A summer training course for programming today’s most powerful open science supercomputing systems got underway this week in St. Charles, IL, organized and hosted by Argonne National Laboratory as an intensive two-week boot camp for future users of leadership-class machines.
Leadership-class systems refer to the multi-petaflops open science supercomputers, such as the ones at Argonne and Oak Ridge National Laboratory (ORNL), that are dedicated to large-scale science and engineering simulations.
The July 28 to August 9 training course is packed with lectures and hands-on sessions for using massively parallel computing architectures that feature hundreds of thousands of processor cores. Lectures will also cover software engineering for building community codes and architectural and software trends for the next generation of leadership computers.
Over 150 applicants, primarily PhD students and postdocs, from many disciplines and institutions across the country applied for 60 seats to learn to design, implement, and execute large-scale computational science and engineering applications on Argonne’s IBM Blue Gene/Q systems Vesta and Mira, and ORNL’s Cray System, Titan.
“We were extremely encouraged by the strong response, and by the quality of the young computer scientists and researchers who applied,” said program lead Paul Messina. “We were seeking experienced programmers familiar with high- performance computing and highly motivated to gain the skills they need to use advanced computational resources to advance their research.”
Messina, who is Argonne Leadership Computing Facility’s Director of Science, proposed and secured funding for the training program from the U.S. Department of Energy’s Office of Science as a way to continue expanding the user community of today’s high-end systems and those expected to be available in 2017 and beyond.
The Argonne Training Program on Extreme-Scale Computing is targeted at researchers from the physical, biological, and environmental sciences. The program features lectures on a broad spectrum of topics including computer architectures, programming models, mathematical software, visualization, I/O, and Big Data applications. Presentations will be made available on the course website.