[Refactor][NFC] Vendor-in compiler_lock for future CUDA-specific changes #565
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gmarkall
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Oct 31, 2025
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We also need to hold the Numba compiler lock, because we'll likely have a route into Numba somewhere through types and / or the data model that doesn't hold or acquire the Numba compiler lock.
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| self._lock = threading.RLock() | ||
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| def acquire(self): | ||
| ev.start_event("numba.cuda:compiler_lock") |
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We're using numba-cuda: as the prefix for events from Numba-CUDA. See
numba-cuda/numba_cuda/numba/cuda/core/event.py
Lines 58 to 64 in 5aa6b2e
gmarkall
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Nov 3, 2025
| self._numba_lock = numba_lock | ||
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| def acquire(self): | ||
| if self._numba_lock: |
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In what circumstance would this ever be False?
gmarkall
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Nov 3, 2025
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| def require_global_compiler_lock(): | ||
| """Sentry that checks the global_compiler_lock is acquired.""" | ||
| # Use assert to allow turning off this check | ||
| assert global_compiler_lock.is_locked() |
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We don't use this, and it feels a little bit of a dangerous API to me, in that the name sounds like a function that will block until the global compiler lock is held (I'd probably have named it assert_global_compiler_lock() or similar). Can we remove it?
Suggested change
| def require_global_compiler_lock(): | |
| """Sentry that checks the global_compiler_lock is acquired.""" | |
| # Use assert to allow turning off this check | |
| assert global_compiler_lock.is_locked() |
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gmarkall
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Thanks for the updates - I think we should simplify things with a few more changes:
- Remove
require_global_compiler_lock()as suggested on the diff. - This means we can also get rid of the
is_locked()and_is_owned()methods on both kinds of lock, as they will no longer be needed. - The
_DualCompilerLockseems to have no reason to check the truthiness ofself._numba_lock- should it just assume it to be true and remove the conditionals?
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Nov 3, 2025
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- Add support for cache-hinted load and store operations (NVIDIA#587) - Add more thirdparty tests (NVIDIA#586) - Add sphinx-lint to pre-commit and fix errors (NVIDIA#597) - Add DWARF variant part support for polymorphic variables in CUDA debug info (NVIDIA#544) - chore: clean up dead workaround for unavailable `lru_cache` (NVIDIA#598) - chore(docs): format types docs (NVIDIA#596) - refactor: decouple `Context` from `Stream` and `Event` objects (NVIDIA#579) - Fix freezing in of constant arrays with negative strides (NVIDIA#589) - Update tests to accept variants of generated PTX (NVIDIA#585) - refactor: replace device functionality with `cuda.core` APIs (NVIDIA#581) - Move frontend tests to `cudapy` namespace (NVIDIA#558) - Generalize the concurrency group for main merges (NVIDIA#582) - ci: move pre-commit checks to pre commit action (NVIDIA#577) - chore(pixi): set up doc builds; remove most `build-conda` dependencies (NVIDIA#574) - ci: ensure that python version in ci matches matrix (NVIDIA#575) - Fix the `cuda.is_supported_version()` API (NVIDIA#571) - Fix checks on main (NVIDIA#576) - feat: add `math.nextafter` (NVIDIA#543) - ci: replace conda testing with pixi (NVIDIA#554) - [CI] Run PR workflow on merge to main (NVIDIA#572) - Propose Alternative Module Path for `ext_types` and Maintain `numba.cuda.types.bfloat16` Import API (NVIDIA#569) - test: enable fail-on-warn and clean up resulting failures (NVIDIA#529) - [Refactor][NFC] Vendor-in compiler_lock for future CUDA-specific changes (NVIDIA#565) - Fix registration with Numba, vendor MakeFunctionToJITFunction tests (NVIDIA#566) - [Refactor][NFC][Cleanups] Update imports to upstream numba to use the numba.cuda modules (NVIDIA#561) - test: refactor process-based tests to use concurrent futures in order to simplify tests (NVIDIA#550) - test: revert back to ipc futures that await each iteration (NVIDIA#564) - chore(deps): move to self-contained pixi.toml to avoid mixed-pypi-pixi environments (NVIDIA#551) - [Refactor][NFC] Vendor-in errors for future CUDA-specific changes (NVIDIA#534) - Remove dependencies on target_extension for CUDA target (NVIDIA#555) - Relax the pinning to `cuda-core` to allow it floating across minor releases (NVIDIA#559) - [WIP] Port numpy reduction tests to CUDA (NVIDIA#523) - ci: add timeout to avoid blocking the job queue (NVIDIA#556) - Handle `cuda.core.Stream` in driver operations (NVIDIA#401) - feat: add support for `math.exp2` (NVIDIA#541) - Vendor in types and datamodel for CUDA-specific changes (NVIDIA#533) - refactor: cleanup device constructor (NVIDIA#548) - bench: add cupy to array constructor kernel launch benchmarks (NVIDIA#547) - perf: cache dimension computations (NVIDIA#542) - perf: remove duplicated size computation (NVIDIA#537) - chore(perf): add torch to benchmark (NVIDIA#539) - test: speed up ipc tests by ~6.5x (NVIDIA#527) - perf: speed up kernel launch (NVIDIA#510) - perf: remove context threading in various pointer abstractions (NVIDIA#536) - perf: reduce the number of `__cuda_array_interface__` accesses (NVIDIA#538) - refactor: remove unnecessary custom map and set implementations (NVIDIA#530) - [Refactor][NFC] Vendor-in vectorize decorators for future CUDA-specific changes (NVIDIA#513) - test: add benchmarks for kernel launch for reproducibility (NVIDIA#528) - test(pixi): update pixi testing command to work with the new `testing` directory (NVIDIA#522) - refactor: fully remove `USE_NV_BINDING` (NVIDIA#525) - Draft: Vendor in the IR module (NVIDIA#439) - pyproject.toml: add search path for Pyrefly (NVIDIA#524) - Vendor in numba.core.typing for CUDA-specific changes (NVIDIA#473) - Use numba.config when available, otherwise use numba.cuda.config (NVIDIA#497) - [MNT] Drop NUMBA_CUDA_USE_NVIDIA_BINDING; always use cuda.core and cuda.bindings as fallback (NVIDIA#479) - Vendor in dispatcher, entrypoints, pretty_annotate for CUDA-specific changes (NVIDIA#502) - build: allow parallelization of nvcc testing builds (NVIDIA#521) - chore(dev-deps): add pixi (NVIDIA#505) - Vendor the imputils module for CUDA refactoring (NVIDIA#448) - Don't use `MemoryLeakMixin` for tests that don't use NRT (NVIDIA#519) - Switch back to stable cuDF release in thirdparty tests (NVIDIA#518) - Updating .gitignore with binaries in the `testing` folder (NVIDIA#516) - Remove some unnecessary uses of ContextResettingTestCase (NVIDIA#507) - Vendor in _helperlib cext for CUDA-specific changes (NVIDIA#512) - Vendor in typeconv for future CUDA-specific changes (NVIDIA#499) - [Refactor][NFC] Vendor-in numba.cpython modules for future CUDA-specific changes (NVIDIA#493) - [Refactor][NFC] Vendor-in numba.np modules for future CUDA-specific changes (NVIDIA#494) - Make the CUDA target the default for CUDA overload decorators (NVIDIA#511) - Remove C extension loading hacks (NVIDIA#506) - Ensure NUMBA can manipulate memory from CUDA graphs before the graph is launched (NVIDIA#437) - [Refactor][NFC] Vendor-in core Numba analysis utils for CUDA-specific changes (NVIDIA#433) - Fix Bf16 Test OB Error (NVIDIA#509) - Vendor in components from numba.core.runtime for CUDA-specific changes (NVIDIA#498) - [Refactor] Vendor in _dispatcher, _devicearray, mviewbuf C extension for CUDA-specific customization (NVIDIA#373) - [MNT] Managed UM memset fallback and skip CUDA IPC tests on WSL2 (NVIDIA#488) - Improve debug value range coverage (NVIDIA#461) - Add `compile_all` API (NVIDIA#484) - Vendor in core.registry for CUDA-specific changes (NVIDIA#485) - [Refactor][NFC] Vendor in numba.misc for CUDA-specific changes (NVIDIA#457) - Vendor in optional, boxing for CUDA-specific changes, fix dangling imports (NVIDIA#476) - [test] Remove dependency on cpu_target (NVIDIA#490) - Change dangling imports of numba.core.lowering to numba.cuda.lowering (NVIDIA#475) - [test] Use numpy's tolerance for float16 (NVIDIA#491) - [Refactor][NFC] Vendor-in numba.extending for future CUDA-specific changes (NVIDIA#466) - [Refactor][NFC] Vendor-in more cpython registries for future CUDA-specific changes (NVIDIA#478)
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- Add support for cache-hinted load and store operations (#587) - Add more thirdparty tests (#586) - Add sphinx-lint to pre-commit and fix errors (#597) - Add DWARF variant part support for polymorphic variables in CUDA debug info (#544) - chore: clean up dead workaround for unavailable `lru_cache` (#598) - chore(docs): format types docs (#596) - refactor: decouple `Context` from `Stream` and `Event` objects (#579) - Fix freezing in of constant arrays with negative strides (#589) - Update tests to accept variants of generated PTX (#585) - refactor: replace device functionality with `cuda.core` APIs (#581) - Move frontend tests to `cudapy` namespace (#558) - Generalize the concurrency group for main merges (#582) - ci: move pre-commit checks to pre commit action (#577) - chore(pixi): set up doc builds; remove most `build-conda` dependencies (#574) - ci: ensure that python version in ci matches matrix (#575) - Fix the `cuda.is_supported_version()` API (#571) - Fix checks on main (#576) - feat: add `math.nextafter` (#543) - ci: replace conda testing with pixi (#554) - [CI] Run PR workflow on merge to main (#572) - Propose Alternative Module Path for `ext_types` and Maintain `numba.cuda.types.bfloat16` Import API (#569) - test: enable fail-on-warn and clean up resulting failures (#529) - [Refactor][NFC] Vendor-in compiler_lock for future CUDA-specific changes (#565) - Fix registration with Numba, vendor MakeFunctionToJITFunction tests (#566) - [Refactor][NFC][Cleanups] Update imports to upstream numba to use the numba.cuda modules (#561) - test: refactor process-based tests to use concurrent futures in order to simplify tests (#550) - test: revert back to ipc futures that await each iteration (#564) - chore(deps): move to self-contained pixi.toml to avoid mixed-pypi-pixi environments (#551) - [Refactor][NFC] Vendor-in errors for future CUDA-specific changes (#534) - Remove dependencies on target_extension for CUDA target (#555) - Relax the pinning to `cuda-core` to allow it floating across minor releases (#559) - [WIP] Port numpy reduction tests to CUDA (#523) - ci: add timeout to avoid blocking the job queue (#556) - Handle `cuda.core.Stream` in driver operations (#401) - feat: add support for `math.exp2` (#541) - Vendor in types and datamodel for CUDA-specific changes (#533) - refactor: cleanup device constructor (#548) - bench: add cupy to array constructor kernel launch benchmarks (#547) - perf: cache dimension computations (#542) - perf: remove duplicated size computation (#537) - chore(perf): add torch to benchmark (#539) - test: speed up ipc tests by ~6.5x (#527) - perf: speed up kernel launch (#510) - perf: remove context threading in various pointer abstractions (#536) - perf: reduce the number of `__cuda_array_interface__` accesses (#538) - refactor: remove unnecessary custom map and set implementations (#530) - [Refactor][NFC] Vendor-in vectorize decorators for future CUDA-specific changes (#513) - test: add benchmarks for kernel launch for reproducibility (#528) - test(pixi): update pixi testing command to work with the new `testing` directory (#522) - refactor: fully remove `USE_NV_BINDING` (#525) - Draft: Vendor in the IR module (#439) - pyproject.toml: add search path for Pyrefly (#524) - Vendor in numba.core.typing for CUDA-specific changes (#473) - Use numba.config when available, otherwise use numba.cuda.config (#497) - [MNT] Drop NUMBA_CUDA_USE_NVIDIA_BINDING; always use cuda.core and cuda.bindings as fallback (#479) - Vendor in dispatcher, entrypoints, pretty_annotate for CUDA-specific changes (#502) - build: allow parallelization of nvcc testing builds (#521) - chore(dev-deps): add pixi (#505) - Vendor the imputils module for CUDA refactoring (#448) - Don't use `MemoryLeakMixin` for tests that don't use NRT (#519) - Switch back to stable cuDF release in thirdparty tests (#518) - Updating .gitignore with binaries in the `testing` folder (#516) - Remove some unnecessary uses of ContextResettingTestCase (#507) - Vendor in _helperlib cext for CUDA-specific changes (#512) - Vendor in typeconv for future CUDA-specific changes (#499) - [Refactor][NFC] Vendor-in numba.cpython modules for future CUDA-specific changes (#493) - [Refactor][NFC] Vendor-in numba.np modules for future CUDA-specific changes (#494) - Make the CUDA target the default for CUDA overload decorators (#511) - Remove C extension loading hacks (#506) - Ensure NUMBA can manipulate memory from CUDA graphs before the graph is launched (#437) - [Refactor][NFC] Vendor-in core Numba analysis utils for CUDA-specific changes (#433) - Fix Bf16 Test OB Error (#509) - Vendor in components from numba.core.runtime for CUDA-specific changes (#498) - [Refactor] Vendor in _dispatcher, _devicearray, mviewbuf C extension for CUDA-specific customization (#373) - [MNT] Managed UM memset fallback and skip CUDA IPC tests on WSL2 (#488) - Improve debug value range coverage (#461) - Add `compile_all` API (#484) - Vendor in core.registry for CUDA-specific changes (#485) - [Refactor][NFC] Vendor in numba.misc for CUDA-specific changes (#457) - Vendor in optional, boxing for CUDA-specific changes, fix dangling imports (#476) - [test] Remove dependency on cpu_target (#490) - Change dangling imports of numba.core.lowering to numba.cuda.lowering (#475) - [test] Use numpy's tolerance for float16 (#491) - [Refactor][NFC] Vendor-in numba.extending for future CUDA-specific changes (#466) - [Refactor][NFC] Vendor-in more cpython registries for future CUDA-specific changes (#478) <!-- Thank you for contributing to numba-cuda :) Here are some guidelines to help the review process go smoothly. 1. 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This change vendors in the global_compiler_lock that is used to protect the core compiler machinery for future CUDA-specific changes.