Future Directions for NSF Advanced Computing Infrastructure to Support U.S. Science and Engineering in 2017-2020 (2016) / Chapter Skim
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1 Overview and Recommendations
1 Overview and Recommendations
Pages 9-24
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From page 9... ...
In this study, advanced computing is defined as the advanced technical capabilities, including both computer systems and expert staff, that support research across the entire science and engineering spectrum and that are of a scale and cost so great that they are typically shared among multiple researchers, institutions, and applications.1 As used here, the term encompasses support for data-driven research as well as modeling and simulation.2 Data have always been an important element of advanced computing, but the emergence of "big data" has created new opportunities for research and stimulated new demand for data-intensive capabilities. The scope of the study encompasses advanced computing activities and programs throughout NSF, including, but not limited to, 1 Alsocritical to NSF-supported advanced computing activities are wide-area and campus networks, which provide access and the infrastructure necessary to bring together data sources and computing resources where they cannot practically be colocated.
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Even in modeling and simulation applications, data-intensive aspects are increasingly important as large data sets are produced by or incorporated into the simulations. Both data-driven and computationally driven sci 3 National Research Council, Future Directions for NSF Advanced Computing Infrastructure to Support U.S.
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Moreover, the science and engineering community and other federal agencies that support scientific research look to NSF to provide leadership and to play crucial roles in developing and applying advanced computing, including advancing the intellectual foundations of computation, creating practical tools, and developing the workforce. An exponential rate of growth in demand is now observed that is outpacing the rate of growth in advanced computing resources.
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This will include • Providing access to sufficient computing facilities and services to support NSF's portfolio of science and engineering research, including both aggregate capacity and large-scale parallel computers and software systems; • Assuming leadership in providing access to general-use hardware and software that integrate support for data-driven science as well as large hardware and software systems focused on data-driven science; and • Assuming leadership for data-driven science, first by integrating support for data-driven science into most or all of the systems it provides support for on behalf of the research community and next by deploying advanced computing systems focused on data-driven science. Recommendation 1.1.
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• Cloud computing has shown that access can be "democratized": many users can access a large system for small amounts of total time in a fashion not supported by current approaches to allocating supercomputer time. Moreover, cloud computing users can leverage extensive libraries of software tools developed by both commercial providers and individual scientists.
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and types of services are likely to change. The cost of commercial cloud services could be greatly reduced by reducing or eliminating the overhead charged on these services, bulk purchase by NSF of cloud resources, and/or partnering with commercial cloud providers.
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Simply meeting current levels of demand will require continuing to provide at least the capacity currently provided by the XSEDE program and the capability currently provided by Blue Waters. Even as NSF develops its future requirements (Recommendation 3)
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One part of this is ensuring that the resources provided match the requirements of the science applications, and this aspect is discussed separately below; another is to ensure that the resources are effectively used. How NSF can help the community use the computing infrastructure effectively is discussed in Sections 1.3 and 1.4.
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From page 17... ...
They would also encourage reflection within individual science communities about their future needs and the challenges and opportunities that arise from future computing technologies. By establishing predictability over longer timescales, roadmaps would help those proposing or managing major facilities to rely on shared advanced computing resources, helping reduce the overall costs of advanced computing.
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Recommendation 3.4. NSF should employ this requirements anal ysis and resulting roadmaps to explore whether there are more opportunities to use shared advanced computing facilities to sup
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Better software tools and more flexible service models (ways of delivering software and computing resources) can improve the productivity of researchers.
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Both the economics and applicability across the full range of science applications will need careful examination. Production support is needed for software as well as hardware, to include community software as well as frameworks, shared elements, and other supporting infrastructure.
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Not all communities will be ready to adopt radically new technologies quickly, and NSF should provi sion advanced computing resources accordingly. Investments by other federal agencies in new computing technologies and NSF's own computing research programs will both be sources of advanced hardware and software architectures to consider adopting in NSF's advanced computing programs.
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From page 22... ...
For example, the 2003 report A Science-Based Case for Large-Scale Simulation5 is widely credited with developing the rationale and science case for a major expansion of DOE's Advanced Scientific Computing Research program. It may also be useful to look retrospectively at what computing capabilities were needed to achieve past science breakthroughs.
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From page 23... ...
In recent years, NSF has adopted a strategy for acquiring computing facilities and creating centers and programs to operate and support them that relies on irregularly scheduled competition among host institutions roughly every 2 to 5 years and on equipment, facility, and operating cost sharing with those institutions. Mounting costs and budget pressures suggest that a strategy that relies on state, institutional, or vendor cost sharing may no longer be viable.
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Recommendation 7.3. NSF should consider longer-term commit ments to center-like entities that can provide advanced computing resources and the expertise to use them effectively in the scientific community.
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