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The Scalable Parallelism in the Extreme (SPX) program aims to support research addressing the challenges of increasing performance in this modern era of parallel computing. This will require a collaborative effort among researchers in multiple areas, from services and applications down to micro-architecture. Objectives, including supporting foundational research toward architecture and software approaches that drive performance improvements in the post-Moore’s Law era; development and deployment of programmable, scalable, and reusable platforms in the national HPC and scientific cyberinfrastructure ecosystem; increased coherence of data analytic computing and modeling and simulation; and capable extreme-scale computing.

The Defense Advanced Research Projects Agency (DARPA) is soliciting innovative proposals in the following technical areas: radio architectures and technology and network architectures and technology that maintain network reliability through periods of data channel degradation.

Nanomanufacturing is the production of useful nano-scale materials, structures, devices and systems in an economically viable manner. The NSF Nanomanufacturing Program supports fundamental research in novel methods and techniques for batch and continuous processes, top-down (addition/subtraction) and bottom-up (directed self-assembly) processes leading to the formation of complex heterogeneous nanosystems. The program supports basic research in nanostructure and process design principles, integration across length-scales, and system-level integration. The Program leverages advances in the understanding of nano-scale phenomena and processes (physical, chemical, electrical, thermal, mechanical and biological), nanomaterials discovery, novel nanostructure architectures, and new nanodevice and nanosystem concepts. It seeks to address quality, efficiency, scalability, reliability, safety and affordability issues that are relevant to manufacturing. To address these issues, the Program encourages research on processes and production systems based on computation, modeling and simulation, use of process metrology, sensing, monitoring, and control, and assessment of product (nanomaterial, nanostructure, nanodevice or nanosystem) quality and performance.

Nanomanufacturing is the production of useful nano-scale materials, structures, devices and systems in an economically viable manner. The NSF Nanomanufacturing Program supports fundamental research in novel methods and techniques for batch and continuous processes, top-down (addition/subtraction) and bottom-up (directed self-assembly) processes leading to the formation of complex heterogeneous nanosystems. The program supports basic research in nanostructure and process design principles, integration across length-scales, and system-level integration. The Program leverages advances in the understanding of nano-scale phenomena and processes (physical, chemical, electrical, thermal, mechanical and biological), nanomaterials discovery, novel nanostructure architectures, and new nanodevice and nanosystem concepts. It seeks to address quality, efficiency, scalability, reliability, safety and affordability issues that are relevant to manufacturing. To address these issues, the Program encourages research on processes and production systems based on computation, modeling and simulation, use of process metrology, sensing, monitoring, and control, and assessment of product (nanomaterial, nanostructure, nanodevice or nanosystem) quality and performance.

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 purpose of the NOAA Research to Operations (R2O) Initiative is to expand and accelerate critical weather forecasting research to operations to address growing service demands and increase the accuracy of weather forecasts. This will be achieved through: (1) accelerated development and implementation of improved global weather prediction models, and inclusion of the coupling of atmosphere, ocean, wave, land surface and ice system components; (2) improved data assimilation techniques; (3) nested regional prediction capabilities; (4) improved hurricane and tropical cyclone modeling techniques; (5) improved ensemble techniques; (6) post-processing forecast tools and techniques; and (7) improved software architecture and system engineering.

New Connections: Increasing Diversity of RWJF Programming is celebrating its 10th year of supporting research grants and career development opportunities for a network of more than 830 researchers from diverse, underrepresented and disadvantaged backgrounds. The program aims to expand the diversity of perspectives that inform RWJF programming and introduce new researchers to the Foundation to help address research and evaluation needs. New Connections is a career development program for early career researchers. Through grantmaking, mentorship, career development and networking, New Connections enhances the research capacity of its grantees and network members. The researchers in this program transcend disciplines (health; health care; social sciences; business; urban planning; architecture and engineering); work to build the case for a Culture of Health with strong qualitative and quantitative research skills; and produce and translate timely research results.

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 Energy, Power, Control, and Networks (EPCN) Program supports innovative research in modeling, optimization, learning, adaptation, 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 novel machine learning algorithms and analysis, adaptive dynamic programming, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN's goal is to encourage research on emerging technologies and applications including energy, transportation, robotics, and biomedical devices & systems. EPCN also emphasizes electric power systems, including generation, transmission, storage, and integration of renewable energy sources into the grid; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory & economic structures and with consumer behavior.

