Cloud Service Providers Poised to Expand AI Accelerator Options with Custom AI Chips

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.

Although China represents more than one-third of the global market for semiconductors, the country relies heavily on foreign sources, especially U.S. chipmakers and foundries headquartered in other Asian countries, for a majority of devices critical to Chinese-made products ranging from smartphones to industrial machinery and supercomputers. For the past few decades, China sought to develop an indigenous capability in an effort to reduce its dependence on the foreign supply of components. Its most recent major effort, the “Made-in-China” semiconductor initiative launched in 2015, targeted supplying 40% of China's semiconductor demand with homegrown products by 2020 and 70% by 2025.