[BUG] Problem linking cu code - with or without pynvjitlink #119
Description
Describe the bug
I cannot link external code with the latest releases of numba 0.61.0 and numba-cuda 0.4.0
Steps/Code to reproduce bug
In python code, have:
import os
import pathlib
from typing import Callable, cast
import numpy as np
from numba import cuda # type: ignore[import]
from pynvjitlink import patch
patch.patch_numba_linker()
# Compile CUDA code
CUDA_ARCH = "sm_80" # ampere architecture
dir = pathlib.Path(__file__).parent
sampling_cu = str(dir / "foo.cu")
libsampling_a = str(dir / "libfoo.a")
os.system(
f"nvcc -lib -Xcompiler -fPIC -arch={CUDA_ARCH} "
f"{sampling_cu} -o {libsampling_a}"
)
THeirarchicalTopK = Callable[[int], None]
hierarchical_topk_device = cast(
THeirarchicalTopK,
cuda.declare_device(
"hierarchical_topk_device",
# "void(CPointer(uint64), CPointer(uint64), int32, int32)",
"void(int32)",
),
)
@cuda.jit(link=[libsampling_a])
def hierarchical_topk_kernel(
# data: TKeyArray, topk: TKeyArray, k: int, n: int
k: int,
) -> None:
"""
Find the top-k elements in the input array using a hierarchical algorithm.
"""
hierarchical_topk_device(np.int32(k))
hierarchical_topk_kernel[(1,), (1,)](2)In foo.cu have:
extern "C" {
__device__ void hierarchical_topk_device(int k) { }
}I get the following error:
File "/data/sda/shaunc-src/factfiber.ai/mlops/ingolstadt/src/ingolstadt/cudautil/sampling/sampling.py", line 60, in <module>
hierarchical_topk_kernel[(1,), (1,)](2)
File "/home/shauncutts/.cache/pypoetry/virtualenvs/ingolstadt-h73rb8xf-py3.11/lib/python3.11/site-packages/numba_cuda/numba/cuda/dispatcher.py", line 608, in __call__
return self.dispatcher.call(args, self.griddim, self.blockdim,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/shauncutts/.cache/pypoetry/virtualenvs/ingolstadt-h73rb8xf-py3.11/lib/python3.11/site-packages/numba_cuda/numba/cuda/dispatcher.py", line 750, in call
kernel = _dispatcher.Dispatcher._cuda_call(self, *args)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/shauncutts/.cache/pypoetry/virtualenvs/ingolstadt-h73rb8xf-py3.11/lib/python3.11/site-packages/numba_cuda/numba/cuda/dispatcher.py", line 758, in _compile_for_args
return self.compile(tuple(argtypes))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/shauncutts/.cache/pypoetry/virtualenvs/ingolstadt-h73rb8xf-py3.11/lib/python3.11/site-packages/numba_cuda/numba/cuda/dispatcher.py", line 1005, in compile
kernel.bind()
File "/home/shauncutts/.cache/pypoetry/virtualenvs/ingolstadt-h73rb8xf-py3.11/lib/python3.11/site-packages/numba_cuda/numba/cuda/dispatcher.py", line 257, in bind
cufunc = self._codelibrary.get_cufunc()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/shauncutts/.cache/pypoetry/virtualenvs/ingolstadt-h73rb8xf-py3.11/lib/python3.11/site-packages/numba_cuda/numba/cuda/codegen.py", line 248, in get_cufunc
cubin = self.get_cubin(cc=device.compute_capability)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/shauncutts/.cache/pypoetry/virtualenvs/ingolstadt-h73rb8xf-py3.11/lib/python3.11/site-packages/numba_cuda/numba/cuda/codegen.py", line 227, in get_cubin
self._link_all(linker, cc, ignore_nonlto=False)
File "/home/shauncutts/.cache/pypoetry/virtualenvs/ingolstadt-h73rb8xf-py3.11/lib/python3.11/site-packages/numba_cuda/numba/cuda/codegen.py", line 192, in _link_all
linker.add_file_guess_ext(path, ignore_nonlto)
TypeError: PatchedLinker.add_file_guess_ext() takes 2 positional arguments but 3 were given
Expected behavior
I would expect the kernel to link and run.
