Volta Architecture vGPU Types#
The NVIDIA Volta architecture introduced Tensor Cores and high-bandwidth HBM2 memory on data center GPUs such as the Tesla V100. Typical workloads include deep learning training and inference, plus HPC and scientific computing.
Volta vGPU uses time-sliced scheduling for shared GPU access in virtualized environments under NVIDIA AI Enterprise, including clusters that still use V100-class accelerators.
Volta GPU Architecture#
Physical GPUs per board: 1
The maximum number of vGPUs per board is the product of the maximum number of vGPUs per GPU and the number of physical GPUs per board.
This GPU does not support mixed-size mode.
Intended use cases:
vGPUs with more than 40 GB of framebuffer: Training Workloads
vGPUs with 40 GB of framebuffer: Inference Workloads
Required license edition: NVIDIA AI Enterprise
These vGPU types support a single display with a fixed maximum resolution.
Virtual GPU Type |
Intended Use Case |
Framebuffer (GB) |
Maximum vGPUs per GPU |
Maximum vGPUs per Board |
Maximum Display Resolution [1] |
Virtual Displays per vGPU |
|---|---|---|---|---|---|---|
V100L-16C |
Training Workloads |
16 |
1 |
1 |
3840x2400 |
1 |
V100L-8C |
Training Workloads |
8 |
2 |
2 |
3840x2400 |
1 |
V100L-4C |
Inference Workloads |
4 |
4 |
4 |
3840x2400 |
1 |
Footnotes