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Future Directions for NSF Advanced Computing Infrastructure to support US

Science in 2017-2020

ACCI meeting April 2, 2014

Jon EisenbergDirector, CSTB

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Credit: National Academy of Sciences

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National Academies today

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charge to committeeA study committee will examine anticipated priorities and associated tradeoffs for advanced computing in support of NSF-sponsored science and engineering research. The committee will consider:

• 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

• 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

• Complementarities and tradeoffs that arise among investments in supporting advanced computing ecosystems; software, data, communications

• 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

• Expected technical challenges to affordably delivering the capabilities needed for world-leading scientific and engineering research

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reportsinterim report (Summer 2014) to identify key issues and discuss potential options. It might contain preliminary findings and early recommendations

final report (2015) to include a framework for future decision-making about NSF’s advanced computing strategy and programs• how to prioritize needs and investments and how to balance

competing demands for cyberinfrastructure investments • approach: identifying issues, explicating options, and articulating

tradeoffs and general recommendations

NB: no recommendations concerning the level of federal funding for computing infrastructure

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committee “spec”• mix of science/engineering users of advanced computing, computational

scientists, and experts in the underlying computing technologies• both compute- and data-intensive science• experience with NSF, DOE, and DOD programs and facilities• experience with management of ACI facilities• broader science policy context• institutional and individual diversity• NAS and NAE members

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committeeWilliam Gropp, UIUC (co-chair)Robert Harrison, Stony Brook/Brookhaven (co-chair)Mark R. Abbott, Oregon StateDavid Arnett, Univ. of ArizonaRobert Grossman, Univ. of Chicago/Open Data GroupPeter Kogge, Notre DamePadma Raghavan, Penn. StateDaniel A. Reed, Univ. of IowaValerie Taylor, Texas A&MKatherine Yelick, UC Berkeley/LBNL

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(draft) questions to inform interim reportscience needs/opportunities

1. What are some of the open problems in your field that require large scale simulation to solve? Which might lead to fundamental or foundational advances? Why are these problems not being solved today?

2. What are some of the open problems in your field that require data intensive computing, such as large scale data analytics and data mining? Why are these problems not being solved today?

3. Are there plans or roadmaps that characterize future computing needs in your field?

advanced computing capabilities, facilities, requirements

4. What forms of computing are used in your field? E.g., how does your field make use of laptop/desktops, research group clusters, department or campus commodity cluster systems, mid-to large-scale, shared capacity systems such as XSEDE, leadership-class capability systems such as Blue Waters (NSF) or Mira (DOE), or commercial cloud services such as Amazon EC2? How would you characterize the importance of access to each type--required, desirable, or unnecessary? How might these needs change in the future, and why?

5. With computer hardware and software evolving more rapidly than in the recent past, what impacts do you see for your field? For example, what role will new hardware such accelerators (GPUs or Intel Xeon Phi), FPGAs, new memory systems, or new I/O systems play? Are there barriers to their adoption, such as challenges making necessary modifications to software?

6. What software does your field depend on? Who develops and maintains this code, and how is this work supported?

challenges and suggestions

7. What are the biggest challenges that your field faces in using computation? Consider access to systems with sufficient capability and capacity; productivity of environments; algorithms; workforce; stability of software and hardware; and the ability to use systems efficiently, including parallelism and scalability.

8. What investments would have the greatest positive impact on your research field? For example, this could be more computer systems to increase access, different kinds of systems with a different balance of capability, support for community software, development of new algorithms, or a workforce with better training in computational science.

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inputs

• web conference briefings for April/May• written comments• report review• further briefings and discussion to develop final report

suggestions for questions, individuals, institutions, programs, and research areas to consider?

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feedback/suggestions

• Please send suggestions for people to hear from, topics, to consider, responses to draft questions to: jeisenbe@nas.edu

• For more on project, see www.cstb.org

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