Environment details (please complete the following information):
- Environment location: [Bare-metal, Docker, Cloud(specify cloud provider)]
- Method of numba-cuda install: [conda, Docker, or from source]
- If method of install is [Docker], provide
docker pull&docker runcommands used
- If method of install is [Docker], provide
ubuntu 22.04
numba -s output
System info:
Time Stamp
Report started (local time) : 2025-01-31 02:41:09.429322
UTC start time : 2025-01-31 07:41:09.429325
Running time (s) : 1.830247
Hardware Information
Machine : x86_64
CPU Name : znver2
CPU Count : 48
Number of accessible CPUs : 32
List of accessible CPUs cores : 0-47
CFS Restrictions (CPUs worth of runtime) : None
CPU Features : 64bit adx aes avx avx2 bmi bmi2
clflushopt clwb clzero cmov crc32
cx16 cx8 f16c fma fsgsbase fxsr
lzcnt mmx movbe mwaitx pclmul
popcnt prfchw rdpid rdpru rdrnd
rdseed sahf sha sse sse2 sse3
sse4.1 sse4.2 sse4a ssse3 wbnoinvd
xsave xsavec xsaveopt xsaves
Memory Total (MB) : 257578
Memory Available (MB) : 222210
OS Information
Platform Name : Linux-5.15.0-116-generic-x86_64-with-glibc2.35
Platform Release : 5.15.0-116-generic
OS Name : Linux
OS Version : #126-Ubuntu SMP Mon Jul 1 10:14:24 UTC 2024
OS Specific Version : ?
Libc Version : glibc 2.35
Python Information
Python Compiler : GCC 12.3.0
Python Implementation : CPython
Python Version : 3.11.8
Python Locale : en_US.UTF-8
Numba Toolchain Versions
Numba Version : 0.61.0
llvmlite Version : 0.44.0
LLVM Information
LLVM Version : 15.0.7
CUDA Information
CUDA Target Implementation : NVIDIA
CUDA Device Initialized : True
CUDA Driver Version : 12.5
CUDA Runtime Version : 12.5
CUDA NVIDIA Bindings Available : False
CUDA NVIDIA Bindings In Use : False
CUDA Minor Version Compatibility Available : False
CUDA Minor Version Compatibility Needed : False
CUDA Minor Version Compatibility In Use : False
CUDA Detect Output:
Found 2 CUDA devices
id 0 b'NVIDIA GeForce RTX 4090' [SUPPORTED]
Compute Capability: 8.9
PCI Device ID: 0
PCI Bus ID: 33
UUID: GPU-1476ba35-b2b3-1140-fd05-d3dae02f9309
Watchdog: Enabled
FP32/FP64 Performance Ratio: 64
id 1 b'NVIDIA GeForce RTX 3070' [SUPPORTED]
Compute Capability: 8.6
PCI Device ID: 0
PCI Bus ID: 1
UUID: GPU-c61e09df-dc55-c4cc-3740-3cd5d5b27f81
Watchdog: Enabled
FP32/FP64 Performance Ratio: 32
Summary:
2/2 devices are supported
CUDA Libraries Test Output:
Finding driver from candidates:
libcuda.so
libcuda.so.1
/usr/lib/libcuda.so
/usr/lib/libcuda.so.1
/usr/lib64/libcuda.so
/usr/lib64/libcuda.so.1
Using loader <class 'ctypes.CDLL'>
Trying to load driver... ok
Loaded from libcuda.so
Mapped libcuda.so paths:
/usr/lib/x86_64-linux-gnu/libcuda.so.555.42.06
Finding nvvm from CUDA_HOME
Located at /usr/local/cuda/nvvm/lib64/libnvvm.so.4.0.0
Trying to open library... ok
Finding nvrtc from CUDA_HOME
Located at /usr/local/cuda/lib64/libnvrtc.so.12.5.82
Trying to open library... ok
Finding cudart from CUDA_HOME
Located at /usr/local/cuda/lib64/libcudart.so.12.5.82
Trying to open library... ok
Finding cudadevrt from CUDA_HOME
Located at /usr/local/cuda/lib64/libcudadevrt.a
Checking library... ok
Finding libdevice from CUDA_HOME
Located at /usr/local/cuda/nvvm/libdevice/libdevice.10.bc
Checking library... ok
Include directory configuration variable:
CUDA_INCLUDE_PATH=/usr/local/cuda/include
Finding include directory from CUDA_INCLUDE_PATH Config Entry
Located at /usr/local/cuda/include
Checking include directory... ok
NumPy Information
NumPy Version : 1.26.4
NumPy Supported SIMD features : ('MMX', 'SSE', 'SSE2', 'SSE3', 'SSSE3', 'SSE41', 'POPCNT', 'SSE42', 'AVX', 'F16C', 'FMA3', 'AVX2')
NumPy Supported SIMD dispatch : ('SSSE3', 'SSE41', 'POPCNT', 'SSE42', 'AVX', 'F16C', 'FMA3', 'AVX2', 'AVX512F', 'AVX512CD', 'AVX512_KNL', 'AVX512_KNM', 'AVX512_SKX', 'AVX512_CLX', 'AVX512_CNL', 'AVX512_ICL')
NumPy Supported SIMD baseline : ('SSE', 'SSE2', 'SSE3')
NumPy AVX512_SKX support detected : False
SVML Information
SVML State, config.USING_SVML : False
SVML Library Loaded : False
llvmlite Using SVML Patched LLVM : True
SVML Operational : False
Threading Layer Information
TBB Threading Layer Available : False
+--> Disabled due to Unknown import problem.
