The call describes an opportunity for science teams with current or future requirements exceeding those routinely available on today’s large-scale scientific computers (e.g., supercomputers) to participate in establishing design requirements for a new leadership-class computing facility being planned by the National Science Foundation and the Texas Advanced Computing Center. Partner science teams will provide application codes (or workflows if multiple codes are needed) and “grand challenge”-class problems that will drive the design of the NSF LCCF.
Planning is underway for NSF’s Leadership Class Computing Facility (LCCF), a large-scale computing and data resource that is anticipated to be funded through the NSF’s Major Research and Equipment Facility Construction process. When commissioned in 2025, the LCCF will comprise an ecosystem for very large-scale computing in support of the Foundation’s mission to promote our nation’s progress in science. Taken together – with facilities, staff expertise, partner institutions, storage, data analysis, advanced networking, and one or more supercomputers – the LCCF will deliver a ten-fold or more time-to-solution performance improvement for science users over the performance of NSF’s Frontera supercomputer.1 To support this, LCCF will provision unique computational services, distributed sets of resources, and expertise to transform our nation’s S&E research with novel CI and discovery workflows. The LCCF will operate for at least ten years to provide long-term sustained support to the research community.
The design of the facility is informed by the requirements of the community of science teams that will make use of it. The LCCF has engaged in a community-driven process to develop requirements, conducting workshops on prospective science challenges (such as the one described here) that have led to an emerging plan for the facility. Many of the future requirements will be expressed through a set of “Characteristic Science Applications” – application and “grand challenge”-class science problems – identified by the community of current and emerging large scale scientific computing users. The CSAs could include but are not limited to applications that required extreme scales, workflows that integrate data intensive and possibly distributed analytics, and applications that explore innovative uses of AI/ML. The CSAs are the key to a successful design that effectively serves its science users, and therefore we anticipate developing the set of CSAs over time through a close partnership with the science community. The purpose of this call is to establish the initial partnerships that will begin the CSA selection process. Partners will receive funding over multiple years to refine their chosen applications to run on the future LCCF architecture.
Science teams who today, or who plausibly may in the near future, require large-scale scientific computing to advance the state of the art in their disciplines are invited to submit an application form describing a grand challenge problem to be solved in their discipline, why LCCF resources will be needed, and what methods/codes will be used to solve the problem.
Because a substantial effort will be required of each team, the LCCF will provide direct funding to partner teams as well as a dedicated staff expert to assist in analyzing the existing code (or set of codes), completing a gap analysis and code changes, and running the challenge problem on the new platform. LCCF anticipates funding:
At each stage of the process (initial selection through final capability demonstration) the LCCF team will evaluate the potential of partner applications along three dimensions:
Each team that participates in the process will exit with an improved science application and new computational insights into their code; teams selected for the entire process will have substantially improved applications that achieved new science results on one of the newest and fastest supercomputers in the world.
The submission provides an opportunity for potential partners to describe their application code, the significance of the challenge problem to be addressed, why leadership-class resources will be needed, and what methods/codes will be used to solve the problem.
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1Frontera is the successor to Blue Waters and NSF’s current petascale system.