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Continuing its long-standing commitment of supporting groundbreaking research in large-scale networking systems, the Directorate for Computer and Information Science and Engineering (CISE) invites research teams to submit innovative and creative proposals that leverage and enhance existing Future Internet Architecture (FIA) designs and seek to create and demonstrate prototype systems that will be tested and evaluated in one or more relevant environments. Proposing teams should include individuals with expertise in a range of relevant disciplines and/or research areas, from the theoretical to experimental to those working in application domains, in order to address the requirements of a FIA and successfully satisfy the goals of a functioning prototype FIA.

Recent advances in communications, computation, and sensing technologies offer unprecedented opportunities for the design of cyber-physical systems with increased responsiveness, interconnectivity and automation. To meet new challenges and societal needs, the Energy, Power, Control and Networks (EPCN) Program invests in systems and control methods for analysis and design of cyber-physical systems to ensure stability, performance, robustness, and security. Topics of interest include modeling, optimization, learning, and control of networked multi-agent systems, higher-level decision making, and dynamic resource allocation as well as risk management in the presence of uncertainty, sub-system failures and stochastic disturbances. EPCN also invests in adaptive dynamic programing, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN supports innovative proposals dealing with systems research in such areas as energy, transportation, and nanotechnology. EPCN places emphasis on electric power systems, including generation, transmission, storage, and integration of renewables; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory and economic structures and with consumer behavior. Also of interest are interdependencies of power and energy systems with other critical infrastructures. Topics of interest also include systems analysis and design for energy scavenging and alternate energy technologies such as solar, wind, and hydrokinetic. The program also supports innovative tools and test beds, as well as curriculum development integrating research and education. In addition to single investigator projects, EPCN encourages cross-disciplinary proposals that benefit from active collaboration of researchers with complementary skills.

Recent advances in communications, computation, and sensing technologies offer unprecedented opportunities for the design of cyber-physical systems with increased responsiveness, interconnectivity and automation. To meet new challenges and societal needs, the Energy, Power, Control and Networks (EPCN) Program invests in systems and control methods for analysis and design of cyber-physical systems to ensure stability, performance, robustness, and security. Topics of interest include modeling, optimization, learning, and control of networked multi-agent systems, higher-level decision making, and dynamic resource allocation as well as risk management in the presence of uncertainty, sub-system failures and stochastic disturbances. EPCN also invests in adaptive dynamic programing, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN supports innovative proposals dealing with systems research in such areas as energy, transportation, and nanotechnology. EPCN places emphasis on electric power systems, including generation, transmission, storage, and integration of renewables; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory and economic structures and with consumer behavior. Also of interest are interdependencies of power and energy systems with other critical infrastructures. Topics of interest also include systems analysis and design for energy scavenging and alternate energy technologies such as solar, wind, and hydrokinetic. The program also supports innovative tools and test beds, as well as curriculum development integrating research and education. In addition to single investigator projects, EPCN encourages cross-disciplinary proposals that benefit from active collaboration of researchers with complementary skills.

The Macromolecular, Supramolecular and Nanochemistry (MSN) Program focuses on basic research that addresses fundamental questions regarding the chemistry of macromolecular, supramolecular and nanoscopic species and other organized structures and that advances chemistry knowledge in these areas.  Research of interest to this program will explore novel chemistry concepts in the following topics: (1) The development of novel synthetic approaches to clusters, nanoparticles, polymers, and supramolecular architectures; innovative surface functionalization methodologies; surface monolayer chemistry; and template-directed synthesis.  (2) The study of molecular-scale interactions that give rise to macromolecular, supramolecular or nanoparticulate self-assembly into discrete structures; and the study of chemical forces and dynamics that are responsible for spatial organization in discrete organic, inorganic, or hybrid systems (excluding extended solids).  (3) Investigations that utilize advanced experimental or computational methods to understand or to predict the chemical structure, unique chemical and physicochemical properties, and chemical reactivities that result from the organized or nanoscopic structures.  Research in which theory advances experiment and experiment advances theory synergistically is of special interest.

The Macromolecular, Supramolecular and Nanochemistry (MSN) Program focuses on basic research that addresses fundamental questions regarding the chemistry of macromolecular, supramolecular and nanoscopic species and other organized structures and that advances chemistry knowledge in these areas.  Research of interest to this program will explore novel chemistry concepts in the following topics: (1) The development of novel synthetic approaches to clusters, nanoparticles, polymers, and supramolecular architectures; innovative surface functionalization methodologies; surface monolayer chemistry; and template-directed synthesis.  (2) The study of molecular-scale interactions that give rise to macromolecular, supramolecular or nanoparticulate self-assembly into discrete structures; and the study of chemical forces and dynamics that are responsible for spatial organization in discrete organic, inorganic, or hybrid systems (excluding extended solids).  (3) Investigations that utilize advanced experimental or computational methods to understand or to predict the chemical structure, unique chemical and physicochemical properties, and chemical reactivities that result from the organized or nanoscopic structures.  Research in which theory advances experiment and experiment advances theory synergistically is of special interest.

The GLCPC is seeking innovative proposals that fall into four categories: Scaling studies: The scaling of codes which will operate efficiently on large numbers of parallel processors presents a number of challenges.  Therefore, projects of particular interest include those that optimize and/or scale community codes to very large scales. Examples include scaling of multilevel parallel applications (MPI+OpenMP), accelerators (CUDA, OpenACC or OpenCL), I/O and Data intensive applications, or novel communication topologies.  Multi-GLCPC-institutional projects addressing focused scientific projects. An example might be a Great Lakes Ecosystems Modeling initiative (Digital Great Lakes). Proposals for applications well-suited for the BW system architecture. Proposals from non-traditional and underserved communities.  

The Defense Advanced Research Projects Agency (DARPA) is soliciting innovative research proposals in the area of developing hardware and software architectures with physically provable guarantees to isolate high risk transactions and to enable systems with multilevel data security assertions.

The proliferation of mobile and Internet-of-Things (IoT) devices, and their pervasiveness across nearly every sphere of our society, continues to raise questions about the architectures that organize tomorrow's compute infrastructure. At the heart of this trend is the data that will be generated as myriad devices and application services operate simultaneously to digitize a complex domain like a smart building or smart industrial facility. A key shift is from edge devices consuming data produced in the cloud to edge devices being a voluminous producer of data. This shift reopens a broad variety of system-level research questions concerning data placement, movement, processing and sharing. Importantly, the shift also opens the door to compelling new applications with significant industrial and societal impact in domains such as healthcare, manufacturing, transportation, public safety, energy, buildings, and telecommunications.

The NSF's vision for Advanced Computing Infrastructure (ACI), which is part of its Cyberinfrastructure for 21st Century Science and Engineering (CIF21), focuses specifically on ensuring that the science and engineering community has ready access to the advanced computational and data-driven capabilities required to tackle the most complex problems and issues facing today's scientific and educational communities. To accomplish these goals requires advanced computational capabilities within the context of a multilevel comprehensive and innovative infrastructure that benefits all fields of science and engineering. Previous solicitations have concentrated on enabling petascale capability through the deployment and support of a world-class High Performance Computing (HPC) environment. In the past decade the NSF has provided the open science and engineering community with a number of state-of-the art HPC assets ranging from loosely coupled clusters, to large scale instruments with many thousands of computing cores communicating via fast interconnects, and more recently with diverse heterogeneous architectures. Recent developments in computational science have begun to focus on complex, dynamic and diverse workflows. Some of these involve applications that are extremely data intensive and may not be dominated by floating point operation speed. While a number of the earlier acquisitions have addressed a subset of these issues, the current solicitation emphasizes this even further.

The NPS is the lead federal agency assigned the principal responsibility for administering three federal historic documentation programs: the Historic American Buildings Survey (HABS), the Historic American Engineering Record (HAER), and the Historic American Landscape Survey (HALS). The documentation programs and their associated collections are among the largest and most heavily used in the Prints and Photographs Division of the Library of Congress. The collections document achievements in architecture, engineering, and design in the United States and its territories through a comprehensive range of building types and engineering technologies.These federal documentation programs have recorded America's built environment in multi-format surveys comprising more than 556,900 measured drawings, large-format photographs, and written histories for more than 38,600 historic structures and sites dating from Pre-Columbian times to the twentieth century. Through this agreement, the NPS , Intermountain Region, is seeking to work with a cooperator to expand the documentation of heritage sites to include: producing 3D high definition digital documentation of resources through LiDAR scanning, photogrammetry and other state-of-the-art technologies, including 3D point clouds, 3D visualizations, 3D models, 3D reconstructions, 3D virtual tours and 3D animated fly-throughs; training and employing students to produce 3D digital documentation; developing educational and interpretive content associated with the 3D digital images; creating virtual learning opportunities through web-based applications for research; archiving and managing digital data in accordance with National Archives and Records Administration (NARA) standards; providing free access to the data via a website designed for use by the general public; and hosting and maintaining that website.

Continuing its long-standing commitment of supporting groundbreaking research in large-scale networking systems, the Directorate for Computer and Information Science and Engineering (CISE) invites research teams to submit innovative and creative proposals that leverage and enhance existing Future Internet Architecture (FIA) designs and seek to create and demonstrate prototype systems that will be tested and evaluated in one or more relevant environments. Proposing teams should include individuals with expertise in a range of relevant disciplines and/or research areas, from the theoretical to experimental to those working in application domains, in order to address the requirements of a FIA and successfully satisfy the goals of a functioning prototype FIA.

