- Ubuntu 16.04
- CUDA 8.0 installed from TensorFlow instructions.
- numba==0.29.0 installed via pip.
NUMBAPRO_CUDALIB
is undocumented and buried in numba/cuda/cudadrv/libs.py
to find.
My numba cuda checking scripts:
check.sh
#!/bin/sh
export NUMBAPRO_NVVM="/usr/local/cuda/nvvm/lib64/libnvvm.so"
export NUMBAPRO_CUDALIB="/usr/local/cuda/targets/x86_64-linux/lib/"
export NUMBAPRO_LIBDEVICE="/usr/local/cuda/nvvm/libdevice/"
python2 check.py
python3 check.py
check.py
import numba.cuda
numba.cuda.api.detect()
numba.cuda.cudadrv.libs.test()
If it all works it should look something like this:
Found 1 CUDA devices
id 0 b'GeForce GTX 960' [SUPPORTED]
compute capability: 5.2
pci device id: 0
pci bus id: 1
Summary:
1/1 devices are supported
Finding cublas
located at /usr/local/cuda/targets/x86_64-linux/lib/libcublas.so.8.0.45
trying to open library... ok
Finding cusparse
located at /usr/local/cuda/targets/x86_64-linux/lib/libcusparse.so.8.0.44
trying to open library... ok
Finding cufft
located at /usr/local/cuda/targets/x86_64-linux/lib/libcufft.so.8.0.44
trying to open library... ok
Finding curand
located at /usr/local/cuda/targets/x86_64-linux/lib/libcurand.so.8.0.44
trying to open library... ok
Finding nvvm
located at /usr/local/cuda/nvvm/lib64/libnvvm.so
trying to open library... ok
finding libdevice for compute_20... ok
finding libdevice for compute_30... ok
finding libdevice for compute_35... ok
finding libdevice for compute_50... ok
Thank you so much! I met this problem and your trick saved my day 👍