- [Quiescent-State Based Reclamation (QSBR)](qsbr.md)

- [asyncio](asyncio.md)

When implementing lock-free data structures, a key challenge is determining

when it is safe to free memory that has been logically removed from a

structure. Freeing memory too early can lead to use-after-free bugs if another

thread is still accessing it. Freeing it too late results in excessive memory

consumption.

Safe memory reclamation (SMR) schemes address this by delaying the free

operation until all concurrent read accesses are guaranteed to have completed.

Quiescent-State Based Reclamation (QSBR) is a SMR scheme used in Python's

free-threaded build to manage the lifecycle of shared memory.

QSBR requires threads to periodically report that they are in a quiescent

state. A thread is in a quiescent state if it holds no references to shared

objects that might be reclaimed. Think of it as a checkpoint where a thread

signals, "I am not in the middle of any operation that relies on a shared

resource." In Python, the eval_breaker provides a natural and convenient place

for threads to report this state.

While CPython's memory management is dominated by reference counting and a

tracing garbage collector, these mechanisms are not suitable for all data

structures. For example, the backing array of a list object is not individually

reference-counted but may have a shorter lifetime than the `PyListObject` that

contains it. We could delay reclamation until the next GC run, but we want

reclamation to be prompt and to run the GC less frequently in the free-threaded

build, as it requires pausing all threads.

Many operations in the free-threaded build are protected by locks. However, for

performance-critical code, we want to allow reads to happen concurrently with

updates. For instance, we want to avoid locking during most list read accesses.

If a list is resized while another thread is reading it, QSBR provides the

mechanism to determine when it is safe to free the list's old backing array.

Specific use cases for QSBR include:

* Dictionary keys (`PyDictKeysObject`) and list arrays (`_PyListArray`): When a

dictionary or list that may be shared between threads is resized, we use QSBR

to delay freeing the old keys or array until it's safe. For dicts and lists

that are not shared, their storage can be freed immediately upon resize.

* Mimalloc `mi_page_t`: Non-locking dictionary and list accesses require

cooperation from the memory allocator. If an object is freed and its memory is

reused, we must ensure the new object's reference count field is at the same

memory location. In practice, this means when a mimalloc page (`mi_page_t`)

becomes empty, we don't immediately allow it to be reused for allocations of a

different size class. QSBR is used to determine when it's safe to repurpose the

page or return its memory to the OS.

The proposal to add QSBR to Python is contained in

[Github issue 115103](https://github.com/python/cpython/issues/115103).

Many details of that proposal have been copied here, so they can be kept

up-to-date with the actual implementation.

Python's QSBR implementation is based on FreeBSD's "Global Unbounded

Sequences." [^1][^2][^3]. It relies on a few key counters:

* Global Write Sequence (`wr_seq`): A per-interpreter counter, `wr_seq`, is started

at 1 and incremented by 2 each time it is advanced. This ensures its value is

always odd, which can be used to distinguish it from other state values. When

an object needs to be reclaimed, `wr_seq` is advanced, and the object is tagged

with this new sequence number.

* Per-Thread Read Sequence: Each thread has a local read sequence counter. When

a thread reaches a quiescent state (e.g., at the eval_breaker), it copies the

current global `wr_seq` to its local counter.

* Global Read Sequence (`rd_seq`): This per-interpreter value stores the minimum

of all per-thread read sequence counters (excluding detached threads). It is

updated by a "polling" operation.

To free an object, the following steps are taken:

1. Advance the global `wr_seq`.

2. Add the object's pointer to a deferred-free list, tagging it with the new

`wr_seq` value as its qsbr_goal.

Periodically, a polling mechanism processes this deferred-free list:

1. The minimum read sequence value across all active threads is calculated and

stored as the global `rd_seq`.

2. For each item on the deferred-free list, if its qsbr_goal is less than or

equal to the new `rd_seq`, its memory is freed, and it is removed from the:

list. Otherwise, it remains on the list for a future attempt.

To reduce memory contention from frequent updates to the global `wr_seq`, its

advancement is sometimes deferred. Instead of incrementing `wr_seq` on every

reclamation request, each thread tracks its number of deferrals locally. Once

the deferral count reaches a limit (QSBR_DEFERRED_LIMIT, currently 10), the

thread advances the global `wr_seq` and resets its local count.

When an object is added to the deferred-free list, its qsbr_goal is set to

`wr_seq` + 2. By setting the goal to the next sequence value, we ensure it's safe

to defer the global counter advancement. This optimization improves runtime

speed but may increase peak memory usage by slightly delaying when memory can

be reclaimed.

Determining the `rd_seq` requires scanning over all thread states. This operation

could become a bottleneck in applications with a very large number of threads

(e.g., >1,000). Future work may address this with more advanced mechanisms,

such as a tree-based structure or incremental scanning. For now, the

implementation prioritizes simplicity, with plans for refinement if

multi-threaded benchmarks reveal performance issues.

[^1]: https://youtu.be/ZXUIFj4nRjk?t=694

[^2]: https://people.kernel.org/joelfernandes/gus-vs-rcu

[^3]: http://bxr.su/FreeBSD/sys/kern/subr_smr.c#44