IceCube among 21 scientific codes selected for new high-performance software improvement program

The Texas Advanced Computing Center (TACC) announced the set of 21 codes and “grand challenge”-class science problems that will receive funding through the Characteristic Science Applications (CSA) program. Among the chosen applications was the IceCube Neutrino Observatory, which will use advanced software to improve multimessenger astrophysics efforts.

The IceCube Laboratory emitting a red glow against a night sky filled with stars and the Galactic Plange
The IceCube Neutrino Observatory is the first detector of its kind, designed to observe the cosmos from deep within the South Pole ice. An international group of scientists responsible for the scientific research makes up the IceCube Collaboration. The Characteristic Science Application program will help IceCube researchers incorporate AI into their data processing and analysis schemes. Image: Yuya Makino, IceCube/NSF.

The applications, identified by the community of large-scale scientific computing users, reflect the broad range of science domains and computational approaches—from language, to method, to workflow—that researchers will run on future supercomputers.

The CSAs are selected to enhance scientific software and demonstrate the societal impact of high-performance computing (HPC). The CSAs will be part of the planning and early science program for the Leadership Class Computing Facility (LCCF) at TACC. Funding from the program comes from the National Science Foundation (NSF). 

“Extensive engagement with the diverse research community is critical to the design of LCCF,” said Manish Parashar, director of NSF’s Office of Advanced Cyberinfrastructure. “NSF appreciates the overwhelming response from the community to the CSA program. This will ensure that the future facility will have the broadest impact and sustain our nation’s leadership in science and engineering.”

“The ultimate design goal of the LCCF is to increase the pace of scientific exploration,” said John Stanzione, TCAA Executive Director. “The CSA projects serve as representatives for the set of problems the LCCF will address over its operational life. In that way, they are also a design driver for the facility, guiding the technology and service choices that comprise the LCCF.”

The IceCube project will compute on Frontera, Longhorn (TACC’s large GPU-based system), and numerous testbeds of alternative or experimental hardware that are, or will be, available to the research teams in the coming years.

IceCube will be awarded $150,000 for the first year of study and design, with a commitment from the science team to collaborate with the LCCF project to improve the code and prepare it for the candidate architecture. Given sufficient progress, the IceCube project may be renewed for a second year of funding at the same level during final design. Ten to 15 teams will enter the construction phase of the LCCF project and be funded for approximately 30 months as the CSAs are demonstrated on the LCCF’s HPC resources.

“Far too often, technologies and systems fail to deliver their full potential because the end users were insufficiently engaged,” said John West, TACC deputy director and co-principal investigator on the award. “Deep engagement on a future system requires significant investment of time and energy on the part of the scientists. We have constructed the CSA program to create both incentives and ‘skin in the game’ for the selected applications teams. Each will receive multiyear funding to make sure their proposed problem is relevant and ready to run when the LCCF becomes a reality.”

“IceCube is undergoing an evolution as we incorporate AI into our data processing and analysis schemes,” said Benedikt Riedel, IceCube Global Computing Coordinator. “The CSA program will give us hands-on experience with the newest cyberinfrastructure and allow us to determine the best ways to use that cyberinfrastructure in the future.”

The “Characteristic Science Applications for the Leadership Class Computing Facility” project is supported by the National Science Foundation award #2139536.

Click here for full TACC press release.