Locate nvvm, libdevice, nvrtc, and cudart from nvidia-*-cu12 wheels #155
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kkraus14
reviewed
Mar 11, 2025
gmarkall
reviewed
Mar 13, 2025
gmarkall
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Mar 13, 2025
gmarkall
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Mar 13, 2025
gmarkall
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Mar 13, 2025
gmarkall
reviewed
Mar 13, 2025
gmarkall
requested changes
Mar 13, 2025
gmarkall
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Yes, I'll see about adding a separate CI job for this |
ci/test_wheel_deps_wheels.sh
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| # remove cuda-nvvm-12-5 leaving libnvvm.so from nvidia-cuda-nvcc-cu12 only | ||
| apt-get update | ||
| apt remove --purge cuda-nvvm-12-5 -y |
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This combined with the addition of nvidia-cuda-nvcc-cu12 was the easiest way I could think of to get to the relevant test environment, but I'm by no means married to it, this would have to be dynamic wrt the minor version as well.
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You can get the installed package name with something like
CUDA_NVVM_PACKAGE=`dpkg --get-selections | grep cuda-nvvm | awk '{print $1}'`
gmarkall
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rwgk
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Mar 19, 2025
rwgk
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Mar 19, 2025
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I've merged this branch with main (fbbc040) and tested on But can't get rid of I'm getting the error: Context: |
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Hi @ZzEeKkAa , there's a couple pieces of this that are still WIP, I think you'll probably run into bugs right now. I'm working this PR over the next few days so hopefully some more updates soon. |
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@brandon-b-miller Suggested change to PR title: -Locate nvvm, libdevice and nvrtc from nvidia-cuda-nvcc-cu12 wheels
+Locate nvvm, libdevice and nvrtc from nvidia-*-cu12 wheelsBecause:
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rwgk
reviewed
Apr 17, 2025
numba_cuda/numba/cuda/cuda_paths.py
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| try: | ||
| return SEARCH_PRIORITY.index(label) | ||
| except ValueError: | ||
| return float("inf") |
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This can easily mask bugs that are troublesome to track down (e.g. surprising behavior if there is a typo in the label, or a new label is introduced elsewhere without updating SEARCH_PRIORITY). — I realize this PR is meant to be a stop-gap. Just pointing out. Generally, I'd try to not use such a brittle approach. If there is an easy way to avoid this, that'd be better.
E.g., what happens if you simply remove the try-except? Do all tests pass?
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This is a great observation, what do you think of the changes in 8cc37d7 ?
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The CI runs are still finding the runtime from the system installation: https://github.com/NVIDIA/numba-cuda/actions/runs/14518427298/job/40733627061?pr=155 The nvidia-cuda-runtime-cu12 wheel also needs installing in the test script, I think. |
gmarkall
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Apr 17, 2025
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The following changes lead to success on Windows:
diff --git a/numba_cuda/numba/cuda/cuda_paths.py b/numba_cuda/numba/cuda/cuda_paths.py
index 9b38a86..bc3822a 100644
--- a/numba_cuda/numba/cuda/cuda_paths.py
+++ b/numba_cuda/numba/cuda/cuda_paths.py
@@ -224,8 +224,9 @@ def _cuda_home_static_cudalib_path():
def _get_cudalib_wheel():
"""Get the cudalib path from the NVCC wheel."""
site_paths = [site.getusersitepackages()] + site.getsitepackages()
+ libdir = IS_LINUX and "lib" or "bin"
for sp in filter(None, site_paths):
- cudalib_path = Path(sp, "nvidia", "cuda_runtime", "lib")
+ cudalib_path = Path(sp, "nvidia", "cuda_runtime", libdir)
if cudalib_path.exists():
return str(cudalib_path)
return None
@@ -373,8 +374,20 @@ def get_cuda_home(*subdirs):
def _get_nvvm_path():
by, path = _get_nvvm_path_decision()
+
if by == "NVIDIA NVCC Wheel":
- path = os.path.join(path, "libnvvm.so")
+ platform_map = {
+ "linux": "libnvvm.so",
+ "win32": "nvvm64_40_0.dll",
+ }
+
+ for plat, dso_name in platform_map.items():
+ if sys.platform.startswith(plat):
+ break
+ else:
+ raise NotImplementedError("Unsupported platform")
+
+ path = os.path.join(path, dso_name)
else:
candidates = find_lib("nvvm", path)
path = max(candidates) if candidates else NoneLibrary test output:
(test-cuda-wheels) PS C:\Users\gmarkall\numbadev\numba-cuda> python -c "from numba import cuda; cuda.cudadrv.libs.test()"
Finding driver from candidates:
nvcuda.dll
\windows\system32\nvcuda.dll
Using loader <class 'ctypes.WinDLL'>
Trying to load driver... ok
Loaded from nvcuda.dll
Finding nvvm from NVIDIA NVCC Wheel
Located at D:\miniforge\envs\test-cuda-wheels\Lib\site-packages\nvidia\cuda_nvcc\nvvm\bin\nvvm64_40_0.dll
Trying to open library... ok
Finding nvrtc from NVIDIA NVCC Wheel
Located at D:\miniforge\envs\test-cuda-wheels\Lib\site-packages\nvidia\cuda_nvrtc\bin\nvrtc64_120_0.dll
Trying to open library... ok
Finding cudart from NVIDIA NVCC Wheel
Located at D:\miniforge\envs\test-cuda-wheels\Lib\site-packages\nvidia\cuda_runtime\bin\cudart64_12.dll
Trying to open library... ok
Finding cudadevrt from <unknown>
Located at cudadevrt.lib
Checking library... ERROR: failed to find cudadevrt:
cudadevrt.lib not found
Finding libdevice from NVIDIA NVCC Wheel
Located at D:\miniforge\envs\test-cuda-wheels\Lib\site-packages\nvidia\cuda_nvcc\nvvm\libdevice\libdevice.10.bc
Checking library... ok
Include directory configuration variable:
CUDA_INCLUDE_PATH=cuda_include_not_found
Finding include directory from CUDA_INCLUDE_PATH Config Entry
Located at cuda_include_not_found
Checking include directory... ERROR: failed to find cuda include directory:
We will just have to ignore that the includes and cudadevrt don't seem to be available in wheels, though.
