![nvidia cuda driver linux nvidia cuda driver linux](https://www.cyberciti.biz/media/new/faq/2018/10/Ubuntu-Linux-Install-Nvidia-Driver-using-Sofware-Manager-GUI-tool.png)
- Nvidia cuda driver linux install#
- Nvidia cuda driver linux serial#
- Nvidia cuda driver linux drivers#
- Nvidia cuda driver linux code#
Yes they Nvidia DockerHub images are 1-2 gig's large, but normally you only have to download them once, as you use the image as a base, if you add your code to it only those layers of your code which are normally small to dozens of Mbi are to be recurrently pulled/pushed, not the entire image, so honestly I can't see a reason why people is so much concerned about image sizes, small is better no doubt but up to a point, spending your valuable time in your actual needs is far better. If you want to be picky go to their Gitlab's repository for dockers, you can build up Debian/Ubuntu by hand pretty easily and quick. Or even better use the "huge" Nvidia DockerHub images (ubuntu LTS based).Īnyway, beyond this question, the Nvidia DockerHub ones are the best way to go, they are supported by the creators of CUDA Toolkit itself and they are no brainers.
Nvidia cuda driver linux install#
Use Debian's slim images or Ubuntu minimal and install official supported files manually, as this is the smallest you can go.
Nvidia cuda driver linux drivers#
Nvidia drivers and CUDA Toolkits are incredibly complex systems that honestly I can't see the point to compile it yourself for an unsupported system library or an unsupported port for libc, with all the unexpected to happen even in the case it compiles.
Nvidia cuda driver linux serial#
I followed this guide from NVIDIA.Ģd:00.0 VGA compatible controller: NVIDIA Corporation TU104 (rev a1)Ģd:00.1 Audio device: NVIDIA Corporation TU104 HD Audio Controller (rev a1)Ģd:00.2 USB controller: NVIDIA Corporation TU104 USB 3.1 Host Controller (rev a1)Ģd:00.3 Serial bus controller : NVIDIA Corporation TU104 USB Type-C UCSI Controller (rev a1)
![nvidia cuda driver linux nvidia cuda driver linux](https://miro.medium.com/max/565/1*RpeY2idTfbgPGEQUPFsJcw.jpeg)
When trying to install CUDA it complains about many packages that have unmet dependencies.īut from the start. Anyways, since I was gonna do a fresh install of CUDA I thought I might bump Tensorflow from 2.4.1 to 2.5.0 too to take advantage of the newest features.
![nvidia cuda driver linux nvidia cuda driver linux](https://www.cyberciti.biz/media/new/faq/2021/09/How-to-get-the-CUDA-version-on-Linux-using-command-option.png)
I also noticed that the CUDA version returned by nvcc -version (Cuda compilation tools, release 10.1, V10.1.243) is older than what Tensorflow requires (11.2). executing _physical_devices only includes the CPU but not the GPU. Recently I discovered that Tensorflow doesn't have access to the GPU anymore.