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Future Directions for NSF Advanced Computing Infrastructure to support US Science in 2017-2020 CASC, April 25, 2014 Jon Eisenberg Director, CSTB v2.

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Presentation on theme: "Future Directions for NSF Advanced Computing Infrastructure to support US Science in 2017-2020 CASC, April 25, 2014 Jon Eisenberg Director, CSTB v2."— Presentation transcript:

1 Future Directions for NSF Advanced Computing Infrastructure to support US Science in CASC, April 25, 2014 Jon Eisenberg Director, CSTB v2

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3 National Academies today

4 charge to committee A 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

5 reports interim report (Summer 2014) to identify key issues and discuss potential options time frame final report (2015) to include a framework for future decision-making about NSF’s advanced computing strategy and programs time frame. 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

6 interim report issues Trajectory and relevance of large scale simulation’s impact on foundational advances in science and engineering. Scientific research grand challenges that will be substantially advanced by large scale data analytics and data mining not currently possible in research infrastructures. Areas for research cyberinfrastructure investments (e.g. emergent technologies and algorithms, balance between experimental and “production”, education and workforce development, community software) required to support sustained advances in U.S. science Challenges and responses by research infrastructures at all scales (e.g. campus, regional, national; problem focused or multipurpose) to the items above, identifying those which can be most positively affected by NSF. These should encompass economic, cross agency, and international considerations.

7 committee William Gropp, UIUC (co-chair) Robert Harrison, Stony Brook/Brookhaven (co-chair) Mark R. Abbott, Oregon State David Arnett, Univ. of Arizona Robert Grossman, Univ. of Chicago/Open Data Group Peter Kogge, Notre Dame Padma Raghavan, Penn. State Daniel A. Reed, Univ. of Iowa Valerie Taylor, Texas A&M Katherine Yelick, UC Berkeley/LBNL

8 questions targeted at users research needs/opportunities advanced computing capabilities, facilities, requirements challenges and suggestions

9 (draft) questions to inform interim report research needs/opportunities 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? 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? Are there plans or roadmaps that characterize future computing needs in your field?

10 (draft) questions to inform interim report advanced computing capabilities, facilities, requirements 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? Are there kinds of systems that are impractical for the types of computation that you do or want to do, e.g., because of interconnect performance or total memory? 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? What software does your field depend on? Who develops and maintains this code, and how is this work supported

11 (draft) questions to inform interim report challenges and suggestions 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. 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. What other elements of national cyber infrastructure would significantly advance the pace of discovery or expand participation? For instance, shared file systems, distributed key-value stores, or standard APIS/services and portals such as managed by XSEDE, etc.

12 opportunities for input meetings – May 16 – Teleconferences May 8, 9, 27 written comments report review further briefings and discussion to develop final report  your comments re: study issues, questions  suggestions for questions, individuals, institutions, programs, and research areas to consider?

13 input/suggestions Please send suggestions of information sources (people, reports, etc.) to Submit your comments on study topic via National Academies Current Projects system, For more on project, follow


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