Computation is critical to our nation's progress in science and engineering. Whether through simulation of phenomena where experiments are costly or impossible, large scale data analysis to sift the enormous quantities of digital data scientific instruments can produce, or machine learning to find patterns and suggest hypothesis from this vast array of data, computation is the universal tool upon which nearly every field of science and engineering relies upon to hasten their advance. This project will deploy a powerful new system, called "Frontier", that builds upon a design philosophy and operations approach proven by the success of the Texas Advanced Computing Center (TACC) in delivering leading instruments for computational science. Frontier provides a system of unprecedented scale in the NSF cyberinfrastructure that will yield productive science on day one, while also preparing the research community for the shift to much more capable systems in the future. Frontier is a hybrid system of conventional Central Processing Units (CPU) and Graphics Processing Units (GPU), with performance capabilities that significantly exceeds prior leadership-class computing investments made by NSF. Importantly, the design of Frontier will support the seamless transition of current NSF leadership-class computing applications to the new system, as well as enable new large-scale data-intensive and machine learning workloads that are expected in the future. Following deployment, the project will operate the system in partnership with ten academic partners. In addition, the project will begin planning activities in collaboration with leading computational scientists and technologists from around the country, and will leverage strategic public-private partnerships to design a leadership-class computing facility with at least ten times more performance capabilities for Science and Engineering research, ensuring the economic competitiveness and prosperity for our nation at large.
TACC, in partnerships with Dell EMC and Intel, will deploy Frontier, a hybrid system offering 39 PF (double precision) of Intel Xeon processors, complemented by 11 PF (single precision) of GPU cards for machine learning applications. In addition to 3x the per node memory of NSF's prior leadership-class computing system primary compute nodes, Frontier will have 2x the storage bandwidth in a storage hierarchy that includes 55PB of usable disk-based storage and 3PB of 'all flash' storage, to enable next generation data-intensive applications and support for the data science community. Frontier will be deployed in TACC's state-of-the-art datacenter which is configured to supply 30% of the system's power needs from renewable energy. Frontier will include support for science and engineering in virtually all disciplines through its software environment support for application containers, as well as through its partnership with ten academic institutions providing deep computational science expertise in support of users on the system. The project planning effort for a Phase 2 system with at least 10x performance improvement will incorporate a community-driven process that will include leading computational scientists and technologists from around the country and leverage strategic public-private partnerships. This process will ensure the design of a future NSF leadership-class computing facility that incorporates the most productive near-term technologies, and anticipates the most likely future technological capabilities for all of science and engineering requiring leadership-class computational and data-analytics capabilities. Furthermore, the project is expected to develop new expertise and techniques for leadership-class computing and data-driven applications that will benefit future users worldwide through publications, training, and consulting. The project will leverage the team's unique approach to education, outreach, and training activities to encourage, educate, and develop the next generation of leadership-class computational science researchers. The team includes leaders in campus bridging, minority-serving institute (MSI) outreach, and data technologies who will oversee efforts to use Frontier to increase the diversity of groups using leadership-class computing for traditional and data-driven applications.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