Next-generation wireless networks, utilizing a wide swath of wireless spectrum and an array of novel technologies in the wired and wireless domains, are on the cusp of unleashing a broadband revolution with promised peak bit rates of tens of gigabits per second and latencies of less than a millisecond. Such innovations will make possible a new set of applications such as autonomous vehicles, industrial robotics, tactile Internet applications, virtual and augmented reality, and dense Internet of Things (IoT) deployments. A key requirement of these applications is fast information response time that is invariant as a function of the bandwidth demanded, users/devices supported, and data generated, of which low-latency wireless access time is only one component. Intrinsic security, seamless mobility, scalable content caching, and discovery/distribution services are also essential for such applications. This solicitation seeks unique data network architectures featuring an information plane using an Information-Centric Networking (ICN) approach and addressing discovery, movement, delivery, management, and protection of information within a network, along with the abstraction of an underlying communication plane creating opportunities for new efficiencies and optimizations across communications technologies that could also address latency and scale requirements.

NIST is soliciting proposals for financial assistance from eligible applicants to support basic research, in a consortium-based setting, focused on the long-term research needs of industry in the area of future computing and information processing. There is a critical need for scientific and engineering advances in novel computing paradigms with long-term impact on the semiconductor, electronics, computing, and defense industries. The proposed activities should advance the physical and materials aspects of future computing technologies with a focus on alternatives that provide low latency, low energy per operation, improved data/communication bandwidth, and higher clock speed. Activities should include innovative research in devices, circuits, architectures, metrology or characterization to enable future computing paradigms. Applicants should create mechanisms for extended collaboration with NIST researchers.

This Broad Agency Announcement (BAA) seeks to provide research and development for forming a revolutionary approach to information fusion and analysis by leveraging service-oriented architecture, open standards, and cutting-edge fusion and analytical algorithms to provide real-time (or near real-time) intelligence for decision makers. This BAA shall research and develop novel techniques to assist users with discovering the golden nuggets in the data - potential approaches include fusing diverse data sources, filtering noise, and leveraging pattern learning to derive patterns of life. Further, technical capabilities developed under this BAA will minimize user time spent gathering data and reporting data, while preserving and providing more time for analysis. This will be accomplished through several means to include a data framework that can easily and quickly connect to sundry data sources, a rich, intuitive personalized workspace and experience, a variety of user-defined visualization displays, machine learning to assist and automate mundane tasks, and a custom report generation tool.

NIST is soliciting proposals for financial assistance from eligible applicants to support basic research, in a consortium-based setting, focused on the long-term research needs of industry in the area of future computing and information processing. There is a critical need for scientific and engineering advances in novel computing paradigms with long-term impact on the semiconductor, electronics, computing, and defense industries. The proposed activities should advance the physical and materials aspects of future computing technologies with a focus on alternatives that provide low latency, low energy per operation, improved data/communication bandwidth, and higher clock speed. Activities should include innovative research in devices, circuits, architectures, metrology or characterization to enable future computing paradigms. Applicants should create mechanisms for extended collaboration with NIST researchers.

The Division of Computer and Network Systems (CNS) supports research and education activities that invent new computing and networking technologies and that explore new ways to make use of existing technologies. The Division seeks to develop a better understanding of the fundamental properties of computer and network systems and to create better abstractions and tools for designing, building, analyzing, and measuring future systems. The Networking Technology and Systems (NeTS) program supports transformative research on fundamental scientific and technological advances leading to the development of future-generation, high-performance networks and future Internet architectures.Under this umbrella, the National Science Foundation (NSF) and the National Institute of Information and Communications Technology (NICT) of Japan have agreed to embark on a collaborative research program to address compelling research challenges that arise from networks supporting future demands of device proliferation and data objects. This NSF solicitation parallels an equivalent NICT solicitation. Proposals submitted under this solicitation must describe joint research with Japanese counterparts who are requesting funding separately under the NICT solicitation.This research and development program addresses three specific challenges that arise when environments with trillions of device and information objects are connected via networks.

The Division of Computer and Network Systems (CNS) supports research and education activities that invent new computing and networking technologies and that explore new ways to make use of existing technologies. The Division seeks to develop a better understanding of the fundamental properties of computer and network systems and to create better abstractions and tools for designing, building, analyzing, and measuring future systems. The Networking Technology and Systems (NeTS) program supports transformative research on fundamental scientific and technological advances leading to the development of future-generation, high-performance networks and future Internet architectures.

