Prerequisite#
If you are new to virtualization, it is recommended to review VMware’s ESXi Getting Started , which includes courses and guidance on potentially any current configuration that you may already have.
At least one NVIDIA data center GPU in a single NVIDIA AI Enterprise Compatible NVIDIA-Certified System. NVIDIA recommends using the following based on your infrastructure.
Adding AI to Mainstream level servers (single to 4-GPU NVLink):
1-8x L4, L40S, H100 NVL, H200 NVL
Large Model Inference in a Single Server (NVL2 High-Capacity AI Server):
2x H200 or Blackwell GPU
Large Model Training and Inference (HGX Scale-Up and Out Server):
4x or 8x H200, or 8x Blackwell GPU
If using NVIDIA A100, the following BIOS settings are required:
Single Root I/O Virtualization (SR-IOV) - Enabled
VT-d/IOMMU - Enabled
If GPU Infrastructure is unavailable, please refer to the CPU Deployment Guide within the Appendix.
NVIDIA AI Enterprise License
VMware ESXi Hypervisor ISO. Please refer to the latest Product Support Matrix for NVIDIA AI Enterprise.
Ubuntu Server 22.04 amd64 ISO. Please refer to the latest Product Support Matrix for NVIDIA AI Enterprise.
NVIDIA AI Enterprise Software:
NVIDIA AI Enterprise Host Software (VIB)
NVIDIA Guest Driver
Note
The NVIDIA AI Enterprise Host Software (VIB) is loaded like a driver in the vSphere hypervisor and is then managed by the vCenter Server.
You may leverage the NVIDIA System Management interface (NV-SMI) management and monitoring tool for testing and benchmarking.
The following server configuration details are considered best practices:
Hyperthreading - Enabled
Power Setting or System Profile - High Performance
CPU Performance (if applicable) - Enterprise or High Throughput
Memory Mapped I/O above 4-GB - Enabled (if applicable)
Note
If NVIDIA card detection does not include all the installed GPUs, set this option to Enabled.