HPC-AI Technology Survey 2023: Cloud Computing


Intersect360 Research surveyed the user community for High Performance Computing (HPC) and artificial intelligence (AI) on a wide range of technology issues. The complete study analyzes users’ current computing systems, processing elements, storage systems, networks, operating environments, cloud computing usage, and selected forward-looking trends. Our goal in this analysis is to provide an overview of how HPC-AI systems are configured, including the breadth of technologies most commonly used. The survey audience included members of the worldwide HPC-AI user community spanning industry, government, and academia.

Intersect360 Research reports available in this HPC-AI Technology Survey report series include the following segmentations:

  • Systems, CPUs, and Accelerators: including system vendors installed, current and planned installations and user preferences for CPUs and accelerators, system utilization rates, and usage of liquid cooling.
  • Storage and Interconnect Technologies: including total active HPC data; storage configurations spanning on-node, attached storage arrays, and cloud storage; parallel file system usage; system interconnects and speeds; and composable infrastructure.
  • Operating Environments: including installations of operating systems, middleware packages, and developer tools.
  • Cloud Computing: including current and planned proportion of computing and storage in public cloud for HPC and top named cloud vendors.

This report provides a detailed examination of the usage of public cloud computing as part of HPC-AI infrastructure. We look at the top cloud computing vendors for HPC-AI, as well as the current and projected changes in cloud computing usage, with an examination of the drivers and barriers affecting adoption. We additionally explore the use of cloud-like, on-premises, as-a-Service offerings.

Cloud computing has been a persistent topic across all of enterprise computing since the early part of the century, with promises to save organizations money on infrastructure and management costs through outsourced IT and utility-based, pay-as-you-go pricing. The recent boom in AI has been a boon to cloud adoption.

In our HPC-AI Technology Survey, users reported that 12% of their total HPC-AI workloads, on average, was served by public cloud. Usage is not spread evenly. Commercial users are much more likely than public-sector to deploy cloud for HPC-AI workloads, and cloud is also used more heavily by those with smaller budgets than those with larger budgets. Overall, cloud computing usage will continue to grow, as users expect it will represent 22% of all HPC-AI workloads, nearly double cloud’s current penetration.

Segmented analysis of growth rates and an examination of drivers and barriers suggest there is an eventual limit to cloud penetration in HPC-AI. Most respondents see cloud as serving a different purpose than on-premises systems, and they also perceive cloud usage to be more expensive than on-premises computing.

The value proposition for cloud computing needs to evolve for it to benefit more HPC-AI users. The majority of the HPC-AI market is not prepared to view cloud computing as inherently superior in either performance or price/performance. As a group, HPC-AI users savvy technology evaluation, and cloud computing is no exception.