OpenMP Threading Layer Available : True
+-->Vendor: GNU
Workqueue Threading Layer Available : True
+-->Workqueue imported successfully.
Numba Environment Variable Information
None found.
Conda Information
Conda Build : not installed
Conda Env : 22.11.1
Conda Platform : linux-64
Conda Python Version : 3.10.8.final.0
Conda Root Writable : True
Installed Packages
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_openmp_mutex 4.5 2_gnu conda-forge
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pytest-timeout 2.2.0 pypi_0 pypi
pytest-tmpfs 0.1.4 pypi_0 pypi
pytest-watch 4.2.0 pypi_0 pypi
pytest-xdist 3.6.1 pypi_0 pypi
python 3.11.8 hab00c5b_0_cpython conda-forge
python-dateutil 2.8.2 pypi_0 pypi
python-gitlab 3.15.0 pypi_0 pypi
python-installer 0.7.0 pyhd8ed1ab_0 conda-forge
python-json-logger 2.0.7 pypi_0 pypi
python-semantic-release 7.34.6 pypi_0 pypi
python-slugify 8.0.1 pypi_0 pypi
python_abi 3.11 3_cp311 conda-forge
pytimeparse 1.1.8 pypi_0 pypi
pytoolconfig 1.2.6 pypi_0 pypi
pytz 2023.3.post1 pypi_0 pypi
pyudorandom 1.0.0 pypi_0 pypi
pyyaml 6.0.1 pypi_0 pypi
pyzmq 25.1.2 pypi_0 pypi
randomname 0.1.5 pypi_0 pypi
rapidfuzz 3.5.2 pypi_0 pypi
readline 8.2 h8228510_1 conda-forge
readme-renderer 44.0 pypi_0 pypi
recursive-diff 1.1.1.dev5+gf925708 pypi_0 pypi
referencing 0.32.1 pypi_0 pypi
requests 2.28.1 pypi_0 pypi
requests-toolbelt 0.9.1 pypi_0 pypi
responses 0.23.3 pypi_0 pypi
rfc3986 2.0.0 pypi_0 pypi
rich 13.9.2 pypi_0 pypi
rope 1.10.0 pypi_0 pypi
rpds-py 0.17.1 pypi_0 pypi
ruamel-yaml 0.18.6 pypi_0 pypi
ruamel-yaml-clib 0.2.8 pypi_0 pypi
ruff 0.5.0 pypi_0 pypi
s3fs 2024.9.0 pypi_0 pypi
s3transfer 0.10.2 pypi_0 pypi
s3tree 0.3.0 pypi_0 pypi
samarqand 0.0.1 pypi_0 pypi
scikit-learn 1.4.0 pypi_0 pypi
scipy 1.12.0 pypi_0 pypi
scmrepo 3.3.8 pypi_0 pypi
seaborn 0.12.2 pypi_0 pypi
secretstorage 3.3.3 py311h38be061_1 conda-forge
semver 3.0.2 pypi_0 pypi
setuptools 68.2.2 pypi_0 pypi
setuptools-scm 8.0.4 pypi_0 pypi
shellingham 1.5.0 pypi_0 pypi
shortuuid 1.0.13 pypi_0 pypi
shtab 1.7.1 pypi_0 pypi
six 1.16.0 pyh6c4a22f_0 conda-forge
smmap 5.0.1 pypi_0 pypi
sortedcontainers 2.4.0 pypi_0 pypi
soupsieve 2.5 pypi_0 pypi
sqltrie 0.11.1 pypi_0 pypi
stack-data 0.6.3 pypi_0 pypi
stack_data 0.6.2 pyhd8ed1ab_0 conda-forge
