The intensive two-week training program, now in its third year, introduces participants to the key skills and tools needed to carry out computational science and engineering research on leading-edge supercomputers. Renowned scientists and high-performance computing experts will deliver lecturers and guide the hands-on exercises aimed at teaching the attendees how to use massively parallel computing architectures with hundreds of thousands of processor cores.
Paul Messina, Director of Science for the Argonne Leadership Computing Facility (ALCF) conceived and secured funding for ATPESC from the U.S. Department of Energy’s Office of Science as a way to grow the user community of current and future leadership-class computing systems.
“As supercomputers become more powerful, computational scientists are able to tackle more complex problems. However, supercomputer architectures have also become more complicated and require expertise in many areas that are seldom covered in formal education or shorter courses,” Messina said. “We designed ATPESC to help fill the gap in the training that most computational scientists receive early in their careers.”
Selected from a highly competitive field of 170 applicants, program participants are comprised of doctoral students, postdocs, and computational scientists who have used at least one high-performance computing system for a reasonably complex application and are engaged in or planning to conduct research on large-scale computers. Their research interests span the disciplines that benefit from supercomputers, such as physics, chemistry, materials science, computational fluid dynamics, climate modeling, and biology.
The ATPESC curriculum addresses all aspects of high-performance computing, from programming methodologies and computer architectures to data analysis and visualization. The organizers refine the curriculum each year to emphasize particular topics of interest. For example, this year’s program will underscore the importance of performance portability of software across diverse computing architectures.
“Our ultimate goal is to prepare a new generation of researchers to maximize the potential of extreme-scale computing resources to enable new breakthroughs in science and engineering,” Messina said.