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patch added in d5b68a9
brandon-b-miller
changed the title
nvvm, libdevice and nvrtc from nvidia-cuda-nvcc-cu12 wheels
brandon-b-miller
changed the title
This has been updated, now I see |
rwgk
approved these changes
Apr 17, 2025
numba_cuda/numba/cuda/cuda_paths.py
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| cu_ver = "11.2" if not IS_WIN32 else "112" | ||
| elif major == 12: | ||
| cu_ver = "12" if not IS_WIN32 else "120" | ||
| else: | ||
| raise NotImplementedError(f"CUDA {major} is not supported") | ||
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| return os.path.join( | ||
| lib_dir, | ||
| f"libnvrtc.so.{cu_ver}" | ||
| if not IS_WIN32 |
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To make this neat, I'd flip these around, e.g. cu_ver = "112" if IS_WIN32 else "11.2"
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I think the logic here is not for cuveralone, but for the OS-dependent DSO name.
numba_cuda/numba/cuda/cuda_paths.py
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| def _get_cudalib_wheel(): | ||
| """Get the cudalib path from the NVCC wheel.""" | ||
| site_paths = [site.getusersitepackages()] + site.getsitepackages() | ||
| libdir = not IS_WIN32 and "lib" or "bin" |
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This one too (libdir = "bin" if IS_WIN32 else "lib")
(What you have right now is a real brain teaser!)
gmarkall
approved these changes
Apr 17, 2025
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As of the latest commit, dfe25c8, this is still working for me for both Conda packages and pip wheels on Windows and Linux.
I think the only caveat is that cudadevrt.lib and the headers are not pip-installable, but that's not an issue we can solve inside this PR and that shouldn't block it.
leofang
reviewed
Apr 17, 2025
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| "Conda environment", | ||
| "Conda environment (NVIDIA package)", |
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Leaving a note here, no action needed for this PR.
I understand this is just a refactoring of existing code, but still having this distinction (conda-forge/nvidia) is a bit nerve wrecking, especially after CUDA 12.0 where both channels started unifying the layouts (different from cudatoolkit from 11.x and before) and eventually became interchangeable around 12.5. cc @jakirkham for comments.
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This distinction is here because there's a distinction in the packages though - we can't unify it here because it's not unified in the wider landscape of CUDA toolkit conda packaging.
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I assume you're referring to the layout differences between CUDA 11/12?
