IN5050 - NVIDIA GeForce GPU Resources & FAQ
A page for resources and frequently asked questions for the Jetson AGX Xavier machines. If you have any other questions, please send an email to in5050@ifi.uio.no
Remember that you might have to SSH into login.ifi.uio.no to access the login machine for IN5050 (roa.sinlab.no). Following this guide, it is possible to set up SSH and SSHFS from external machines.
A username and password have been provided to all groups. The following table gives an overview of the status of the ARM machines with GPU at IFI:
| Computer | CPU | GPU | Memory | Compute Capability | SIMD Capability | Status |
| in5050-2016-10 | Intel Core i7-6700K | Quadro K2200 | 16 GB | 5.0 | SSE 4.2 / AVX2 | Operational |
| in5050-2014-11 | Intel Core i5-4590 | Quadro K2200 | 8 GB | 5.0 | SSE 4.2 / AVX2 | Operational |
GPU Programming Resources
Paper on optimizing the Motion JPEG encoder for Cell and GPU (access from UiO)
NVIDIA CUDA Toolkit 12.8 Documentation
Frequently Asked Questions
Q: Can I use my own GPU?
A: Yes, you can. However, we do not recommend this. The program has to be compiled and run on the lab machines. Your CPU code should be optimized for 64-bit x86, and the GPU code should be optimized for the Maxwell architecture (Compute 5.x).
Q: Do we have any video source files to test with?
A: The video source files are stored in /opt/media.
Q: My video is broken, are there some tools to analyze the video?
A: Yes, there are! Try out YUView, an open-source and cross-platform YUV player and analysis tool.
Q: What software do I need to run on my own GPU?
A: At IFI, we run Ubuntu 20.04 LTS (x86_64) with CUDA 12.8 from NVIDIA. You must download a CUDA-certified driver and CUDA 12.8 toolkit from NVIDIA. The CUDA SDK is optional, but it contains several useful functions.