Re: [LSF/MM/BPF TOPIC] Reimagining Memory Cgroup (memcg_ext)

[hui.zhu@linux.dev]

2026年3月8日 02:24, "Shakeel Butt" <shakeel.butt@linux.dev mailto:shakeel.butt@linux.dev?to=%22Shakeel%20Butt%22%20%3Cshakeel.butt%40linux.dev%3E > 写到:


> 
> Over the last couple of weeks, I have been brainstorming on how I would go
> about redesigning memcg, taking inspiration from sched_ext and bpfoom, with a
> focus on existing challenges and issues. This proposal outlines the high-level
> direction. Followup emails and patch series will cover and brainstorm the
> mechanisms (of course BPF) to achieve these goals.
> 
> Memory cgroups provide memory accounting and the ability to control memory usage
> of workloads through two categories of limits. Throttling limits (memory.max and
> memory.high) cap memory consumption. Protection limits (memory.min and
> memory.low) shield a workload's memory from reclaim under external memory
> pressure.
> 
> Challenges
> ----------
> 
> - Workload owners rarely know their actual memory requirements, leading to
>  overprovisioned limits, lower utilization, and higher infrastructure costs.
> 
> - Throttling limit enforcement is synchronous in the allocating task's context,
>  which can stall latency-sensitive threads.
> 
> - The stalled thread may hold shared locks, causing priority inversion -- all
>  waiters are blocked regardless of their priority.
> 
> - Enforcement is indiscriminate -- there is no way to distinguish a
>  performance-critical or latency-critical allocator from a latency-tolerant
>  one.
> 
> - Protection limits assume static working sets size, forcing owners to either
>  overprovision or build complex userspace infrastructure to dynamically adjust
>  them.
> 
> Feature Wishlist
> ----------------
> 
> Here is the list of features and capabilities I want to enable in the
> redesigned memcg limit enforcement world.
> 
> Per-Memcg Background Reclaim
> 
> In the new memcg world, with the goal of (mostly) eliminating direct synchronous
> reclaim for limit enforcement, provide per-memcg background reclaimers which can
> scale across CPUs with the allocation rate.

I am aware that several companies maintain out-of-tree patches for
asynchronous reclaim, though some have not yet attempted to upstream
them.

Would it be feasible to introduce a generic memcg asynchronous reclaim
framework into the upstream kernel, where eBPF is used to orchestrate
and control the reclaim logic? In this model, the kernel's role would
be to enforce "guardrails" for these operations—for instance,
restricting a BPF program to initiating only one asynchronous reclaim
pass at a time—to ensure system safety and predictability.

Best,
Hui


> 
> Lock-Aware Throttling
> 
> The ability to avoid throttling an allocating task that is holding locks, to
> prevent priority inversion. In Meta's fleet, we have observed lock holders stuck
> in memcg reclaim, blocking all waiters regardless of their priority or
> criticality.
> 
> Thread-Level Throttling Control
> 
> Workloads should be able to indicate at the thread level which threads can be
> synchronously throttled and which cannot. For example, while experimenting with
> sched_ext, we drastically improved the performance of AI training workloads by
> prioritizing threads interacting with the GPU. Similarly, applications can
> identify the threads or thread pools on their performance-critical paths and
> the memcg enforcement mechanism should not throttle them.
> 
> Combined Memory and Swap Limits
> 
> Some users (Google actually) need the ability to enforce limits based on
> combined memory and swap usage, similar to cgroup v1's memsw limit, providing a
> ceiling on total memory commitment rather than treating memory and swap
> independently.
> 
> Dynamic Protection Limits
> 
> Rather than static protection limits, the kernel should support defining
> protection based on the actual working set of the workload, leveraging signals
> such as working set estimation, PSI, refault rates, or a combination thereof to
> automatically adapt to the workload's current memory needs.
> 
> Shared Memory Semantics
> 
> With more flexibility in limit enforcement, the kernel should be able to
> account for memory shared between workloads (cgroups) during enforcement.
> Today, enforcement only looks at each workload's memory usage independently.
> Sensible shared memory semantics would allow the enforcer to consider
> cross-cgroup sharing when making reclaim and throttling decisions.
> 
> Memory Tiering
> 
> With a flexible limit enforcement mechanism, the kernel can balance memory
> usage of different workloads across memory tiers based on their performance
> requirements. Tier accounting and hotness tracking are orthogonal, but the
> decisions of when and how to balance memory between tiers should be handled by
> the enforcer.
> 
> Collaborative Load Shedding
> 
> Many workloads communicate with an external entity for load balancing and rely
> on their own usage metrics like RSS or memory pressure to signal whether they
> can accept more or less work. This is guesswork. Instead of the
> workload guessing, the limit enforcer -- which is actually managing the
> workload's memory usage -- should be able to communicate available headroom or
> request the workload to shed load or reduce memory usage. This collaborative
> load shedding mechanism would allow workloads to make informed decisions rather
> than reacting to coarse signals.
> 
> Cross-Subsystem Collaboration
> 
> Finally, the limit enforcement mechanism should collaborate with the CPU
> scheduler and other subsystems that can release memory. For example, dirty
> memory is not reclaimable and the memory subsystem wakes up flushers to trigger
> writeback. However, flushers need CPU to run -- asking the CPU scheduler to
> prioritize them ensures the kernel does not lack reclaimable memory under
> stressful conditions. Similarly, some subsystems free memory through workqueues
> or RCU callbacks. While this may seem orthogonal to limit enforcement, we can
> definitely take advantage by having visibility into these situations.
> 
> Putting It All Together
> -----------------------
> 
> To illustrate the end goal, here is an example of the scenario I want to
> enable. Suppose there is an AI agent controlling the resources of a host. I
> should be able to provide the following policy and everything should work out
> of the box:
> 
> Policy: "keep system-level memory utilization below 95 percent;
> avoid priority inversions by not throttling allocators holding locks; trim each
> workload's usage to its working set without regressing its relevant performance
> metrics; collaborate with workloads on load shedding and memory trimming
> decisions; and under extreme memory pressure, collaborate with the OOM killer
> and the central job scheduler to kill and clean up a workload."
> 
> Initially I added this example for fun, but from [1] it seems like there is a
> real need to enable such capabilities.
> 
> [1] https://arxiv.org/abs/2602.09345
>