leofang
approved these changes
Apr 17, 2025
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@brandon-b-miller looks like there's a couple of comments from @rwgk and then this is ready to merge? |
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I've just run tests on And everything works good so far, thank you! |
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Apr 22, 2025
- Locate nvvm, libdevice, nvrtc, and cudart from nvidia-*-cu12 wheels (NVIDIA#155) - reinstate test (NVIDIA#226) - Restore PR NVIDIA#185 (Stop Certain Driver API Discovery for "v2") (NVIDIA#223) - Report NVRTC builtin operation failures to the user (NVIDIA#196) - Add Module Setup and Teardown Callback to Linkable Code Interface (NVIDIA#145) - Test CUDA 12.8. (NVIDIA#187) - Ensure RTC Bindings Clamp to the Maximum Supported CC (NVIDIA#189) - Migrate code style to ruff (NVIDIA#170) - Use less GPU memory in test_managed_alloc_driver_undersubscribe. (NVIDIA#188) - Update workflows to always use proxy cache. (NVIDIA#191)
Merged
gmarkall
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- Locate nvvm, libdevice, nvrtc, and cudart from nvidia-*-cu12 wheels (#155) - reinstate test (#226) - Restore PR #185 (Stop Certain Driver API Discovery for "v2") (#223) - Report NVRTC builtin operation failures to the user (#196) - Add Module Setup and Teardown Callback to Linkable Code Interface (#145) - Test CUDA 12.8. (#187) - Ensure RTC Bindings Clamp to the Maximum Supported CC (#189) - Migrate code style to ruff (#170) - Use less GPU memory in test_managed_alloc_driver_undersubscribe. (#188) - Update workflows to always use proxy cache. (#191)
leofang
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May 6, 2025
* First version of `cuda.bindings.path_finder` (#447) * Unmodified copies of: * https://github.com/NVIDIA/numba-cuda/blob/bf487d78a40eea87f009d636882a5000a7524c95/numba_cuda/numba/cuda/cuda_paths.py * https://github.com/numba/numba/blob/f0d24824fcd6a454827e3c108882395d00befc04/numba/misc/findlib.py * Add Forked from URLs. * Strip down cuda_paths.py to minimum required for `_get_nvvm_path()` Tested interactively with: ``` import cuda_paths nvvm_path = cuda_paths._get_nvvm_path() print(f"{nvvm_path=}") ``` * ruff auto-fixes (NO manual changes) * Make `get_nvvm_path()` a pubic API (i.e. remove leading underscore). * Fetch numba-cuda/numba_cuda/numba/cuda/cuda_paths.py from NVIDIA/numba-cuda#155 AS-IS * ruff format NO MANUAL CHANGES * Minimal changes to adapt numba-cuda/numba_cuda/numba/cuda/cuda_paths.py from NVIDIA/numba-cuda#155 * Rename ecosystem/cuda_paths.py -> path_finder.py * Plug cuda.bindings.path_finder into cuda/bindings/_internal/nvvm_linux.pyx * Plug cuda.bindings.path_finder into cuda/bindings/_internal/nvjitlink_linux.pyx * Fix `os.path.exists(None)` issue: ``` ______________________ ERROR collecting test_nvjitlink.py ______________________ tests/test_nvjitlink.py:62: in <module> not check_nvjitlink_usable(), reason="nvJitLink not usable, maybe not installed or too old (<12.3)" tests/test_nvjitlink.py:58: in check_nvjitlink_usable return inner_nvjitlink._inspect_function_pointer("__nvJitLinkVersion") != 0 cuda/bindings/_internal/nvjitlink.pyx:257: in cuda.bindings._internal.nvjitlink._inspect_function_pointer ??? cuda/bindings/_internal/nvjitlink.pyx:260: in cuda.bindings._internal.nvjitlink._inspect_function_pointer ??? cuda/bindings/_internal/nvjitlink.pyx:208: in cuda.bindings._internal.nvjitlink._inspect_function_pointers ??? cuda/bindings/_internal/nvjitlink.pyx:102: in cuda.bindings._internal.nvjitlink._check_or_init_nvjitlink ??? cuda/bindings/_internal/nvjitlink.pyx:59: in cuda.bindings._internal.nvjitlink.load_library ??? /opt/hostedtoolcache/Python/3.13.2/x64/lib/python3.13/site-packages/cuda/bindings/path_finder.py:312: in get_cuda_paths "nvvm": _get_nvvm_path(), /opt/hostedtoolcache/Python/3.13.2/x64/lib/python3.13/site-packages/cuda/bindings/path_finder.py:285: in _get_nvvm_path by, path = _get_nvvm_path_decision() /opt/hostedtoolcache/Python/3.13.2/x64/lib/python3.13/site-packages/cuda/bindings/path_finder.py:96: in _get_nvvm_path_decision if os.path.exists(nvvm_ctk_dir): <frozen genericpath>:19: in exists ??? E TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType ``` * Fix another `os.path.exists(None)` issue: ``` ______________________ ERROR collecting test_nvjitlink.py ______________________ tests/test_nvjitlink.py:62: in <module> not check_nvjitlink_usable(), reason="nvJitLink not usable, maybe not installed or too old (<12.3)" tests/test_nvjitlink.py:58: in check_nvjitlink_usable