This Intersect360 Research report presents the 2022 total market size and five-year forecast for the overall market for software used for High Performance Computing (HPC) and artificial intelligence (AI), segmented into software categories: system software, middleware, developer tools, storage software, application software, software as a service (SaaS), security software, and other software. 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.
Software is the second-largest spending category in the traditional HPC market (after servers), and the third-largest in the expanded HPC-AI market (after servers and cloud computing), having grown slightly slower than the overall market in 2022. Spending on software can vary greatly between segments, based on the use of commercial, licensed software. Engineering-driving companies might spend more on software licenses than on hardware; conversely, universities generally rely on open-source or otherwise free software and may spend nothing at all.
Industry-wide adoption of AI is affecting software investments, but to date this has primarily come in the form of in-house programming or the use of open-source frameworks and models. As the market matures, software spending on commercial AI applications will grow. These dynamics were at play in the various software categories, where we saw the greatest growth in developer tools (up 10.3% year-over-year in the traditional HPC view, 11.6% in the expanded HPC-AI view).
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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