Currently, we only use per-thread reference counting for heap type objects and
the naming reflects that. We will extend it to a few additional types in an
upcoming change to avoid scaling bottlenecks when creating nested functions.
Rename some of the files and functions in preparation for this change.
The free-threaded build partially stores heap type reference counts in
distributed manner in per-thread arrays. This avoids reference count
contention when creating or destroying instances.
Co-authored-by: Ken Jin <kenjin@python.org>
We already intern and immortalize most string constants. In the
free-threaded build, other constants can be a source of reference count
contention because they are shared by all threads running the same code
objects.
The module itself is a thin wrapper around calls to functions in
`Python/codecs.c`, so that's where the meaningful changes happened:
- Move codecs-related state that lives on `PyInterpreterState` to a
struct declared in `pycore_codecs.h`.
- In free-threaded builds, add a mutex to `codecs_state` to synchronize
operations on `search_path`. Because `search_path_mutex` is used as a
normal mutex and not a critical section, we must be extremely careful
with operations called while holding it.
- The codec registry is explicitly initialized as part of
`_PyUnicode_InitEncodings` to simplify thread-safety.
This is similar to the situation with threading._DummyThread. The methods (incl. __del__()) of interpreters.Interpreter objects must be careful with interpreters not created by interpreters.create(). The simplest thing to start with is to disable any method that modifies or runs in the interpreter. As part of this, the runtime keeps track of where an interpreter was created. We also handle interpreter "refcounts" properly.
Most mutable data is protected by a striped lock that is keyed on the
referenced object's address. The weakref's hash is protected using the
weakref's per-object lock.
Note that this only affects free-threaded builds. Apart from some minor
refactoring, the added code is all either gated by `ifdef`s or is a no-op
(e.g. `Py_BEGIN_CRITICAL_SECTION`).
Introduce a unified 16-bit backoff counter type (``_Py_BackoffCounter``),
shared between the Tier 1 adaptive specializer and the Tier 2 optimizer. The
API used for adaptive specialization counters is changed but the behavior is
(supposed to be) identical.
The behavior of the Tier 2 counters is changed:
- There are no longer dynamic thresholds (we never varied these).
- All counters now use the same exponential backoff.
- The counter for ``JUMP_BACKWARD`` starts counting down from 16.
- The ``temperature`` in side exits starts counting down from 64.
I added it quite a while ago as a strategy for managing interpreter lifetimes relative to the PEP 554 (now 734) implementation. Relatively recently I refactored that implementation to no longer rely on InterpreterID objects. Thus now I'm removing it.
Mostly we unify the two different implementations of the conversion code (from PyObject * to int64_t. We also drop the PyArg_ParseTuple()-style converter function, as well as rename and move PyInterpreterID_LookUp().
Somehow we ended up with two separate counter variables tracking "the next function version".
Most likely this was a historical accident where an old branch was updated incorrectly.
This PR merges the two counters into a single one: `interp->func_state.next_version`.
This adds `_PyMem_FreeDelayed()` and supporting functions. The
`_PyMem_FreeDelayed()` function frees memory with the same allocator as
`PyMem_Free()`, but after some delay to ensure that concurrent lock-free
readers have finished.
This adds a safe memory reclamation scheme based on FreeBSD's "GUS" and
quiescent state based reclamation (QSBR). The API provides a mechanism
for callers to detect when it is safe to free memory that may be
concurrently accessed by readers.
Biased reference counting maintains two refcount fields in each object:
`ob_ref_local` and `ob_ref_shared`. The true refcount is the sum of these two
fields. In some cases, when refcounting operations are split across threads,
the ob_ref_shared field can be negative (although the total refcount must be
at least zero). In this case, the thread that decremented the refcount
requests that the owning thread give up ownership and merge the refcount
fields.
For interpreters that share state with the main interpreter, this points
to the same static memory structure. For interpreters with their own
obmalloc state, it is heap allocated. Add free_obmalloc_arenas() which
will free the obmalloc arenas and radix tree structures for interpreters
with their own obmalloc state.
