-11355 | 0.097 us | __calc_delta();
388.944716 | 0) sleepgr-11355 | 0.071 us | update_min_vruntime();
388.944717 | 0) sleepgr-11355 | 1.473 us | } /* update_curr */
388.944717 | 0) sleepgr-11355 | 0.142 us | __update_load_avg_se();
388.944718 | 0) sleepgr-11355 | 0.100 us | __update_load_avg_cfs_rq();
388.944719 | 0) sleepgr-11355 | 0.069 us | clear_buddies();
388.944719 | 0) sleepgr-11355 | 0.098 us | account_entity_dequeue();
388.944720 | 0) sleepgr-11355 | | update_cfs_group() {
388.944720 | 0) sleepgr-11355 | 0.110 us | reweight_entity();
388.944721 | 0) sleepgr-11355 | 0.847 us | } /* update_cfs_group */
388.944721 | 0) sleepgr-11355 | 6.197 us | } /* dequeue_entity */
388.944722 | 0) sleepgr-11355 | 0.053 us | hrtick_update();
388.944722 | 0) sleepgr-11355 | 14.141 us | } /* dequeue_task_fair */
388.944723 | 0) sleepgr-11355 | 14.827 us | } /* deactivate_task */
388.944723 | 0) sleepgr-11355 | | pick_next_task_fair() {
388.944723 | 0) sleepgr-11355 | | update_blocked_averages() {
388.944724 | 0) sleepgr-11355 | 0.070 us | _raw_spin_lock_irqsave();
388.944724 | 0) sleepgr-11355 | 0.090 us | update_rq_clock();
388.944725 | 0) sleepgr-11355 | 0.120 us | __update_load_avg_cfs_rq();
388.944726 | 0) sleepgr-11355 | 0.162 us | __update_load_avg_se();
388.944727 | 0) sleepgr-11355 | 0.090 us | __update_load_avg_cfs_rq();
388.944727 | 0) sleepgr-11355 | 0.081 us | __update_load_avg_cfs_rq();
388.944728 | 0) sleepgr-11355 | | update_rt_rq_load_avg() {
388.944728 | 0) sleepgr-11355 | 0.063 us | __accumulate_pelt_segments();
388.944729 | 0) sleepgr-11355 | 0.785 us | } /* update_rt_rq_load_avg */
388.944729 | 0) sleepgr-11355 | | update_dl_rq_load_avg() {
388.944730 | 0) sleepgr-11355 | 0.066 us | __accumulate_pelt_segments();
388.944730 | 0) sleepgr-11355 | 0.763 us | } /* update_dl_rq_load_avg */
388.944731 | 0) sleepgr-11355 | 0.061 us | _raw_spin_unlock_irqrestore();
388.944731 | 0) sleepgr-11355 | 7.452 us | } /* update_blocked_averages */
388.944731 | 0) sleepgr-11355 | | load_balance() {
388.944732 | 0) sleepgr-11355 | | find_busiest_group() {
388.944732 | 0) sleepgr-11355 | 0.100 us | update_nohz_stats();
388.944733 | 0) sleepgr-11355 | 0.057 us | idle_cpu();
388.944734 | 0) sleepgr-11355 | 0.098 us | update_nohz_stats();
388.944734 | 0) sleepgr-11355 | 2.407 us | } /* find_busiest_group */
388.944735 | 0) sleepgr-11355 | 3.120 us | } /* load_balance */
388.944735 | 0) sleepgr-11355 | 0.065 us | __msecs_to_jiffies();
388.944736 | 0) sleepgr-11355 | | load_balance() {
388.944736 | 0) sleepgr-11355 | | find_busiest_group() {
388.944736 | 0) sleepgr-11355 | 0.087 us | update_nohz_stats();
388.944737 | 0) sleepgr-11355 | 0.063 us | idle_cpu();
388.944738 | 0) sleepgr-11355 | 0.086 us | update_nohz_stats();
388.944739 | 0) sleepgr-11355 | 0.068 us | update_nohz_stats();
388.944739 | 0) sleepgr-11355 | 0.098 us | idle_cpu();
