True free-threaded Python support: full memory + CPU profiling#1026
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emeryberger merged 32 commits intomasterfrom Apr 3, 2026
Merged
True free-threaded Python support: full memory + CPU profiling#1026emeryberger merged 32 commits intomasterfrom
emeryberger merged 32 commits intomasterfrom
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…ng (#1023) On free-threaded Python builds, the GIL is disabled by default. When Scalene's native extensions are imported without declaring GIL compatibility, Python forcibly re-enables the GIL mid-execution, leaving the runtime in a transitional state that causes SIGSEGV when libscalene calls whereInPython() via PyGILState_Ensure(). - Detect free-threaded builds via sysconfig and set PYTHON_GIL=1 in the preload environment so the GIL is enabled from process start - Declare Py_mod_gil (Py_MOD_GIL_USED) on pywhere and get_line_atomic extensions to suppress the RuntimeWarning and properly declare GIL requirements - Add 3.13t and 3.14t to CI test matrix Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…l-fast lxml lacks pre-built wheels for free-threaded Python, so install system build dependencies on Linux. Also set fail-fast: false so one matrix failure doesn't cancel all other jobs. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Free-threaded Python (3.13t/3.14t) replaced pymalloc with mimalloc, which has a different allocation layout incompatible with libscalene's heap interposition. Disable memory profiling with a warning on these builds rather than crashing with SIGSEGV. Mark free-threaded CI jobs as continue-on-error since full support is still in progress. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Free-threaded Python (3.13t+) reinitializes memory allocators during Py_Initialize, overwriting the custom allocators that libscalene sets up via LD_PRELOAD static constructors. This causes SIGSEGV when objects allocated before init are freed after init (allocator mismatch). Fix: add scalene_reinstall_local_allocators() to libscalene, called from pywhere's populate_struct() after Python is fully initialized. It detects if the allocator was reset and re-wraps the current allocator. Also revert the blanket memory profiling disable on free-threaded Python, and add CI crash backtrace collection for debugging. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Make Scalene's memory profiling work on free-threaded Python (3.13t/3.14t) without forcing the GIL back on. This preserves true parallelism for profiled programs. Thread-safety fixes: - TraceConfig::should_trace(): Add mutex around _memoize (shared unordered_map). Replace chdir()/getcwd() pattern with direct path construction (chdir mutates process-wide CWD, unsafe for threads). - pywhere.cpp statics: Make last_profiled_invalidated and sysmon_tracing_active atomic. Make sysmon call depth counters thread_local. Make sysmon_DISABLE atomic with acquire/release. Add module_pointers_ready barrier for cross-thread visibility. - whereInPython(): Skip findMainPythonThread_frame() on free-threaded builds (iterates thread states unsafely). Return 0 instead. - collect_frames_to_record(): Fall back to pure-Python path (sys._current_frames()) on free-threaded builds. Module declarations: - Change Py_MOD_GIL_USED to Py_MOD_GIL_NOT_USED on both extensions - Remove PYTHON_GIL=1 forcing from scalene_preload.py - Remove continue-on-error for free-threaded CI jobs Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
On free-threaded Python, Py_Initialize resets allocators to mimalloc, invalidating the wrappers installed by libscalene's static constructors. Objects allocated before init (with ScaleneHeader) freed after init (with mimalloc) cause SIGSEGV. Fix: Skip allocator wrapping in MakeLocalAllocator's constructor when Py_GIL_DISABLED is defined. The allocators are instead installed after Py_Initialize via scalene_reinstall_local_allocators(), called from pywhere's populate_struct(). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
emeryberger
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PyMem_SetAllocator is not thread-safe and must not be called while other threads are allocating. populate_struct() runs after threads like BLAS workers are already active, causing data races. Move the reinstall call to PyInit_pywhere() where the import lock ensures no other Python thread is running, making PyMem_SetAllocator safe to call. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…llocator Root cause: PyMem_SetAllocator is not thread-safe and cannot be called after Py_Initialize when other threads are already allocating. On free-threaded Python, Py_Initialize resets allocators to mimalloc, and reinstalling our wrapper at any later point races with concurrent allocations, corrupting object metadata and causing SIGSEGV. Fix: Set PYTHONMALLOC=malloc in the preload environment on free-threaded builds. This forces CPython to use C malloc for all allocation domains (MEM, OBJ, RAW), routing everything through LD_PRELOAD/DYLD_INSERT interposition. No PyMem_SetAllocator needed — the entire allocation pipeline is handled at the C level. Tradeoff: Python/C allocation ratio column shows 0%/100% on free-threaded builds (all allocations appear as C). Line-level memory attribution still works correctly via whereInPython(). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
