How can I install CUDA to work correctly with my older nvidia driver so I can conduct some GPU computations? Is there a list someplace that lists the what CUDA toolkits go with each NVIDIA driver? I suspect I need an older toolkit, I just don't know which one. The Linux Getting Started Manual says I should just need to install CUDA with apt-get but I need an older driver for my graphics card. I have verified that the nvidia-346 is the problem by specifically installing it as opposed to nvidia-current. This document provides guidance to ensure. Kepler Compatibility Guide This application note is intended to help developers ensure that their NVIDIA CUDA applications will run effectively on GPUs based on the NVIDIA Kepler Architecture. Also, you may not be able to update to the latest version of CUDA toolkit since each CUDA version has minimum. If you want to do deep learning, you may find difficulties since most CUDA features for deep learning are available for GPU with compute capability 3.0 or higher. After this check, if the Cuda path is set in the environment variables. The intent is to provide guidelines for obtaining the best performance from NVIDIA GPUs using the CUDA Toolkit. Quadro 2000 has Fermi architecture with compute capability 2.1.
Naturally, I thought I could then install cuda with: sudo apt-get install cudaīut this tries to install nvidia-346 on my system causing my system to no longer display my desktop and the installation is incorrect. CopyIf you are deploying applications on NVIDIA Tesla products in a server or cluster environment, please use the latest recommended Tesla driver that has been.
The NVIDIA CUDA Deep Neural Network library (cuDNN) is a GPU.
Sudo apt-get install nvidia-current (this installs nvidia-304 in my case)Īfter rebooting, a quick query shows that my kernel is indeed using nvidia successfully lspci -vnn | grep -i VGA -A 12Ġ1:00.0 VGA compatible controller : NVIDIA Corporation GT218 (rev a2) (prog-if 00 ) A: For convenience, the installer packages on this page include NVIDIA drivers which support application development for all CUDA-capable GPUs supported by this release of the CUDA Toolkit. After finishing the CUDA Toolkit installation you have to install cuDNN on Windows 10 which is compatible with CUDA version. I have tried to complete the installation successfully but have stumbled upon a problem. I have been provided an older NVIDIA graphics card (GeForce 8400 GS) to begin exploring some GPU computing.