This Intersect360 Research report presents the 2022 total market size and five-year forecast for the overall market for the on-premises or colocated (i.e., non-cloud) servers and systems used for High Performance Computing (HPC) and artificial intelligence (AI), segmented into server classes. The primary consideration for server class is sales price—entry-level HPC systems under $50K, midrange HPC systems from $50K to $250K, high-end HPC systems from $250K to $1.5 million, and supercomputers over $1.5 million—although architecture, sales channel, and sales cycle are all additional considerations. The forecast horizon is from 2023 through 2027, with compound annual growth rates (CAGRs) using 2022 as a base.
This report presents multiple views of the market for infrastructure for HPC and AI. The “traditional HPC” market view represents HPC user budgets. In most cases, these environments have evolved to include machine learning as part of their overall workloads, and HPC budgets have generally increased because of machine learning; they are still essentially HPC budgets, for systems that would have existed regardless of machine learning. The “expanded HPC-AI” view incorporates the growing effect of spending on scalable infrastructure for AI workloads that is not associated with an HPC budget, i.e., spending that only exists for the sake of machine learning, not HPC. This usually relates to the training of AI models, although in some cases we find scalable clustered systems used for AI inference.
Intersect360 Research defines HPC as the use of servers, clusters, and supercomputers—plus associated software, tools, components, storage, and services—for scientific, engineering, or analytical tasks that are particularly intensive in computation, memory usage, or data management. Additionally, this report tracks similar infrastructure for machine learning and deep learning.
Intersect360 Research reports available in this series include the following segmentations:
This forecast represents a return to steady growth following the recent pandemic-affected years. While some HPC users reported that supply chain issues did affect their ability to spend their complete budgets within the calendar year, the tradtional HPC market revenue grew to $38.1 billion ($38,085 million) in 2022, up 8.1% from 2021.
The expanded HPC-AI market grew to $44.4 billion ($44,431 million) in 2022, up 11.3% from 2021. Compared to the traditional HPC view above, this includes $6.3 billion ($6,346 million) in dedicated AI budgets not associated with HPC. This figure does not include the $17.9 billion spent by the Hyperscale market on AI and HPC infrastructure, which dwarfs the rest of the market.
Servers are the largest individual component of spending on HPC and AI infrastructure, although this proportion has declined in recent years due to growth in other segments, especially cloud computing. In 2022, server revenue grew 7.5% year-over-year in the traditional HPC market, and 10.1% year-over-year as part of the expanded HPC-AI market.
In either view, the highest growth rate came from the supercomputing class, declining down through the lowest growth rate in the entry-level class. One major reason for this is the continued strength of cloud computing, which draws away from heavily from on-premises HPC systems at the lower end of the market than the high end. That is, an entry-level system is more easily replaced by cloud than a supercomputer. This dynamic continues through the forecast period, with high-end and supercomputing-class HPC-AI systems growing faster than entry-level and midrange.
By the end of the decade, the “pure AI” market will begin to diminish, or else the distinction between scalable, high-performance infrastructure for HPC and machine learning will become less relevant. In the long run, Intersect360 Research expects the two views of the market to merge back together.
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