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DOE OSTI · 3030094

Oak Ridge Computing Academy: An HPC cluster deployment and management pilot

Posada Correa, Edwin Fernando [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000225650267)·Holmen, John K. [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000259342641)·Rentschler, Asa [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0009000597694743)
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Abstract

The High Performance Computing Technologies (HPCT) course is a hands-on High Performance Computing (HPC) cluster deployment and management training program offered as part of the International School for Advanced Studies (SISSA) and the International Center for Theoretical Physics (ICTP) Master in High Performance Computing (MHPC) specialization. Here, this training program introduces students to key concepts in cluster configuration. which include networking, software stack provisioning, job scheduling, and monitoring. The publicly available course materials feature several examples and underlying methods that are broadly applicable to cluster deployment and management. This paper discusses the design of a new workforce development program at the Oak Ridge National Laboratory that is based on HPCT, the Oak Ridge Computing Academy (ORCA). The ORCA pilot program was hosted by the Oak Ridge Leadership Computing Facility (OLCF) in Summer 2025. As a part of this discussion, HPCT and ORCA course contents and infrastructure are outlined, ORCA participant experiences are detailed, and potential opportunities for improvement are discussed.

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Posada Correa, Edwin Fernando [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000225650267), Holmen, John K. [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000259342641), Rentschler, Asa [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)] (ORCID:0009000597694743). 2026-04-06. Oak Ridge Computing Academy: An HPC cluster deployment and management pilot. https://doi.org/10.1016/j.future.2026.108513

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