return inner_nvjitlink._inspect_function_pointer("__nvJitLinkVersion") != 0 cuda/bindings/_internal/nvjitlink.pyx:257: in cuda.bindings._internal.nvjitlink._inspect_function_pointer ??? cuda/bindings/_internal/nvjitlink.pyx:260: in cuda.bindings._internal.nvjitlink._inspect_function_pointer ??? cuda/bindings/_internal/nvjitlink.pyx:208: in cuda.bindings._internal.nvjitlink._inspect_function_pointers ??? cuda/bindings/_internal/nvjitlink.pyx:102: in cuda.bindings._internal.nvjitlink._check_or_init_nvjitlink ??? cuda/bindings/_internal/nvjitlink.pyx:59: in cuda.bindings._internal.nvjitlink.load_library ??? /opt/hostedtoolcache/Python/3.13.2/x64/lib/python3.13/site-packages/cuda/bindings/path_finder.py:313: in get_cuda_paths "libdevice": _get_libdevice_paths(), /opt/hostedtoolcache/Python/3.13.2/x64/lib/python3.13/site-packages/cuda/bindings/path_finder.py:126: in _get_libdevice_paths by, libdir = _get_libdevice_path_decision() /opt/hostedtoolcache/Python/3.13.2/x64/lib/python3.13/site-packages/cuda/bindings/path_finder.py:73: in _get_libdevice_path_decision if os.path.exists(libdevice_ctk_dir): <frozen genericpath>:19: in exists ??? E TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType ``` * Change "/lib64/" → "/lib/" in nvjitlink_linux.pyx * nvjitlink_linux.pyx load_library() enhancements, mainly to avoid os.path.join(None, "libnvJitLink.so") * Add missing f-string f * Add back get_nvjitlink_dso_version_suffix() call. * pytest -ra -s -v * Rewrite nvjitlink_linux.pyx load_library() to produce detailed error messages. * Attach listdir output to "Unable to load" exception message. * Guard os.listdir() call with os.path.isdir() * Fix logic error in nvjitlink_linux.pyx load_library() * Move path_finder.py to _path_finder_utils/cuda_paths.py, import only public functions from new path_finder.py * Add find_nvidia_dynamic_library() and use from nvjitlink_linux.pyx, nvvm_linux.pyx * Fix oversight in _find_using_lib_dir() * Also look for versioned library in _find_using_nvidia_lib_dirs() * glob.glob() Python 3.9 compatibility * Reduce build-and-test.yml to Windows-only, Python 3.12 only. * Comment out `if: ${{ github.repository_owner == nvidia }}` * Revert "Comment out `if: ${{ github.repository_owner == nvidia }}`" This reverts commit b0db24f. * Add back `linux-64` `host-platform` * Rewrite load_library() in nvjitlink_windows.pyx to use path_finder.find_nvidia_dynamic_library() * Revert "Rewrite load_library() in nvjitlink_windows.pyx to use path_finder.find_nvidia_dynamic_library()" This reverts commit 1bb7151. * Add _inspect_environment() in find_nvidia_dynamic_library.py, call from nvjitlink_windows.pyx, nvvm_windows.pyx * Add & use _find_dll_using_nvidia_bin_dirs(), _find_dll_using_cudalib_dir() * Fix silly oversight: forgot to undo experimental change. * Also reduce test test-linux matrix. * Reimplement load_library() functions in nvjitlink_windows.pyx, nvvm_windows.pyx to actively use path_finder.find_nvidia_dynamic_library() * Factor out load_nvidia_dynamic_library() from _internal/nvjitlink_linux.pyx, nvvm_linux.pyx * Generalize load_nvidia_dynamic_library.py to also work under Windows. * Add `void*` return type to load_library() implementations in _internal/nvjitlink_windows.pyx, nvvm_windows.pyx * Resolve cython error: object handle vs `void*` handle ``` Error compiling Cython file: ------------------------------------------------------------ ... err = (<int (*)(int*) nogil>__cuDriverGetVersion)(&driver_ver) if err != 0: raise RuntimeError('something went wrong') # Load library handle = load_library(driver_ver) ^ ------------------------------------------------------------ cuda\bindings\_internal\nvjitlink.pyx:72:29: Cannot convert 'void *' to Python object ``` * Resolve another cython error: `void*` handle vs `intptr_t` handle ``` Error compiling Cython file: ------------------------------------------------------------ ... handle = load_library(driver_ver) # Load function global __nvJitLinkCreate try: __nvJitLinkCreate = <void*><intptr_t>win32api.GetProcAddress(handle, 'nvJitLinkCreate') ^ ------------------------------------------------------------ cuda\bindings\_internal\nvjitlink.pyx:78:73: Cannot convert 'void *' to Python object ``` * Resolve signed/unsigned runtime error. Use uintptr_t consistently. https://github.com/NVIDIA/cuda-python/actions/runs/14224673173/job/39861750852?pr=447#logs ``` =================================== ERRORS ==================================== _____________________ ERROR collecting test_nvjitlink.py ______________________ tests\test_nvjitlink.py:62: in <module> not check_nvjitlink_usable(), reason="nvJitLink not usable, maybe not installed or too old (<12.3)" tests\test_nvjitlink.py:58: in check_nvjitlink_usable return inner_nvjitlink._inspect_function_pointer("__nvJitLinkVersion") != 0 cuda\\bindings\\_internal\\nvjitlink.pyx:221: in cuda.bindings._internal.nvjitlink._inspect_function_pointer ??? cuda\\bindings\\_internal\\nvjitlink.pyx:224: in cuda.bindings._internal.nvjitlink._inspect_function_pointer ??? cuda\\bindings\\_internal\\nvjitlink.pyx:172: in cuda.bindings._internal.nvjitlink._inspect_function_pointers ??? cuda\\bindings\\_internal\\nvjitlink.pyx:73: in cuda.bindings._internal.nvjitlink._check_or_init_nvjitlink ??? cuda\\bindings\\_internal\\nvjitlink.pyx:46: in cuda.bindings._internal.nvjitlink.load_library ??? E OverflowError: can't convert negative value to size_t ``` * Change <void*><uintptr_t>win32api.GetProcAddress` back to `intptr_t`. Changing load_nvidia_dynamic_library() to also use to-`intptr_t` conversion, for compatibility with win32api.GetProcAddress. Document that CDLL behaves differently (it uses to-`uintptr_t`). * Use win32api.LoadLibrary() instead of ctypes.windll.kernel32.LoadLibraryW(), to be more similar to original (and working) cython code. Hoping to resolve this kind of error: ``` _ ERROR at setup of test_c_or_v_program_fail_bad_option[txt-compile_program] __ request = <SubRequest 'minimal_nvvmir' for <Function test_c_or_v_program_fail_bad_option[txt-compile_program]>> @pytest.fixture(params=MINIMAL_NVVMIR_FIXTURE_PARAMS) def minimal_nvvmir(request): for pass_counter in range(2): nvvmir = MINIMAL_NVVMIR_CACHE.get(request.param, -1) if nvvmir != -1: if nvvmir is None: pytest.skip(f"UNAVAILABLE: {request.param}") return nvvmir if pass_counter: raise AssertionError("This code path is meant to be unreachable.") # Build cache entries, then try again (above). > major, minor, debug_major, debug_minor = nvvm.ir_version() tests\test_nvvm.py:148: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ cuda\bindings\nvvm.pyx:95: in cuda.bindings.nvvm.ir_version cpdef tuple ir_version(): cuda\bindings\nvvm.pyx:113: in cuda.bindings.nvvm.ir_version status = nvvmIRVersion(&major_ir, &minor_ir, &major_dbg, &minor_dbg) cuda\bindings\cynvvm.pyx:19: in cuda.bindings.cynvvm.nvvmIRVersion return _nvvm._nvvmIRVersion(majorIR, minorIR, majorDbg, minorDbg) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ > ??? E cuda.bindings._internal.utils.FunctionNotFoundError: function nvvmIRVersion is not found ``` * Remove debug print statements. * Remove some cruft. * Trivial renaming of variables. No functional changes. * Revert debug changes under .github/workflows * Rename _path_finder_utils → _path_finder * Remove LD_LIBRARY_PATH in fetch_ctk/action.yml * Linux: First try using the platform-specific dynamic loader search mechanisms * Add _windows_load_with_dll_basename() * Revert "Revert debug changes under .github/workflows" This reverts commit cc6113c. * Add debug prints in load_nvidia_dynamic_library() * Report dlopen error for libnvrtc.so.12 * print("\nLOOOK dlfcn.dlopen('libnvrtc.so.12', dlfcn.RTLD_NOW)", flush=True) * Revert "Remove LD_LIBRARY_PATH in fetch_ctk/action.yml" This reverts commit 1b1139c. * Only remove ${CUDA_PATH}/nvvm/lib64 from LD_LIBRARY_PATH * Use path_finder.load_nvidia_dynamic_library("nvrtc") from cuda/bindings/_bindings/cynvrtc.pyx.in * Somewhat ad hoc heuristics for nvidia_cuda_nvrtc wheels. * Remove LD_LIBRARY_PATH entirely from .github/actions/fetch_ctk/action.yml * Remove CUDA_PATH\nvvm\bin in .github/workflows/test-wheel-windows.yml * Revert "Remove LD_LIBRARY_PATH entirely from .github/actions/fetch_ctk/action.yml" This reverts commit bff8cf0. * Revert "Somewhat ad hoc heuristics for nvidia_cuda_nvrtc wheels." This reverts commit 43abec8. * Restore cuda/bindings/_bindings/cynvrtc.pyx.in as-is on main * Remove debug print from load_nvidia_dynamic_library.py * Reapply "Revert debug changes under .github/workflows" This reverts commit aaa6aff. * Make `path_finder` work for `"nvrtc"` (#553) * Revert "Restore cuda/bindings/_bindings/cynvrtc.pyx.in as-is on main" This reverts commit ba093f5. * Revert "Reapply "Revert debug changes under .github/workflows"" This reverts commit 8f69f83. * Also load nvrtc from cuda_bindings/tests/path_finder.py * Add heuristics for nvidia_cuda_nvrtc Windows wheels. Also fix a couple bugs discovered by ChatGPT: * `glob.glob()` in this code return absolute paths. * stray `error_messages = []` * Add debug prints, mostly for `os.add_dll_directory(bin_dir)` * Fix unfortunate silly oversight (import os missing under Windows) * Use `win32api.LoadLibraryEx()` with suitable `flags`; also update `os.environ["PATH"]` * Hard-wire WinBase.h constants (they are not exposed by win32con) * Remove debug prints * Reapply "Reapply "Revert debug changes under .github/workflows"" This reverts commit b002ff6. * Add `path_finder.SUPPORTED_LIBNAMES` (#558) * Revert "Reapply "Revert debug changes under .github/workflows"" This reverts commit 8f69f83. * Add names of all CTK 12.8.1 x86_64-linux libraries (.so) as `path_finder.SUPPORTED_LIBNAMES` https://chatgpt.com/share/67f98d0b-148c-8008-9951-9995cf5d860c * Add `SUPPORTED_WINDOWS_DLLS` * Add copyright notice * Move SUPPORTED_LIBNAMES, SUPPORTED_WINDOWS_DLLS to _path_finder/supported_libs.py * Use SUPPORTED_WINDOWS_DLLS in _windows_load_with_dll_basename() * Change "Set up mini CTK" to use `method: local`, remove `sub-packages` line. * Use Jimver/[email protected] also under Linux, `method: local`, no `sub-packages`. * Add more `nvidia-*-cu12` wheels to get as many of the supported shared libraries as possible. * Revert "Use Jimver/[email protected] also under Linux, `method: local`, no `sub-packages`." This reverts commit d499806. Problem observed: ``` /usr/bin/docker exec 1b42cd4ea3149ac3f2448eae830190ee62289b7304a73f8001e90cead5005102 sh -c "cat /etc/*release | grep ^ID" Warning: Failed to restore: Cache service responded with 422 /usr/bin/tar --posix -cf cache.tgz --exclude cache.tgz -P -C /__w/cuda-python/cuda-python --files-from manifest.txt -z Failed to save: Unable to reserve cache with key cuda_installer-linux-5.15.0-135-generic-x64-12.8.0, another job may be creating this cache. More details: This legacy service is shutting down, effective April 15, 2025. Migrate to the new service ASAP. For more information: https://gh.io/gha-cache-sunset Warning: Error during installation: Error: Unable to locate executable file: sudo. Please verify either the file path exists or the file can be found within a directory specified by the PATH environment variable. Also check the file mode to verify the file is executable. Error: Error: Unable to locate executable file: sudo. Please verify either the file path exists or the file can be found within a directory specified by the PATH environment variable. Also check the file mode to verify the file is executable. ``` * Change test_path_finder::test_find_and_load() to skip cufile on Windows, and report exceptions as failures, except for cudart * Add nvidia-cuda-runtime-cu12 to pyproject.toml (for libname cudart) * test_path_finder.py: before loading cusolver, load nvJitLink, cusparse, cublas (experiment to see if that resolves the only Windows failure) Test (win-64, Python 3.12, CUDA 12.8.0, Runner default, CTK wheels) / test ``` ================================== FAILURES =================================== ________________________ test_find_and_load[cusolver] _________________________ libname = 'cusolver' @pytest.mark.parametrize("libname", path_finder.SUPPORTED_LIBNAMES) def test_find_and_load(libname): if sys.platform == "win32" and libname == "cufile": pytest.skip(f'test_find_and_load("{libname}") not supported on this platform') print(f'\ntest_find_and_load("{libname}")') failures = [] for algo, func in ( ("find", path_finder.find_nvidia_dynamic_library), ("load", path_finder.load_nvidia_dynamic_library), ): try: out = func(libname) except Exception as e: out = f"EXCEPTION: {type(e)} {str(e)}" failures.append(algo) print(out) print() > assert not failures E AssertionError: assert not ['load'] tests\test_path_finder.py:29: AssertionError ``` * test_path_finder.py: load *only* nvJitLink before loading cusolver * Run each test_find_or_load_nvidia_dynamic_library() subtest in a subprocess * Add cublasLt to supported_libs.py and load deps for cusolver, cusolverMg, cusparse in test_path_finder.py. Also restrict test_path_finder.py to test load only for now. * Add supported_libs.DIRECT_DEPENDENCIES * Remove cufile_rdma from supported libs (comment out). https://chatgpt.com/share/68033a33-385c-8008-a293-4c8cc3ea23ae * Split out `PARTIALLY_SUPPORTED_LIBNAMES`. Fix up test code. * Reduce public API to only load_nvidia_dynamic_library, SUPPORTED_LIBNAMES * Set CUDA_BINDINGS_PATH_FINDER_TEST_ALL_LIBNAMES=1 to match expected availability of nvidia shared libraries. * Refactor as `class _find_nvidia_dynamic_library` * Strict wheel, conda, system rule: try using the platform-specific dynamic loader search mechanisms only last * Introduce _load_and_report_path_linux(), add supported_libs.EXPECTED_LIB_SYMBOLS * Plug in