A Thought Experiment on Accelerated HPC Cloud Growth

Hyperion Research projects that between 2021 and 2026, worldwide installations of leading-edge exascale and near-exascale systems will total 28-38 new systems, worth an estimated $10-$15 billion, with China, the EU, and the United States each fielding 7 -10 systems in the six year interval. Being an exascale trailblazer can be expensive, with systems on the near horizon costing upwards of $500 million or more each, and only the most ambitious governments can commit to participating in these early rounds of exascale progress. However, as HPC price/performance moderates, a long-verified phenomenon in the HPC space, additional nations will also be looking to provide their domestic R&D base with access to exascale-class HPCs either developed domestically or procured from foreign sources.

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.