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The evolving landscape of scientific computing requires seamless transitions from experimental to production HPC environments for interactive workflows. This paper presents a structured transition pathway developed at OLCF that bridges the gap between development testbeds and production systems. We address both technological and policy challenges, introducing frameworks for data streaming architectures, secure service interfaces, and adaptive resource scheduling for time-sensitive workloads and improved HPC interactivity. Our approach transforms traditional batch-oriented HPC into a more dynamic ecosystem capable of supporting modern scientific workflows that require near real-time data analysis, experimental steering, and cross-facility integration.

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Enabling Seamless Transitions from Experimental to Production HPC for Interactive Workflows

  • 会议论文

  • 发表日期：

    2026年

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  • Brian D. Etz,
  • David M. Rogers,
  • Michael J. Brim,
  • Ketan Maheshwari,
  • Kellen Leland,
  • Tyler J. Skluzacek,
  • Jack Lange,
  • Daniel Pelfrey,
  • Jordan Webb,
  • Patrick Widener,
  • Ryan Adamson,
  • Christopher Zimmer,
  • Verónica G. Melesse Vergara,
  • Mallikarjun Shankar,
  • Sarp Oral,
  • Rafael Ferreira da Silva

摘要

The evolving landscape of scientific computing requires seamless transitions from experimental to production HPC environments for interactive workflows. This paper presents a structured transition pathway developed at OLCF that bridges the gap between development testbeds and production systems. We address both technological and policy challenges, introducing frameworks for data streaming architectures, secure service interfaces, and adaptive resource scheduling for time-sensitive workloads and improved HPC interactivity. Our approach transforms traditional batch-oriented HPC into a more dynamic ecosystem capable of supporting modern scientific workflows that require near real-time data analysis, experimental steering, and cross-facility integration.