Perspectives on Sustainability in HPC: Current Views and Future Considerations

Hyperion Research covers the worldwide market for deep learning (DL) and machine learning (ML) that is challenging enough to require the use of HPC server systems and other HPC resources (we do not cover the mainstream DL/ML market that does not use HPC, e.g. social media and large internet providers).

Expertise is now a major concern for both HPC and AI users, outranked only by budget concerns among top barriers to expanding HPC on-premises. A third of HPC sites (33.1%) reported that lack of knowledge or skilled support staff was one of their top three barriers. Only a third of respondents (35.4%) report that they do not have any staffing concerns within the next year. When asked about barriers to furthering AI capabilities, AI-specific expertise was identified as a significant concern. Other significant barriers also included access to AI expertise (48.9%), skills in AI model development (47.2%), and skills in AI programming (36.1%). This data is from an annual study that is part of the eighth edition of Hyperion Research's HPC end-user-based tracking of the HPC marketplace. It included 181 HPC end-user sites with 3,830 HPC systems.