Overview of Key Government Support to Quantum Technology Development

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.

AI and HPDA applications continue to grow in utilization and importance in the HPC space, altering the direction of system architecture and design as well as widening the scope of HPC and AI. HPC system architects now have to factor in a variety of processor technologies as well as interconnect, storage, and memory configurations to handle a more diverse set of workloads. Not only are HPC sites adopting emergent AI and HPDA workloads, but some are applying AI techniques to traditional modelling and simulation workloads to uncover new capabilities and solutions. This frequent pairing of simulation and analytics requires that HPC system designs be both compute and data friendly. As a result, recent designs are starting to reverse the emphasis on compute-centrism of past decades and establishing a better balance. Insights into the critical factors driving these and other trends are detailed in the 2021 iteration of Hyperion Research's annual Multi-Client Study (MCS) end users' report, AI and HPDA Usage and Future Technology Trends. Key findings from the report are summarized in this document.