The HPC Cloud Market by Geographic Region and Competitive Segment

The HPC market is experiencing many challenges and opportunities from the covid-19 virus and its resulting economic impacts. In July 2020, the situation appeared bleak, with a potential for 2020 HPC server revenues being down by as much as 20% year on year. More recently, surveys show an improved outlook, although still with a market contraction of approximately 14% compared with 2019. The Workgroup segment is bearing the near-term brunt of the downside impact.

Covid-related HPC investment impacts are not equally distributed across the vertical markets; several segments are already experiencing increased HPC investments. These include bio/life sciences and government labs. At the same time other verticals are facing a greater negative impact, including oil & gas, manufacturing, and DCC/content distribution

HPC cloud adoption has grown aggressively over the last few years as cloud providers have recognized the HPC market as a high value target and have brought HPC-specific capabilities to their platforms to entice users. This has resulted in growing number of HPC users that are now using external clouds for parts of their HPC workload portfolio.   Hyperion Research has followed the growth vector of cloud adoption for many years and conducted a number of broad studies to better understand the underlying trends of cloud usage. This research has shown that users are contemplating different approaches of cloud adoption including what types of applications to send to the cloud; how much to send to the cloud; and ultimately whether to run a specific workload in the cloud or not.   As the performance capabilities of the cloud for HPC workloads improve, many of the barriers to adoption have been reduced, but some remained consistent barriers despite the technological advancements. These adoption inhibitors may be offset in many situations by the corresponding drivers and benefits. This will lead to increased cloud usage for many HPC applications and workloads in both traditional modeling/simulation as well as artificial intelligence.