Julie Bernauer — senior solutions architect for machine learning and deep learning at NVIDIA — led the small team that successfully built Selene, the world’s fifth-fastest supercomputer.

Adding to an already impressive feat, Bernauer’s team brought up Selene as the world went into lockdown in early 2020. They used skeleton crews, social distancing protocols, and remote cable validation to achieve what typically takes months with a larger install team in a few weeks.

Bernauer told NVIDIA AI Podcast host Noah Kravitz about the goal in creating Selene, which was primarily to support NVIDIA’s researchers. Referencing her time as a doctoral student, Bernauer explains how researchers are often prevented from working on larger models due to expense and infrastructure.

With Selene, the infrastructure is modular and can be scaled up or down depending on what users require, and allows for different types of research to be performed simultaneously. Bernauer said that Selene is proving most useful to autonomous vehicle and language modeling research at the moment.

Going forward, Bernauer envisions some of the power and efficiency of systems like Selene becoming more available on widely accessible devices, such as laptops or edge products such as cars.