CUDA Tutorials I CUDA Compatibility

Which versions of the NVIDIA CUDA Toolkit (CTK) are compatible with each other? What do developers need to consider when writing their applications? How often do infrastructure teams need to update their Kernel Drivers?

With monthly releases of the CTK, and quarterly releases of NVIDIA drivers, you can use this video as a quick reference to understand how NVIDIA software, libraries, and drivers interact with each other.

#CUDA #CUDACompatibility #NVIDIA #DisplayCompatibility
CUDA, CUDA Compatibility, Display Compatibility, Runtime, parallel computing, parallel programming, CUDA Toolkit, HPC CUDA Python, NVIDIA CUDA, NVIDIA drivers, CUDA Python, Python

[kevinhamb]

This is exactly what i was looking for! Thanks for the video :)

[walterppk]

I guess this was the full explanation for people who use the CUDA infra directly, but that's not how I usually interact with this stack. As a DS, I've struggled to get CUDA installed on custom docker images in order to develop gpu accelerated tensorflow imgs. The difficulty there lies in the question 'what parts of the CUDA stack do I need, and which version numbers do I need to align, in order to receive GPU support?'. In the end, I defaulted to a tensorflow:tensorflow-gpu image as my base because I couldn't figure it out from a base linux img. I ended up splitting my CI/CD pipeline into a 2 stage build (one where it installs the requirements, and the other to actually add my code), which generates a fairly large final docker image (5gb) and a CI/CD pipeline that takes about 6min when nothing changes.

TL;DR: if you need tensorflow gpu support, trying to manually install the required cuda on ubuntu is a pain. Using tensorflow:tensorflow:gpu does the job and frees you from having to worry about any of this underlying cuda architecture stuff, but you do end up with large docker imgs.

[ElinLiu]

Hi, beginner asks:Can i learn CUDA just with C basics?Or C and C++ are both required?

[aswinfamily]

Could i use the application developed in CUDA 10.1 into CUDA 12 or 11.6 ? I'm usually facing kernel driver error..

[yonnileung]

The most difficult part to working on Ai stuff is installing the "God will know version combination between Cuda and Tensorflow"

[yuan.pingchen]

could you help me solve the problem of the coda device too expensive ? I'm really want to try the most recent version of CUDA compute capability and want to try write program the tensor core....

[xeon]

i tried everything to make my cuda compatible.
i have Nvidia gtx 1660ti (6GB Vram) Notebook Graphics Card.
I know for sure it it cuda compatible. [as its mentioned in card spec]
i want my use stable diffusion 2.1 web ui with GPU's cuda.
please he me figure out correct version for:

nvidia graphics driver: xx
cuda driver : xx
cudnn driver: xx

please tell which version of above drivers should i install so its works.

when i run below program it returns false, i want it to return true.

import torch
torch.cuda.is_available()