Re: [PATCH v3] sched/fair: Rebuild load weight when switching to fair

[sashiko-bot@kernel.org]

Thank you for your contribution! Sashiko AI review found 1 potential issue(s) to consider:
- [High] Updating task load weight without scaling its PELT averages corrupts load_sum when attaching to fair.
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commit 5e323dec0121afc6858dcf6c332ec85a8dc01718
Author: Zicheng Qu <quzicheng@huawei.com>

sched/fair: Rebuild load weight when switching to fair

Tasks running outside the fair scheduling class may not keep their
load weight in sync. This commit rebuilds the load weight from the
switching_to hook before enqueueing back into fair.

> diff --git a/kernel/sched/fair.c b/kernel/sched/fair.c
> index 62a2dcb0d03e6..3671b512dcf7f 100644
> --- a/kernel/sched/fair.c
> +++ b/kernel/sched/fair.c

[ ... ]

> @@ -14957,6 +14957,15 @@ static void switched_from_fair(struct rq *rq, struct task_struct *p)
>  	detach_task_cfs_rq(p);
>  }
>  
> +static void switching_to_fair(struct rq *rq, struct task_struct *p)
> +{
> +	/*
> +	 * Tasks may come from classes that don't keep se.load up to date.
> +	 * Rebuild it before the task is enqueued.
> +	 */
> +	set_load_weight(p, false);

[Severity: High]
Does updating the task load weight without scaling its PELT averages corrupt
load_sum when attaching to fair?

When a task transitions to fair, switched_to_fair() enqueues it by calling
attach_task_cfs_rq() -> attach_entity_load_avg(). The attach_entity_load_avg()
function relies on se.load.weight matching se.avg.load_avg to reconstruct the
unweighted load_sum:

kernel/sched/fair.c:attach_entity_load_avg() {
    ...
    se->avg.load_sum = div_u64(se->avg.load_sum, se_weight(se));
    ...
}

Since load_avg is based on the old weight but se_weight() returns the newly
updated weight, load_sum ends up mathematically scaled by old_weight /
new_weight. If a task's nice value was changed to a lower priority (smaller
weight) while outside fair, load_sum could be artificially inflated by a
massive factor, polluting cfs_rq->avg and disrupting CPU load balancing.

> +}
> +

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Sashiko AI review · https://sashiko.dev/#/patchset/20260528131238.3879110-1-quzicheng315@gmail.com?part=1