The Nectar GPU service has been made available for researchers to access high end resources which would not otherwise be available to them. Note: this service is now in beta release mode. Due to global supply chain issues, we are still waiting for some of the GPU servers for the National GPU Service to come online. Therefore, the service is available with limited capacity and flavors, but more resources will be coming online in the next couple of months. 


The GPUs are available to use via the Nectar Reservation Service and currently 2 flavor classes are provided:


Flavor Class

Description

G1 

Come with Nvidia A40 GPUs which bring state-of-the-art features for ray-traced rendering, simulation and virtual production.


G2

Contains Nvidia A100 GPUs and provide the highest performance for machine learning training and high performance computing in the cloud.



The specifications (RAM, VCPUs etc), are available on our Nectar flavors page.


Note: All flavors use Nvidia virtual GPU technology meaning the GPU your instance has access to is shared. All flavors have a minimum guaranteed slice alongside dedicated GPU RAM with bigger flavors having a larger minimum slice of computing power.

Using a GPU instance

Once you have made a reservation, you need to run through the standard process to launch an instance, by selecting the appropriate flavor and image. 


The flavor which contains the particular GPU resources you reserved can be found on the detail page for the reservation. You can find this by clicking the reservation ID. 

It would look something similar to what’s pictured below. 



When you are in the launching instance dialog, you should see it appear on the flavor tab.



The image, which is usually the operating system you add to an instance, is a specially built one for use with a GPU. You need to select the one called NeCTAR Ubuntu 20.04 LTS (Focal) amd64 (NVIDIA vGPU). As per its name, it is our standard Nectar Ubuntu 20.04 image, but includes the NVIDIA vGPU driver installed.


Similarly, in the launching instance dialog, on the source tab, you should see it appear in the list of images.


The provided image also contains the appropriate licensing required to run the GPU hardware, which is automatically configured for you. If the current image isn’t sufficient, or you want to use your own image, reach out to us for help. You can lodge a support ticket.


Once you have launched your instance, you can check the GPU and provided license is active by using the following command: 


nvidia-smi -q


The output will contain information about the attached GPU, and at the bottom, should show the licensed status as `licensed`.