Fix #2363: Support using bundled headers with NVRTC 13.3+. - #2753
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* Prepare cuda.core v1.2.0 release Fill remaining user-visible entries in the 1.2.0 release notes and add 1.1.1 and 1.2.0 to the docs version switcher. Version is derived from the git tag via setuptools-scm, so no pyproject.toml bump is needed. New features documented: - ProgramOptions.use_bundled_headers for NVRTC 13.3+ (#2753 closes #2363) - cuda-gdb source display for JIT-compiled kernels (#2678, #2679) Fixes and enhancements documented: - PinnedMemoryResource host-pool validation at construction (#2487) - is_host_accessible for NUMA-located VMM (#2503) - Graph predecessor/successor query truncation on large graphs (#2587) - Per-domain NVML clock queries treated as independently optional (#2651) - Temperature threshold checks forward-compat with unknown archs (#2488) - import cuda.core non-integer opt-out crash (#2535) - Frozen CUresult explanation table refreshed for CUDA 13.3 (#2383) -- Leo's bot * Update cuda_core/docs/source/release/1.2.0-notes.rst Co-authored-by: Michael Droettboom <[email protected]> --------- Co-authored-by: Michael Droettboom <[email protected]>
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This adds support for using bundled headers, as provided in NVRTC 13.3.
This sidesteps a lot of the complexity of what #2363 suggested by just using the
--use-bundled-headerscommandline argument, rather than making API calls directly. It handles updating to a new version (only when necessary) and adding the installed-header location to the include paths appropriately, so we don't have to re-invent those wheels.This always uses a user-global cache directory (following the platform-specific conventions for those). There is a small refactor here to pull out the logic for that that already existed for
program_cacheinto a general utility that this and theprogram_cacheboth use.