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authorThomas Gleixner <tglx@linutronix.de>2025-11-19 18:27:14 +0100
committerThomas Gleixner <tglx@linutronix.de>2025-11-25 19:45:41 +0100
commit9a723ed7facff6955da8d64cc9de7066038036c1 (patch)
tree803913a3e145a039495348fb672fb68471ce3798 /scripts/lib/abi/helpers.py
parent23343b6b09acb4bf97f34ed60e135000ca57ede1 (diff)
sched/mmcid: Provide new scheduler CID mechanism
The MM CID management has two fundamental requirements: 1) It has to guarantee that at no given point in time the same CID is used by concurrent tasks in userspace. 2) The CID space must not exceed the number of possible CPUs in a system. While most allocators (glibc, tcmalloc, jemalloc) do not care about that, there seems to be at least some LTTng library depending on it. The CID space compaction itself is not a functional correctness requirement, it is only a useful optimization mechanism to reduce the memory foot print in unused user space pools. The optimal CID space is: min(nr_tasks, nr_cpus_allowed); Where @nr_tasks is the number of actual user space threads associated to the mm and @nr_cpus_allowed is the superset of all task affinities. It is growth only as it would be insane to take a racy snapshot of all task affinities when the affinity of one task changes just do redo it 2 milliseconds later when the next task changes it's affinity. That means that as long as the number of tasks is lower or equal than the number of CPUs allowed, each task owns a CID. If the number of tasks exceeds the number of CPUs allowed it switches to per CPU mode, where the CPUs own the CIDs and the tasks borrow them as long as they are scheduled in. For transition periods CIDs can go beyond the optimal space as long as they don't go beyond the number of possible CPUs. The current upstream implementation adds overhead into task migration to keep the CID with the task. It also has to do the CID space consolidation work from a task work in the exit to user space path. As that work is assigned to a random task related to a MM this can inflict unwanted exit latencies. Implement the context switch parts of a strict ownership mechanism to address this. This removes most of the work from the task which schedules out. Only during transitioning from per CPU to per task ownership it is required to drop the CID when leaving the CPU to prevent CID space exhaustion. Other than that scheduling out is just a single check and branch. The task which schedules in has to check whether: 1) The ownership mode changed 2) The CID is within the optimal CID space In stable situations this results in zero work. The only short disruption is when ownership mode changes or when the associated CID is not in the optimal CID space. The latter only happens when tasks exit and therefore the optimal CID space shrinks. That mechanism is strictly optimized for the common case where no change happens. The only case where it actually causes a temporary one time spike is on mode changes when and only when a lot of tasks related to a MM schedule exactly at the same time and have eventually to compete on allocating a CID from the bitmap. In the sysbench test case which triggered the spinlock contention in the initial CID code, __schedule() drops significantly in perf top on a 128 Core (256 threads) machine when running sysbench with 255 threads, which fits into the task mode limit of 256 together with the parent thread: Upstream rseq/perf branch +CID rework 0.42% 0.37% 0.32% [k] __schedule Increasing the number of threads to 256, which puts the test process into per CPU mode looks about the same. Signed-off-by: Thomas Gleixner <tglx@linutronix.de> Signed-off-by: Peter Zijlstra (Intel) <peterz@infradead.org> Signed-off-by: Thomas Gleixner <tglx@linutronix.de> Reviewed-by: Mathieu Desnoyers <mathieu.desnoyers@efficios.com> Link: https://patch.msgid.link/20251119172550.023984859@linutronix.de
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