Speaker
Description
With the ever-increasing data sizes employed at large experiments and their associated computing needs, many applications can benefit from access to dedicated cluster resources, in particular server-grade GPUs for machine learning applications. However, computing clusters are more often tailored to batch job submission and not to online data visualisation. Infrastructure-as-a-Service (IaaS) applications offer a route for users to access these resources using graphical applications through their web browser. Reliability and simplicity of use are key for these to be used effectively. At the same time, the security of the cluster resources must be maintained and so these must be configured in such a way that resources are not exposed to unauthorised users over the internet.
In this contribution I will discuss the planned deployment of IaaS applications at GSI, including a centrally managed JupyterHub instance for launching Python notebooks and a noVNC system for launching desktop applications on the computing cluster.
