NVIDIA vGPU Licensing

Through various recent projects, I had to work through the clutter of information regarding NVIDIA vGPU licensing.

Here is a small summary of this information.

NVIDIA vGPU Architecture

Under the control of the NVIDIA GPU Virtual Manager, running in the hypervisor, the NVIDIA Physical GPU can operate multiple virtual GPU devices (vGPUs), that can be assigned directly to the Guest VM.

Diagram showing the high-level architecture of NVIDIA vGPU

The Guest VMs use the NVIDIA virtual vGPUs in the same way as a physical GPU would come from the hypervisor by direct passed through. The NVIDIA Driver loaded into the guest VM provides Direct GPU Access for high-performance operations. The NVIDIA Virtual GPU Manager paravirtualized interface performs the non-performance management operations for the NVIDIA Driver.

Continue reading “NVIDIA vGPU Licensing”

Optimization of VMs by NUMA

Introduction CPU & NUMA architecture

The main task of every CPU is to process data. But here is the misconception, the faster the CPU (or the more CPUs I allocate), the faster the data will be processed. This is unfortunately not quite that easy, because before the CPU can process the data, it must be read out by the slower system RAM and that latency can slow the CPU processing. In order to minimize the time the CPU is waiting on reading data, CPU architectures include on-chip memory caches (local RAM) that are much faster than RAM (the access is up to 95% faster).

Optimization of VMs by NUMA
Continue reading “Optimization of VMs by NUMA”