Buyers’ Expected HPC Spending Changes: On-Premises and Cloud

Innovations are constantly occurring across all aspects of HPC infrastructure. Much of that innovation has been focused on the computing infrastructure:

• CPU performance once driven by faster clock speeds have evolved to integrating more cores.
• GPUs have emerged to advance performance of AI-related workloads.
• Application-specific accelerators are now being introduced to address unique elements of AI applications.

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.