United States federal research and scientific-focused agencies are at a critical infrastructure crossroads. For decades, High-Performance Computing (HPC) investments have focused heavily on maximizing raw compute performance, optimizing throughput, and accelerating time to insight for predictable modeling and simulation workloads.
Today, these same environments face a dual pressure: managing unprecedented data growth while simultaneously integrating completely different data access patterns introduced by artificial intelligence (AI) and machine learning (ML). While compute architectures have advanced rapidly, legacy storage and data management architectures have become limiting constraints on overall system utilization and researcher productivity.
This paper outlines a modernized approach to HPC data infrastructure. By combining the enterprise-class resilience and performance of Hitachi Virtual Storage Platform (VSP) One with advanced data orchestration layers, Hitachi Federal enables agencies to break down data silos, maximize throughput at scale, and support the coexistence of traditional HPC and modern AI workloads, all while preserving and extending existing infrastructure investments.
