Take a look at the Medium article [1] and it will be clear to you that this is not the same.
Each complete GPU sharing approach must have:
- A mechanism to facilitate sharing (security, isolation, avoiding OOM errors).
- A K8s integration.
Most approaches (like the one you mentioned above) lack a mechanism and simply work around the 1-1 GPU allocation on Kubernetes by advertizing more devices per physical GPU.
Those are not viable solutions.
Please take a look at Paragraph 5 ("The real challenge of GPU virtualization on K8s") onwards as well as the repo notes.
Each complete GPU sharing approach must have:
Most approaches (like the one you mentioned above) lack a mechanism and simply work around the 1-1 GPU allocation on Kubernetes by advertizing more devices per physical GPU.Those are not viable solutions.
Please take a look at Paragraph 5 ("The real challenge of GPU virtualization on K8s") onwards as well as the repo notes.
[1]: https://grgalex.medium.com/gpu-virtualization-in-k8s-challen...