Hello, it looks like you’re running Cuda 9 which does not support sm_75. You can either use sm_70 or cuda 10. To select the card you want the code to run on: check with nvidia-smi cards numbers (first number before card hardware name, called GPU). When launching Smartg function, add as parameter dev...

Hey,

Looks like you have installed a MKL (Intel Math Kernel Library) enabled version of numpy. Either you can disable MKL optimizations, or install MKL.

Please see https://docs.anaconda.com/mkl-optimizations/ for further informations.

HTH,

Hello jandrey, It looks like pycuda (which is a quite old version) depends on an old version of cuda (8). Simpler (but a bit ugly) way that should work: find where libcurand.so* is located (find / -name 'libcurand.so*' in linux). Go to that directory, and make a symbolic link (ln -s libcurand.so.?.0...

Hello Javier,

Though we don’t have tested such hardware, smart-g should run flawlessly with yours.
Feel free to send us feedback so we can add that to tested hardware list.

Best,

Hello Clémence,

Sorry, our README was probably not clear enough. You need a Nvidia graphic card to be able to run any CUDA code. Without such hardware, you simply can’t run SMART-G. If you need any advice to buy some card, feel free to ask.

Best,

Hello Clémence, your hardware may be too new for cuda 8. Can you tell me which card you possess ? Have you been able to run any cuda code (cuda samples are an easy try) with cuda 8 ? Also, I would need the driver version you use. Could you please try installing pycuda with pip install instead of luk...

Hi npal, So I guess you’re using CentOS (or RHEL, or Scientific Linux) 7.x. Do you have installed some redhat devtoolset or any other gcc version that could have been used during installation of polymer ? The error message looks like there were some heavily modified environment used during installat...

Hello npal,

Could you tell me:

• OS used and its version
• gcc/g++ version used (gcc --version and g++ --version)

It looks likely you’re hitting something like https://stackoverflow.com/questions/203 ... -not-found

Hope that helps.

Hi rif, If you are using CentOS: You need to install glibc-headers and glibc-devel: (as root) yum install glibc-headers glibc-devel -y If you are using Ubuntu: apt install libc6-dev -y If you are using any other platform, you have to find out which packages provide libc.so and libpthread.so and inst...

Hello amitd, We currently use Cuda 10.0.130 coming straight from official Nvidia repository: https://developer.nvidia.com/cuda-downloads with the recommended driver (410.79) provided by the same repository. Our development platform runs CentOS 7.6 with 6x0, 9x0 and 10x0 models. Could you tell us mor...