If a thread blocks while waiting on the `shared->mutex` lock, the array
of QSBR states may be reallocated. The `tstate->qsbr` values before the
lock is acquired may not be the same as the value after the lock is acquired.
This implements the delayed reuse of mimalloc pages that contain Python
objects in the free-threaded build.
Allocations of the same size class are grouped in data structures called
pages. These are different from operating system pages. For thread-safety, we
want to ensure that memory used to store PyObjects remains valid as long as
there may be concurrent lock-free readers; we want to delay using it for
other size classes, in other heaps, or returning it to the operating system.
When a mimalloc page becomes empty, instead of immediately freeing it, we tag
it with a QSBR goal and insert it into a per-thread state linked list of
pages to be freed. When mimalloc needs a fresh page, we process the queue and
free any still empty pages that are now deemed safe to be freed. Pages
waiting to be freed are still available for allocations of the same size
class and allocating from a page prevent it from being freed. There is
additional logic to handle abandoned pages when threads exit.
A previous commit introduced a bug to `interpreter_clear()`: it set
`interp->ceval.instrumentation_version` to 0, without making the corresponding
change to `tstate->eval_breaker` (which holds a thread-local copy of the
version). After this happens, Python code can still run due to object finalizers
during a GC, and the version check in bytecodes.c will see a different result
than the one in instrumentation.c causing an infinite loop.
The fix itself is straightforward: clear `tstate->eval_breaker` when clearing
`interp->ceval.instrumentation_version`.
Make `_thread.ThreadHandle` thread-safe in free-threaded builds
We protect the mutable state of `ThreadHandle` using a `_PyOnceFlag`.
Concurrent operations (i.e. `join` or `detach`) on `ThreadHandle` block
until it is their turn to execute or an earlier operation succeeds.
Once an operation has been applied successfully all future operations
complete immediately.
The `join()` method is now idempotent. It may be called multiple times
but the underlying OS thread will only be joined once. After `join()`
succeeds, any future calls to `join()` will succeed immediately.
The internal thread handle `detach()` method has been removed.
This changes the `sym_set_...()` functions to return a `bool` which is `false`
when the symbol is `bottom` after the operation.
All calls to such functions now check this result and go to `hit_bottom`,
a special error label that prints a different message and then reports
that it wasn't able to optimize the trace. No executor will be produced
in this case.
This undoes the *temporary* default disabling of the T2 optimizer pass in gh-115860.
- Add a new test that reproduces Brandt's example from gh-115859; it indeed crashes before gh-116028 with PYTHONUOPSOPTIMIZE=1
- Re-enable the optimizer pass in T2, stop checking PYTHONUOPSOPTIMIZE
- Rename the env var to disable T2 entirely to PYTHON_UOPS_OPTIMIZE (must be explicitly set to 0 to disable)
- Fix skipIf conditions on tests in test_opt.py accordingly
- Export sym_is_bottom() (for debugging)
- Fix various things in the `_BINARY_OP_` specializations in the abstract interpreter:
- DECREF(temp)
- out-of-space check after sym_new_const()
- add sym_matches_type() checks, so even if we somehow reach a binary op with symbolic constants of the wrong type on the stack we won't trigger the type assert
- Any `sym_set_...` call that attempts to set conflicting information
cause the symbol to become `bottom` (contradiction).
- All `sym_is...` and similar calls return false or NULL for `bottom`.
- Everything's tested.
- The tests still pass with `PYTHONUOPSOPTIMIZE=1`.
* Rename _Py_UOpsAbstractInterpContext to _Py_UOpsContext and _Py_UOpsSymType to _Py_UopsSymbol.
* #define shortened form of _Py_uop_... names for improved readability.
The theory is that even if we saw a jump go in the same direction the
last 16 times we got there, we shouldn't be overly confident that it's
still going to go the same way in the future. This PR makes it so that
in the extreme cases, the confidence is multiplied by 0.9 instead of
remaining unchanged. For unpredictable jumps, there is no difference
(still 0.5). For somewhat predictable jumps, we interpolate.