This program seeks to accelerate fundamental, broad-based research on wireless-specific machine learning (ML) techniques, towards a new wireless system and architecture design, which can dynamically access shared spectrum, efficiently operate with limited radio and network resources, and scale to address the diverse and stringent quality-of-service requirements of future wireless applications. In parallel, this program also targets research on reliable distributed ML by addressing the challenge of computation over wireless edge networks to enable ML for wireless and future applications. Model-based approaches for designing the wireless network stack have proven quite efficient in delivering the networks in wide use today; research enabled by this program is expected to identify realistic problems that can be best solved by ML and to address fundamental questions about expected improvements from using ML over model-based methods.

The confluence of transistor scaling, increases in the number of architecture designs per process generation, the slowing of clock frequency growth, and recent success in research exploiting Thread Level Parallelism (TLP) and Data Level Parallelism (DLP) all point to an increasing opportunity for innovative microarchitecture techniques and methodologies in delivering performance growth in the future. The NSF/Intel Partnership on Foundational Microarchitecture Research will support transformative microarchitecture research targeting improvements in instructions per cycle (IPC). This solicitation seeks microarchitecture technique innovations beyond simplistic, incremental scaling of existing microarchitectural structures. Specifically, FoMR seeks to advance research that has the following characteristics: (1) high IPC techniques ranging from microarchitecture to code generation; (2) "microarchitecture turbo" techniques that marshal chip resources and system memory bandwidth to accelerate sequential or single-threaded programs; and (3) techniques to support efficient compiler code generation. Advances in these areas promise to provide significant performance improvements to continue the cadence promised by Moore's Law.

The Office of Naval Research (ONR) is interested in a research project to develop architectures, abstraction methods, and navigation filtering and fusion algorithms to combine inputs from multiple sensors to achieve a high quality precision ship-relative navigation (PS-RN) solution in demanding naval environments. The resulting PS-RN solution must be capable of being directly plugged into an air vehicle's command guidance system such that the air vehicle's flight control system can fly the vehicle along the desired approach path to landing.

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 objective of this activity is to competitively solicit projects in novel technologies under the Crosscutting Research Program Area to support Department of Energy Strategic Goals. The United States Department of Energy National Energy Technology Laboratory is seeking innovative research and development of novel sensor and control systems for use in advanced power generation systems. New sensor and control technology will contribute the goals of high efficiency, near zero emission, and effective carbon capture for the next generation power generation technologies. These technologies include advanced combustion, gasification, turbines, fuel cells, gas cleaning and separation technologies, and carbon dioxide separation and capture technologies. The inclusion of transformational power generation and emission control technology will enable high process efficiency and integration to achieve performance goals at reasonable cost. Integration o f new technology will introduce unprecedented levels of complexity and process conditions that must be address by improved sensor and control technology. To manage complexity and achieve performance goals, advances in the capability and architecture of instrumentation, sensors, and process controls are vital in assuring integrated unit operations, predictive on-line maintenance, and continuous life cycle monitoring and real time process optimization. Innovations in these areas are being supported by the National Energy Technology Laboratorys Crosscutting Research Program which aims at bridging the gap between the basic sciences and applied research as it relates to Advanced Power Systems that utilize domestic resources. Long range transitional type research is needed to support the identification and growth of novel concepts that will to scientific breakthroughs and early adoption of innovative concepts into applications for power generation.

Successful projects will address at least one of ARPA-E?s two Mission Areas: 1. Enhance the economic and energy security of the United States through the development of energy technologies that result in: a. reductions of imports of energy from foreign sources; b. reductions of energy-related emissions, including greenhouse gases; and c. improvement in the energy efficiency of all economic sectors; and 2. Ensure that the United States maintains a technological lead in developing and deploying advanced energy technologies. This program seeks to fund the development of transformational electrochemical energy storage technologies that will accelerate widespread electric vehicle adoption by dramatically improving their driving range, cost, and reliability. To achieve this long-term objective, this program aims to maximize specific energy and minimize cost of energy storage systems at the vehicle level. Central to this system-level approach is the use of robust design principles for energy storage systems. Robust design is defined as electrochemical energy storage chemistries and/or architectures (i.e. physical designs) that avoid thermal runaway and are immune to catastrophic failure regardless of manufacturing quality or abuse conditions. In addition, this program seeks multifunctional energy storage designs that use these robust storage systems to simultaneously serve other functions on a vehicle (for example, in the frame, body, and/or crumple zone), thus further reducing an energy storage syst em?s effective weight when normalized to the entire electric vehicle weight.

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.