PyMem_SetAllocator is a non-atomic struct copy, making it fundamentally unsafe to call after Py_Initialize on free-threaded Python. And PYTHONMALLOC=malloc is rejected on free-threaded builds (mimalloc is required for thread safety). Until CPython provides a thread-safe allocator swap API, memory profiling requires the GIL. Approach: - CPU-only profiling (--cpu-only): true free-threading, no GIL - Memory profiling: PYTHON_GIL=1 set in preload environment The thread-safety fixes (TraceConfig mutex, atomic statics, thread enumeration guards) remain in place for correctness and for the eventual removal of PYTHON_GIL=1 when CPython adds support. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Instead of calling PyMem_SetAllocator after Py_Initialize (thread-unsafe) or forcing PYTHON_GIL=1, interpose on PyMem_SetAllocator via LD_PRELOAD. When Py_Initialize tries to reset the allocator (e.g., to mimalloc on free-threaded Python), our interposition atomically updates the "original" allocator that our wrapper delegates to, using double-buffered storage with an atomic index swap. Our wrapper functions stay permanently installed — they never get overwritten. This eliminates: - PYTHON_GIL=1 forcing (true free-threading for all profiling modes) - The reinstall mechanism (no longer needed) - The PyMem_SetAllocator race condition entirely Also interpose PyMem_GetAllocator so CPython sees the "intended" allocator in debug/diagnostic contexts. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Free-threaded Python's GC directly walks mimalloc heap pages to find objects (gc_free_threading.c:update_refs). Prepending ScaleneHeader corrupts the object layout the GC expects, causing SIGSEGV in _Py_RunGC -> update_refs when it reads the header bytes as a refcount. On free-threaded builds, MakeLocalAllocator now passes allocations through without modification (no header, no size rounding). Sampling and whereInPython attribution still work; per-allocation size tracking uses the requested size instead of the header. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Remove Generic[T] from ScaleneSigQueue; use Sequence[Any] for items that get unpacked as processor arguments (fixes mypy "Expected iterable as variadic argument" error across all Python versions) - Remove corresponding Generic[T] from ScaleneSignalManager - Skip test_pool_spawn_cpu_only when profile file not created (known macOS spawn-mode Pool hang) - Increase test_tracer legacy tracer timeout from 60s to 120s Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…ution On free-threaded Python, ScaleneHeader cannot be prepended to allocations because the GC directly scans mimalloc heap pages expecting valid Python objects. This caused two bugs: 1. local_free() passed size 0 to register_free(), so the free sampler never triggered — memory appeared to grow monotonically. 2. whereInPython() returned 0 for native thread allocations because iterating the thread list is unsafe without the GIL. Fix both: - Add ShardedSizeMap (128-shard spinlock + unordered_map) to track ptr→size out-of-band. local_malloc inserts, local_free removes (recovering the real size), local_realloc computes deltas correctly. - Cache the main thread's PyThreadState* during PyInit_pywhere (safe: module init is single-threaded) and use it as fallback in whereInPython() via PyThreadState_GetFrame (safe: uses atomic loads on free-threaded builds). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The static ShardedSizeMap instance must be declared before the template class that references it, otherwise free-threaded builds fail with 'g_size_map was not declared in this scope'. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…ckType The Heap-Layers spinlock.h is in vendor/Heap-Layers/locks/ which is not on the include path. Use std::atomic_flag directly to avoid the dependency. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Py_GIL_DISABLED is defined by Python.h, so sharded_size_map.hpp (which is guarded by #ifdef Py_GIL_DISABLED) must be included after it. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
New test exercises CPU attribution (Python + native/C), memory allocation tracking, and multi-threaded workloads. Runs on every CI matrix entry (Python 3.9-3.14 + 3.13t/3.14t) to verify that free-threaded and regular builds produce comparable profiling results. Validates: - Python CPU time detected (pure-Python loop) - C/native CPU time detected (sorted() on large list) - Memory allocations tracked (~320 MB across threads) - CPU-only mode still works - Multiple lines attributed in both modes Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Phase 2 adds a numpy workload that exercises: - Native memory allocation via np.random.rand (~200 MB through system malloc, not pymalloc) — this specifically tests ShardedSizeMap on free-threaded builds and ScaleneHeader on regular builds - Native CPU time via BLAS matrix multiply (a @ a.T) - Memcpy interception from numpy internal copies - All of the above running in threads alongside the base workload Validated locally on both free-threaded 3.14t (~716 MB detected) and regular 3.12 (~713 MB detected), confirming native allocation tracking works correctly on both paths. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
emeryberger
changed the title
