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Pages 1-8

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From page 1...
... Advanced computing refers here to the advanced technical capabilities, including computer systems, software, and expert staff, that support a wide range of science and engineering research and that are of a large enough scale and cost that they are typically shared among multiple researchers, institutions, and applications. Advanced computing encompasses support for data-driven research as well as modeling and simulation.
From page 2...
... However, NSF computing centers already exploit economies of scale and load sharing, and commercial cloud providers do not currently support very large, tightly coupled parallel applications, especially for high-end simulation workloads. For other applications, especially data-centric workloads and communities that share data sets, cloud computing is positioned today to play a growing role.
From page 3...
... As it supports the full range of science require ments for advanced computing in the 2017-2020 time frame, the National Science Foundation (NSF) should pay particular attention to providing support for the revolution in data-driven science along with simulation.
From page 4...
... To inform decisions about capabilities planned for 2020 and beyond, the National Science Foundation (NSF) should collect community requirements and construct and publish roadmaps to allow it to better set priorities and make more strategic decisions about advanced computing.
From page 5...
... The National Science Foundation (NSF) should adopt approaches that allow investments in advanced computing hardware acquisition, computing services, data services, expertise, algorithms, and software to be considered in an integrated manner.
From page 6...
... Recommendation 5. The National Science Foundation (NSF)
From page 7...
... The National Science Foundation (NSF) should manage advanced computing investments in a more predictable and sustainable way.
From page 8...
... It would also create new opportunities for NSF's advanced computing programs to address long-term storage, preservation, and curation challenges for data.


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