Physics at the Information Frontier (PIF) includes support for data-enabled science, community research networks, and new computational infrastructure, as well as for next-generation computing. It focuses on cyber-infrastructure for the disciplines supported by the Physics Division while encouraging broader impacts on other disciplines. Disciplines within the purview of the Physics Division include: atomic, molecular, optical, plasma, elementary particle, nuclear, particle astrophysics, gravitational and biological physics. Proposals with intellectual focus in areas supported by other NSF Divisions should be submitted to those divisions directly. Proposals that cross Divisional lines are welcome, but the Physics Division encourages PIs to request a co-review by naming other divisional programs on the cover sheet. This facilitates the co-review and participation of other programs in the review process. PIF provides support for physics proposals in three subareas: 1) computational physics, 2) data enabled physics, and 3) quantum information science and revolutionary computing. Computational physics emphasizes methods for high-performance computing that require significant code development, are led by physicists, and may include applied mathematicians and computer scientists. Priority will be given to proposals that, in addition to compelling scientific goals, have a computational advance or new enabling capability. Proposals should include either innovation in computing such as algorithm development and efficient use of novel architectures or provide significant improvement to community codes.Data enabled physics seeks proposals to develop tools and infrastructure that provide rapid, secure, and efficient access to physics data stores via heterogeneous or distributed computing resources and networks.

The Advanced Scientific Computing Research (ASCR) program of the Office of Science (SC), U.S. Department of Energy (DOE), hereby invites exploratory basic research proposals with the potential to deliver significantly advanced or improved science capabilities in light of emerging and disruptive technology changes. Desired outcomes include advances that will make massively parallel, heterogeneous computer architectures more efficient and practical to use in carrying out scientific research activities. A complementary ASCR objective is to build up the computational research infrastructure for enabling data-intensive science advances. 

This research will include all aspects of sensor development and management, innovative sensing, sensor exploitation, performance metrics, performance analysis and methods for sensor exploitation performance prediction, cooperative autonomous systems, information visualization, mobile computing architectures and applications, and computational sciences.

NSF is interested in supporting activities by the NSF Cyberinfrastructure community in the analysis of existing benchmarks, and in the development of new benchmarks, that measure real-world performance and effectiveness of large-scale computing systems for science and engineering discovery. Research, development, and use of performance benchmarks in high-performance computing (HPC) has been active for over 20 years, as evidenced by the development of LINPACK and the emergence of the TOP500 list in the early 1990s, followed by the development of the HPC Challenge Benchmark and the current HPCG effort (http://tiny.cc/hpcg). There have been efforts to provide benchmarks that include real applications, such as the SPEC High Performance Computing Benchmarks (http://spec.org/benchmarks.html#hpg), the Blue Waters SPP suite (http://www.ncsa.illinois.edu/assets/pdf/news/BW1year_apps.pdf), and the NERSC SSP (https://www.nersc.gov/users/computational-systems/nersc-8-system-cori/nersc-8-procurement/trinity-nersc-8-rfp/nersc-8-trinity-benchmarks/ssp/). Recent efforts have sought to broaden the set of relevant benchmarks to more effectively cover performance under different application environments such as data-intensive analysis (e.g., Graph500). Energy efficiency has also emerged in recent years as a relevant and increasingly important area of measurement and profiling for HPC systems (e.g., Green500). In addition to HPC, the Big Data community has gained interest in benchmarking; reference approaches to measuring and characterizing system performance for large-scale data analysis hardware and software systems remains an area of research, development, and community discussion (e.g., on the Big Data Top 100). Industry and academe have convened an ongoing series of workshops and meetings on the topic of Big Data benchmarking (http://clds.ucsd.edu/bdbc/workshops). Given the emergence of inference-based computing, the growing role of data analysis, changes in scientific workflow du

PIF provides support for physics proposals in three subareas: 1) computational physics, 2) data enabled physics, and 3) quantum information science and revolutionary computing. Computational physics emphasizes methods for high-performance computing that require significant code development, are led by physicists, and may include applied mathematicians and computer scientists. Priority will be given to proposals that, in addition to compelling scientific goals, have a computational advance or new enabling capability. Proposals should include either innovation in computing such as algorithm development and efficient use of novel architectures or provide significant improvement to community codes. Data enabled physics seeks proposals to develop tools and infrastructure that provide rapid, secure, and efficient access to physics data stores via heterogeneous or distributed computing resources and networks. Examples include development of reliable digital preservation, access, integration, and curation capabilities associated with data from Physics Division experimental facilities and the tools for data handling needed to maximize the scientific payoff. Priority will be given to proposals that serve broad communities or that bring dramatic new capabilities to a specific sub-area of physics. Quantum information and revolutionary computing supports theoretical and experimental proposals that explore applications of quantum mechanics to new computing paradigms or that foster interactions between physicists, mathematicians, and computer scientists that push the frontiers of quantum-based information, transmission, and manipulation.