tabulate 0.9.0 pypi_0 pypi
tdigest 0.5.2.2 pypi_0 pypi
tenacity 8.2.2 pypi_0 pypi
termcolor 2.4.0 pypi_0 pypi
text-unidecode 1.3 pypi_0 pypi
textwrap3 0.9.2 pypi_0 pypi
threadpoolctl 3.2.0 pypi_0 pypi
tinycss2 1.3.0 pypi_0 pypi
tk 8.6.13 noxft_h4845f30_101 conda-forge
toml 0.10.2 pypi_0 pypi
tomli 2.0.1 pyhd8ed1ab_0 conda-forge
tomlkit 0.11.6 pypi_0 pypi
toolz 0.12.1 pypi_0 pypi
toposort 1.10 pypi_0 pypi
tornado 6.4 pypi_0 pypi
tqdm 4.66.5 pypi_0 pypi
traitlets 5.13.0 pypi_0 pypi
trash-cli 0.24.5.26 pypi_0 pypi
trove-classifiers 2023.5.24 pyhd8ed1ab_0 conda-forge
twine 3.8.0 pypi_0 pypi
typer 0.12.5 pypi_0 pypi
types-aiobotocore 2.5.0.post2 pypi_0 pypi
types-aiobotocore-s3 2.6.0 pypi_0 pypi
types-awscrt 0.16.18 pypi_0 pypi
types-cachetools 5.5.0.20240820 pypi_0 pypi
types-python-dateutil 2.9.0.20241003 pypi_0 pypi
types-pytz 2024.2.0.20241003 pypi_0 pypi
types-pyyaml 6.0.12.12 pypi_0 pypi
types-s3transfer 0.6.1 pypi_0 pypi
types-tabulate 0.9.0.20240106 pypi_0 pypi
typing 3.10.0.0 pyhd8ed1ab_0 conda-forge
typing-extensions 4.9.0 pypi_0 pypi
tzdata 2022.7 pypi_0 pypi
urllib3 2.2.0 pypi_0 pypi
uvloop 0.17.0 pypi_0 pypi
vine 5.1.0 pypi_0 pypi
virtualenv 20.29.1 pypi_0 pypi
voluptuous 0.15.2 pypi_0 pypi
watchdog 3.0.0 pypi_0 pypi
wcwidth 0.2.9 pypi_0 pypi
webencodings 0.5.1 pypi_0 pypi
websockets 11.0.3 pypi_0 pypi
werkzeug 3.0.0 pypi_0 pypi
wheel 0.45.0 pypi_0 pypi
widgetsnbextension 4.0.11 pypi_0 pypi
wrapt 1.16.0 pypi_0 pypi
xarray 2024.3.0 pypi_0 pypi
xarray-dataclasses 0.3.0 pypi_0 pypi
xmltodict 0.13.0 pypi_0 pypi
xz 5.2.6 h166bdaf_0 conda-forge
yapic-json 1.9.1 pypi_0 pypi
yarl 1.13.1 pypi_0 pypi
zarr 2.16.1 pypi_0 pypi
zc-lockfile 3.0.post1 pypi_0 pypi
zipp 3.19.2 pyhd8ed1ab_0 conda-forge
zope-dottedname 6.0 pypi_0 pypi
No errors reported.
Warning log
Warning (psutil): psutil cannot be imported. For more accuracy, consider installing it.
Warning (no file): /sys/fs/cgroup/cpuacct/cpu.cfs_quota_us
Warning (no file): /sys/fs/cgroup/cpuacct/cpu.cfs_period_us
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Additional context
Without pynvjitlink fails with numba.cuda.cudadrv.driver.LinkerError: [200] Call to cuLinkAddFile results in CUDA_ERROR_INVALID_IMAGE - I presume this is expected.