Hyperion Research Study Quantifies Use of HPC Economically Important AI Applications

During the recent Wells Fargo 2022 TMT Summit, Mark Papermaster, CTO of AMD, reported that the Instinct MI300 accelerated processing unit (APU) is, as of early December 2022, up and running. Currently confined to their in-house lab, the Instinct MI300 will be used in the exascale supercomputer currently in development at Lawrence Livermore National Laboratory, El Capitan, scheduled to be delivered in 2024. Described by Papermaster as a "true datacenter APU," AMD expects general availability of the processor in 2023. This multi-chiplet processor makes use of both AMD's Zen 4 (x86) CPU architecture and CDNA 3, AMD's GPU architecture, designed specifically with exascale computing in mind, and will be produced by Taiwan's TSCM at the 5nm process node. Papermaster sees this development as an important way to continue introducing greater density and optimization into components now that the sector is no longer in the era of the "old Moore's Law."

Expertise is now a major concern for both HPC and AI centers, outranked only by budget concerns. When asked about barriers to furthering AI capabilities, AI-specific expertise was a significant concern. Popular responses included access to AI expertise (49%), skills in AI model development (47%), and skills in AI programming (36%). This development comes at a time when a third of HPC sites (33%) report a lack of knowledge or skilled staff and identified this issue among their top three barriers to expanding on-premises HPC. This data is from the eighth annual study of Hyperion Research's high-performance computing (HPC) end-user-based tracking of the HPC marketplace. It included 181 HPC end-user sites with 3,830 HPC systems.