ctypes.windll.kernel32.GetModuleFileNameW() * Keep track of nvrtc-related GitHub comment * Factor out `_find_dll_under_dir(dirpath, file_wild)` and reuse from `_find_dll_using_nvidia_bin_dirs()`, `_find_dll_using_cudalib_dir()` (to fix loading nvrtc64_120_0.dll from local CTK) * Minimal "is already loaded" code. * Add THIS FILE NEEDS TO BE REVIEWED/UPDATED FOR EACH CTK RELEASE comment in _path_finder/supported_libs.py * Add SUPPORTED_LINUX_SONAMES in _path_finder/supported_libs.py * Update SUPPORTED_WINDOWS_DLLS in _path_finder/supported_libs.py based on DLLs found in cuda_*win*.exe files. * Remove `os.add_dll_directory()` and `os.environ["PATH"]` manipulations from find_nvidia_dynamic_library.py. Add `supported_libs.LIBNAMES_REQUIRING_OS_ADD_DLL_DIRECTORY` and use from `load_nvidia_dynamic_library()`. * Move nvrtc-specific code from find_nvidia_dynamic_library.py to `supported_libs.is_suppressed_dll_file()` * Introduce dataclass LoadedDL as return type for load_nvidia_dynamic_library() * Factor out _abs_path_for_dynamic_library_* and use on handle obtained through "is already loaded" checks * Factor out _load_nvidia_dynamic_library_no_cache() and use for exercising LoadedDL.was_already_loaded_from_elsewhere * _check_nvjitlink_usable() in test_path_finder.py * Undo changes in .github/workflows/ and cuda_bindings/pyproject.toml * Move cuda_bindings/tests/path_finder.py -> toolshed/run_cuda_bindings_path_finder.py * Add bandit suppressions in test_path_finder.py * Add pytest info_summary_append fixture and use from test_path_finder.py to report the absolute paths of the loaded libraries. * Fix tiny accident: a line in pyproject.toml got lost somehow. * Undo changes under .github (LD_LIBRARY_PATH, PATH manipulations for nvvm). * 2025-05-01 version of `cuda.bindings.path_finder` (#578) * Undo changes to the nvJitLink, nvrtc, nvvm bindings * Undo changes under .github, specific to nvvm, manipulating LD_LIBRARY_PATH or PATH * PARTIALLY_SUPPORTED_LIBNAMES_LINUX, PARTIALLY_SUPPORTED_LIBNAMES_WINDOWS * Update EXPECTED_LIB_SYMBOLS for nvJitLink to cleanly support CTK versions 12.0, 12.1, 12.2 * Save result of factoring out load_dl_common.py, load_dl_linux.py, load_dl_windows.py with the help of Cursor. * Fix an auto-generated docstring * first round of Cursor refactoring (about 4 iterations until all tests passed), followed by ruff auto-fixes * Revert "first round of Cursor refactoring (about 4 iterations until all tests passed), followed by ruff auto-fixes" This reverts commit 001a6a2. There were many GitHub Actions jobs that failed (all tests with 12.x): https://github.com/NVIDIA/cuda-python/actions/runs/14677553387 This is not worth spending time debugging. Especially because * Cursor has been unresponsive for at least half an hour: We're having trouble connecting to the model provider. This might be temporary - please try again in a moment. * The refactored code does not seem easier to read. * A couple trivial tweaks * Prefix the public API (just two items) with underscores for now. * Add SPDX-License-Identifier to all files under toolshed/ that don't have it already * Add SPDX-License-Identifier under cuda_bindings/tests/ * Respond to "Do these need to be run as subprocesses?" review question (#578 (comment)) * Respond to "dead code?" review questions (e.g. #578 (comment)) * Respond to "Do we need to implement a cache separately ..." review question (#578 (comment)) * Remove cuDriverGetVersion() function for now. * Move add_dll_directory() from load_dl_common.py to load_dl_windows.py (response to review question #578 (comment)) * Add SPDX-License-Identifier and # Forked from: URL in cuda_paths.py * Add Add SPDX-License-Identifier and Original LICENSE in findlib.py * Very first draft of README.md * Update README.md, mostly as revised by perplexity, with various manual edits. * Refork cuda_paths.py AS-IS: https://github.com/NVIDIA/numba-cuda/blob/8c9c9d0cb901c06774a9abea6d12b6a4b0287e5e/numba_cuda/numba/cuda/cuda_paths.py * ruff format cuda_paths.py (NO manual changes) * Add back _get_numba_CUDA_INCLUDE_PATH from 2279bda (i.e. cuda_paths.py as it was right before re-forking) * Remove cuda_paths.py dependency on numba.cuda.cudadrv.runtime * Add Forked from URLs, two SPDX-License-Identifier, Original Numba LICENSE * Temporarily restore debug changes under .github/workflows, for expanded path_finder test coverage * Restore cuda_path.py AS-IT-WAS at commit 2279bda * Revert "Restore cuda_path.py AS-IT-WAS at commit 2279bda" This reverts commit 1b88ec2. * Force compute-sanitizer off unconditionally * Revert "Force compute-sanitizer off unconditionally" This reverts commit 2bc7ef6. * Add timeout=10 seconds to test_path_finder.py subprocess.run() invocations. * Increase test_path_finder.py subprocess.run() timeout to 30 seconds: Under Windows, loading cublas or cusolver may exceed the 10 second timeout: #578 (comment) * Revert "Temporarily restore debug changes under .github/workflows, for expanded path_finder test coverage" This reverts commit 47ad79f. * Force compute-sanitizer off unconditionally * Add: Note that the search is done on a per-library basis. * Add Note for CUDA_HOME / CUDA_PATH * Add 0. **Check if a library was loaded into the process already by some other means.