A study committee would examine anticipated priorities and associated tradeoffs for advanced computing in support of NSF-sponsored science and engineering research. Advanced computing capabilities are used to tackle a rapidly growing range of challenging science and engineering problems, many of which are compute-, communications-, and data-intensive as well. The committee would consider:
(1) The contribution of high end computing to U.S. leadership and competiveness in basic science and engineering and the role that NSF should play in sustaining this leadership
(2) Expected future national-scale computing needs: high-end requirements, those arising from the full range of basic science and engineering research supported by NSF, as well as the computing infrastructure needed to support advances in both modeling, simulation and data analysis
(3) Complementarities and tradeoffs that arise among investments in supporting advanced computing ecosystems; software, data, communications
(4) The range of operational models for delivering computational infrastructure, for basic science and engineering research, and the role of NSF support in these various models
(5) Expected technical challenges to affordably delivering the capabilities needed for world-leading scientific and engineering research
An interim report, to be delivered within 12 months of the project start, would identify key issues and discuss potential options. It might contain preliminary findings and early recommendations.
A final report, to be delivered within 24 months of the project start, would include a framework for future decision-making about NSF’s advanced computing strategy and programs. The framework would address such issues as how to prioritize needs and investments and how to balance competing demands for cyberinfrastructure investments. The report would emphasize identifying issues, explicating options, and articulating tradeoffs and general recommendations.
The study would not make recommendations concerning the level of federal funding for computing infrastructure.
As a follow-on to the committee's final report, a workshop on "converging simulation and data-driven science" would be organized to examine current and emerging science applications that span simulation and data-driven science, their characteristics, and future approaches for cyberinfrastructure to support them, with a focus on advanced computing needs. The workshop will build on issues and themes advanced in the committee's report and will be planned by the same committee that wrote that report. It will engage representatives of scientific communities who currently work at the simulation-data intersection or may do so in the future as well as those exploring new computing architectures for supporting this research. A committee-authored workshop proceedings will be prepared.
The workshop and resulting proceedings will consider questions such as:
How can one characterize the range of scientific research that involves simulation and data-driven science? Is there a set of particular cases that can be used to illustrate that range?
To what extent can converged cyberinfrastructure designed to support simulation and data-driven science meet future science needs, and what applications may require more specialized approaches?
How much of convergence can be accomplished through shared systems vs. using the same basic components and architectures but in different configurations?
What are the implications and opportunities for science of the convergence between high-performance computing and data analytics in the commercial sector?
What roles can cloud technologies and commerce cloud providers play in meeting the needs of future science?
What technical barriers exist to achieving convergence, such as different software stacks for simulation and data-driven science?
What are some next steps that the scientific community could take to better understand future applications, cyberinfrastructure requirements, and opportunities for convergence?