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NVIDIA GPU's can run in MIG (Multi-Instance GPU), allowing you to pack more jobs on than you have GPUs. Very common in HPC but I don't about in the cloud.
by bluedino 1y ago
NVIDIA GPU's can run in MIG (Multi-Instance GPU), allowing you to pack more jobs on than you have GPUs. Very common in HPC but I don't about in the cloud.
- privatelypublic 1y agoI thought about splitting the GPU between workloads, as well terminal server/virtualized desktop situations. I'd expect all code to be strongly controlled in the former, and reasonably secured in the latter with software/driver level mitigations possible and the fact that corrupting somebody else's desktop with row-hammer doesn't seem like good investment. As another person mentioned- and maybe it is a wider usage than I thought- cloud gpu compute running custom code seems to be the only useful item. But, I'm having a hard time coming up with a useful scenario. Maybe corrupting a SIEM's analysis & alerting of an ongoing attack?
- cyberax 1y agoNo large cloud hoster (AWS, Google, Azure) shares GPUs between tenants.
- shakna 1y agoIs that not what AWS is offering here? [0] "In multi-tenant environments where the goal is to ensure strict isolation." [0] https://aws.amazon.com/blogs/containers/gpu-sharing-on-amazon-eks-with-nvidia-time-slicing-and-accelerated-ec2-instances/ https://aws.amazon.com/blogs/containers/gpu-sharing-on-amazo...
- cyberax 1y agoThis is for customers. AWS can use virtualization to slice their GPUs across multiple workloads (in their K8s), but AWS itself doesn't share GPUs.