![]() 2.148 - 1 _amd64 # You can use this line to find out the directory name # !ls /var/ | grep cuda-repo ! apt - key add / var / cuda - repo - 9 - 2 - local / 7 fa2af80. ! dpkg - i cuda - repo - ubuntu1710 - 9 - 2 - local_9. To find out, run this cell below in a Colab notebook. In Colab case, which is running on an Ubuntu Linux machine, g++ compiler is employed to compile the native CUDA extension. But CUDA version 9.0 has a bug working with g++ compiler to compile native CUDA extensions, that's why we picked CUDA version 9.2 which got the bug fixed.īack to installing, the Nvidia developer site will ask you for the Ubuntu version where you want to run the CUDA. The downside is you need to compile them from source for the individual platform. Some sophisticated Pytorch projects contain custom c++ CUDA extensions for custom layers/operations which run faster than their Python implementations.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |