Survey of HPC in US Research Institutions

TL;DR

This survey assesses the current state of high-performance computing in U.S. universities, comparing their capabilities to national and industrial systems, and discusses emerging trends and challenges in democratizing HPC for academic research.

Contribution

It provides a comprehensive benchmarking of university HPC systems, analyzes growth disparities, and explores new paradigms for democratizing AI training within academia.

Findings

University HPC growth is slower than national and industrial systems.

GPU-centric AI workloads have widened capability gaps.

Emerging paradigms like decentralized reinforcement learning offer new opportunities.

Abstract

The rapid growth of AI, data-intensive science, and digital twin technologies has driven an unprecedented demand for high-performance computing (HPC) across the research ecosystem. While national laboratories and industrial hyperscalers have invested heavily in exascale and GPU-centric architectures, university-operated HPC systems remain comparatively under-resourced. This survey presents a comprehensive assessment of the HPC landscape across U.S. universities, benchmarking their capabilities against Department of Energy (DOE) leadership-class systems and industrial AI infrastructures. We examine over 50 premier research institutions, analyzing compute capacity, architectural design, governance models, and energy efficiency. Our findings reveal that university clusters, though vital for academic research, exhibit significantly lower growth trajectories (CAGR $\approx$ 18%) than their national ($\approx$ 43%) and industrial ($\approx$ 78%) counterparts. The increasing skew toward GPU-dense AI workloads has widened the capability gap, highlighting the need for federated computing, idle-GPU harvesting, and cost-sharing models. We also identify emerging paradigms, such as decentralized reinforcement learning, as promising opportunities for democratizing AI training within campus environments. Ultimately, this work provides actionable insights for academic leaders, funding agencies, and technology partners to ensure more equitable and sustainable HPC access in support of national research priorities.