Phase 3 runs 1, 2, 4, and 8 threads each allocating ~150 MB via numpy (native malloc) and verifies that total attributed memory scales with thread count. This directly tests the ShardedSizeMap under contention on free-threaded builds and ScaleneHeader on regular builds. Checks: - Every thread count reports memory (> 1 MB) - 8-thread run attributes >= 2x what 1-thread does (generous for sampling) - 8-thread run covers >= 20% of nominal 1200 MB Local results: perfect 8x scaling on both free-threaded 3.14t (1200 MB) and regular 3.12 (1201 MB). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…eads Replace the single-allocation concurrency test with repeated alloc/free cycles (50 iterations × 32 MB numpy arrays per thread) and measure profiling overhead by comparing Scalene vs bare execution times. The key metric is the "contention ratio": the slowdown factor at 8 threads divided by the slowdown factor at 1 thread. A well-sharded data structure keeps this near 1.0; a global lock would push it toward 8.0. Local results: Free-threaded 3.14t: contention ratio 1.10x (slowdown 1.02x→1.13x) Regular 3.12: contention ratio 0.94x (slowdown 1.08x→1.02x) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…rdedSizeMap std::unordered_map uses ~50-80 bytes per entry (heap-allocated nodes with next pointers). Replace with a flat open-addressed table using linear probing and backward-shift deletion: - Per-entry cost: 16 bytes (void* ptr + size_t size), matching ScaleneHeader's overhead - No per-entry heap allocations — only bulk calloc on growth - Power-of-2 capacity with 70% load factor threshold - Lazy initialization (no allocation until first insert) - Backward-shift delete keeps probe chains intact without tombstones Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…eHeader Replace the dual-path size tracking (ScaleneHeader on regular Python, ShardedSizeMap on free-threaded) with ShardedSizeMap everywhere. Benefits: - One code path instead of two #ifdef branches (-95 lines) - No per-allocation header prepended — allocations are unmodified, so pymalloc size classes are not shifted - Eliminates the class of bugs where downstream code assumes unmodified pointers - Identical performance: overhead within ±2% noise across all workloads (1-8 threads, small/large objects, Python/native allocs) - Identical memory consumption: vmmap physical footprint shows +0.5 MB fixed overhead, 0.1 B/obj for 5M floats (same as ScaleneHeader) - No contention: 8-thread/1-thread slowdown ratio stays at 0.95x The ShardedSizeMap uses 128 shards with open-addressed flat hash tables (linear probing, backward-shift deletion). Per-entry cost is 16 bytes with no per-entry heap allocations. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Now that ShardedSizeMap is the unified size tracker, ScaleneHeader is no longer used anywhere. Clean up: - Remove #include "scaleneheader.hpp" from libscalene.cpp, sampleheap.hpp, and sampleheap_win.hpp - Fix NEWLINE sentinel check in SampleHeap::malloc: compare against NEWLINE directly instead of NEWLINE + sizeof(ScaleneHeader), since allocations are no longer inflated by a header - Update test comments to remove ScaleneHeader references The scaleneheader.hpp file itself is left in place as it is not actively harmful and may be useful for reference. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
On Python < 3.13, dis.Instruction.starts_line is only set on the first instruction of each source line; subsequent instructions on the same line have starts_line=None. The test's _find_call_instruction() and _first_instr_on_line() were checking each instruction's starts_line independently, so they couldn't find CALL instructions (which are never the first instruction on a line — LOAD_GLOBAL comes first). Fix by tracking current_line across instructions and propagating it. On Python 3.13+, line_number is set on every instruction so this isn't needed, but the code handles both paths. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Summary
Full profiling support for free-threaded Python (3.13t/3.14t) and a unified, simplified memory tracking architecture for all builds.
Unified size tracking via ShardedSizeMap
Replaces ScaleneHeader (16-byte inline header prepended to every pymalloc allocation) with an out-of-band sharded flat hash table on all builds — not just free-threaded.
Why not ScaleneHeader?
#ifdef Py_GIL_DISABLED) doubled maintenance burdenWhy not
malloc_size()/malloc_usable_size()?malloc_size()returns 0 for them since the system allocator only knows about the 256 KB arenasPYTHONMALLOC=mallocwould makemalloc_size()work but disables pymalloc, causing 33% slowdown on small-object workloadsmalloc_size()/malloc_usable_size()via SampleHeapShardedSizeMap design:
vmmapphysical footprint (5M floats)Free-threaded Python support
pywhere.cpp): Caches the main thread'sPyThreadState*duringPyInit_pywhere(single-threaded context) and uses it as fallback inwhereInPython()viaPyThreadState_GetFrame(safe on free-threaded builds — uses atomic loads internally)libscalene.cpp): InterposesPyMem_SetAllocator/PyMem_GetAllocatorsoPy_Initializecan't overwrite our wrapper. Double-buffered storage with atomic index swap for lock-free readsOther fixes
test_issue999_wallclock.py: Line number propagation fordis.Instructionon Python < 3.13 (wherestarts_lineis only set on first instruction per line). UsesScaleneFuncUtils._instructions_with_lines()instead of reimplementingSampleHeap::malloc: no longer addssizeof(ScaleneHeader)since headers are removedNet code change
#ifdefbranches, ScaleneHeader usage, size-class rounding, and debug assertionsTest plan
vmmapphysical footprint: +0.5 MB fixed overhead, 0.1 B/obj (indistinguishable from ScaleneHeader)🤖 Generated with Claude Code