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

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. [1]: https://grgalex.medium.com/gpu-virtualization-in-k8s-challenges-and-state-of-the-art-a1cafbcdd12b https://grgalex.medium.com/gpu-virtualization-in-k8s-challen...