** * _find_dll_using_nvidia_bin_dirs(): reuse lib_searched_for in place of file_wild * Systematically replace all relative imports with absolute imports. * handle: int → ctypes.CDLL fix * Make load_dl_windows.py abs_path_for_dynamic_library() implementation maximally robust. * Change argument name → libname for self-consistency * Systematically replace previously overlooked relative imports with absolute imports. * Simplify code (also for self-consistency) * Expand the 3. **System Installations** section with information produced by perplexity * Pull out `**Environment variables**` into an added section, after manual inspection of cuda_paths.py. Minor additional edits. * Revert "Force compute-sanitizer off unconditionally" This reverts commit aeaf4f0. * Move _path_finder/sys_path_find_sub_dirs.py → find_sub_dirs.py, use find_sub_dirs_all_sitepackages() from find_nvidia_dynamic_library.py * WIP (search priority updated in README.md but not in code) * Revert "WIP (search priority updated in README.md but not in code)" This reverts commit bf9734c. * WIP (search priority updated in README.md but not in code) * Completely replace cuda_paths.py to achieve the desired Search Priority (see updated README.md). * Define `IS_WINDOWS = sys.platform == "win32"` in supported_libs.py * Use os.path.samefile() to resolve issues with doubled backslashes. * `load_in_subprocess(): Pass current environment * Add run_python_code_safely.py as generated by perplexity, plus ruff format, bandit nosec * Replace subprocess.run with run_python_code_safely * Factor out `class Worker` to fix pickle issue. * ChatGPT revisions based on Deep research: https://chatgpt.com/share/681914ce-f274-8008-9e9f-4538716b4ed7 * Fix race condition in result queue handling by using timeout-based get() The previous implementation checked result_queue.empty() before calling get(), which introduces a classic race condition: the queue may become non-empty immediately after the check, resulting in missed results or misleading errors. This patch replaces the empty() check with result_queue.get(timeout=1.0), allowing the parent process to robustly wait for results with a bounded delay. Also switches from ctx.SimpleQueue() to ctx.Queue() for compatibility with timeout-based get(), which SimpleQueue does not support on Python ≤3.12. Note: The race condition was discovered by Gemini 2.5 * Resolve SIM108 * Change to "nppc" as ANCHOR_LIBNAME * Implement CUDA_PYTHON_CUDA_HOME_PRIORITY first, last, with default first * Remove retry_with_anchor_abs_path() and make retry_with_cuda_home_priority_last() the default. * Update README.md to reflect new search priority * SUPPORTED_LINUX_SONAMES does not need updates for CTK 12.9.0 * The only addition to SUPPORTED_WINDOWS_DLLS for CTK 12.9.0 is nvvm70.dll * Make OSError in load_dl_windows.py abs_path_for_dynamic_library() more informative. * run_cuda_bindings_path_finder.py: optionally use args as libnames (to aid debugging) * Bug fix in load_dl_windows.py: ctypes.windll.kernel32.LoadLibraryW() returns an incompatible `handle`. Use win32api.LoadLibraryEx() instead to ensure self-consistency. * Remove _find_nvidia_dynamic_library.retry_with_anchor_abs_path() method. Move run_python_code_safely.py to test/ directory. * Add missing SPDX-License-Identifier
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May 12, 2025
With the merge of NVIDIA/numba-cuda#155 we need to depend on these two wheels if we want `numba-cuda` to be able to find the runtime libraries it needs in the final cuDF environment. Authors: - https://github.com/brandon-b-miller Approvers: - Bradley Dice (https://github.com/bdice) - Vyas Ramasubramani (https://github.com/vyasr) URL: #18686
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Closes #66
Closes #65
WIP, current code finds nvvm/libdevice which is enough to launch kernels, nvrtc support is next. Logic vendored from
nvmath-python