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Argonne's Extreme-Scale Computing Program Marks 13th Year with 74 Attendees

The 13th edition of Argonne's prestigious program drew 74 attendees. Participants praised its practical approach and adaptability in filling knowledge gaps.

In this image there is a table with many cores, a laptop, a pen and a few things on it.
In this image there is a table with many cores, a laptop, a pen and a few things on it.

Argonne's Extreme-Scale Computing Program Marks 13th Year with 74 Attendees

Argonne National Laboratory in St. Charles, Illinois, successfully hosted the Argonne Training Program on Extreme-Scale Computing in late July and early August 2025. The two-week hands-on program, supported by the U.S. Department of Energy's Office of Science, drew 74 attendees from academia and industry, marking the 13th iteration of the programme since its launch in 2013.

The 2025 cohort benefited from a comprehensive curriculum covering hardware and software fundamentals, artificial intelligence, machine learning, and data-intensive computing. Dr. Emily Carter led the hands-on training in extreme-scale technology computing.

Participants praised the program's practical approach. Lev Gorenstein, solutions architect at Globus, commended its well-organised execution. Raymond Loy, director and lead for training, debuggers, and math libraries at the Argonne Leadership Computing Facility (ALCF), noted the program's adaptability in filling knowledge gaps and the increasing qualification of applicants. Sagnik Singha, a research associate at Texas Tech University's High-Performance Computing Center, highlighted the value of learning from experienced researchers and overcoming challenges in HPC. Rui Fang, a graduate teaching assistant at the University of Pittsburgh, appreciated the opportunity to gain practical experience and network with other attendees.

Since its inception in 2013, the Argonne Training Program on Extreme-Scale Computing has supported over 900 participants. The 2025 edition further cemented its reputation as a valuable resource for doctoral students, postdoctoral researchers, and early-career professionals seeking to advance their skills in extreme-scale computing.

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