388.944740 | 0) sleepgr-11355 | 0.094 us | update_nohz_stats();
388.944741 | 0) sleepgr-11355 | 0.065 us | idle_cpu();
388.944741 | 0) sleepgr-11355 | 5.160 us | } /* find_busiest_group */
388.944742 | 0) sleepgr-11355 | 5.831 us | } /* load_balance */
388.944742 | 0) sleepgr-11355 | 0.062 us | __msecs_to_jiffies();
388.944743 | 0) sleepgr-11355 | 0.065 us | _raw_spin_lock();
388.944743 | 0) sleepgr-11355 | 20.205 us | } /* pick_next_task_fair */
388.944744 | 0) sleepgr-11355 | | pick_next_task_idle() {
388.944744 | 0) sleepgr-11355 | | put_prev_task_fair() {
388.944745 | 0) sleepgr-11355 | | put_prev_entity() {
388.944745 | 0) sleepgr-11355 | 0.064 us | check_cfs_rq_runtime();
388.944746 | 0) sleepgr-11355 | 0.713 us | } /* put_prev_entity */
388.944746 | 0) sleepgr-11355 | | put_prev_entity() {
388.944746 | 0) sleepgr-11355 | 0.068 us | check_cfs_rq_runtime();
388.944747 | 0) sleepgr-11355 | 0.691 us | } /* put_prev_entity */
388.944747 | 0) sleepgr-11355 | 2.633 us | } /* put_prev_task_fair */
388.944748 | 0) sleepgr-11355 | 0.094 us | __update_idle_core();
388.944748 | 0) sleepgr-11355 | 3.899 us | } /* pick_next_task_idle */
388.944749 | 0) sleepgr-11355 | | enter_lazy_tlb() {
388.944749 | 0) sleepgr-11355 | | switch_mm() {
388.944749 | 0) sleepgr-11355 | | switch_mm_irqs_off() {
388.944750 | 0) sleepgr-11355 | 0.244 us | load_new_mm_cr3();
388.944751 | 0) sleepgr-11355 | 0.955 us | } /* switch_mm_irqs_off */
388.944751 | 0) sleepgr-11355 | 1.472 us | } /* switch_mm */
388.944751 | 0) sleepgr-11355 | 2.023 us | } /* enter_lazy_tlb */
388.950636 | 0) sleepgr-11355 | 0.103 us | finish_task_switch();
388.950638 | 0) sleepgr-11355 | 5932.632 us | } /* schedule */
388.950638 | 0) sleepgr-11355 | | prepare_to_wait_event() {
388.950638 | 0) sleepgr-11355 | 0.068 us | _raw_spin_lock_irqsave();
388.950638 | 0) sleepgr-11355 | 0.053 us | _raw_spin_unlock_irqrestore();
388.950639 | 0) sleepgr-11355 | 0.866 us | } /* prepare_to_wait_event */
388.950639 | 0) sleepgr-11355 | | finish_wait() {
388.950639 | 0) sleepgr-11355 | 0.046 us | _raw_spin_lock_irqsave();
388.950640 | 0) sleepgr-11355 | 0.052 us | _raw_spin_unlock_irqrestore();
388.950640 | 0) sleepgr-11355 | 0.788 us | } /* finish_wait */
388.950640 | 0) sleepgr-11355 | 5939.443 us | } /* wb_wait_for_completion */
Can these outliers be avoided? As this is in `schedule`, is it related to the used scheduler? At least the Intel Skylake i7-7500U CPU @ 2.70GHz processor with four threads in the TUXEDO laptop should have enough performance.
No scheduler seems to be used for the NVMe device.$ more /sys/devices/pci0000:00/0000:00:1d.0/0000:04:00.0/nvme/nvme0/nvme0n1/queue/scheduler
[none]
Kind regards,
Paul
[1]: https://01.org/suspendresume
[2]: https://github.com/01org/pm-graph
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