Co-authored-by: Eric Snow <ericsnowcurrently@gmail.com>
The `--disable-gil` builds occasionally need to pause all but one thread. Some
examples include:
* Cyclic garbage collection, where this is often called a "stop the world event"
* Before calling `fork()`, to ensure a consistent state for internal data structures
* During interpreter shutdown, to ensure that daemon threads aren't accessing Python objects
This adds the following functions to implement global and per-interpreter pauses:
* `_PyEval_StopTheWorldAll()` and `_PyEval_StartTheWorldAll()` (for the global runtime)
* `_PyEval_StopTheWorld()` and `_PyEval_StartTheWorld()` (per-interpreter)
(The function names may change.)
These functions are no-ops outside of the `--disable-gil` build.
* gh-112532: Isolate abandoned segments by interpreter
Mimalloc segments are data structures that contain memory allocations along
with metadata. Each segment is "owned" by a thread. When a thread exits,
it abandons its segments to a global pool to be later reclaimed by other
threads. This changes the pool to be per-interpreter instead of process-wide.
This will be important for when we use mimalloc to find GC objects in the
`--disable-gil` builds. We want heaps to only store Python objects from a
single interpreter. Absent this change, the abandoning and reclaiming process
could break this isolation.
* Add missing '&_mi_abandoned_default' to 'tld_empty'
Every PyThreadState instance is now actually a _PyThreadStateImpl.
It is safe to cast from `PyThreadState*` to `_PyThreadStateImpl*` and back.
The _PyThreadStateImpl will contain fields that we do not want to expose
in the public C API.
This moves several general internal APIs out of _xxsubinterpretersmodule.c and into the new Python/crossinterp.c (and the corresponding internal headers).
Specifically:
* _Py_excinfo, etc.: the initial implementation for non-object exception snapshots (in pycore_pyerrors.h and Python/errors.c)
* _PyXI_exception_info, etc.: helpers for passing an exception beween interpreters (wraps _Py_excinfo)
* _PyXI_namespace, etc.: helpers for copying a dict of attrs between interpreters
* _PyXI_Enter(), _PyXI_Exit(): functions that abstract out the transitions between one interpreter and a second that will do some work temporarily
Again, these were all abstracted out of _xxsubinterpretersmodule.c as generalizations. I plan on proposing these as public API at some point.
This is partly to clear this stuff out of pystate.c, but also in preparation for moving some code out of _xxsubinterpretersmodule.c. This change also moves this stuff to the internal API (new: Include/internal/pycore_crossinterp.h). @vstinner did this previously and I undid it. Now I'm re-doing it. :/
We do the following:
* add a per-interpreter XID registry (PyInterpreterState.xidregistry)
* put heap types there (keep static types in _PyRuntimeState.xidregistry)
* clear the registries during interpreter/runtime finalization
* avoid duplicate entries in the registry (when _PyCrossInterpreterData_RegisterClass() is called more than once for a type)
* use Py_TYPE() instead of PyObject_Type() in _PyCrossInterpreterData_Lookup()
The per-interpreter registry helps preserve isolation between interpreters. This is important when heap types are registered, which is something we haven't been doing yet but I will likely do soon.
The existence of background threads running on a subinterpreter was preventing interpreters from getting properly destroyed, as well as impacting the ability to run the interpreter again. It also affected how we wait for non-daemon threads to finish.
We add PyInterpreterState.threads.main, with some internal C-API functions.
Kumar Aditya
Tian Gao
Sam Gross
Savannah Ostrowski
Jason Fried
Victor Stinner
Irit Katriel
Ken Jin
Brett Simmers
Eric Snow
mpage
Guido van Rossum
cui fliter
Mark Shannon
Donghee Na
Neil Schemenauer
Michael Droettboom
Pablo Galindo Salgado