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The NSF/Intel Partnership on Computer Assisted Programming for Heterogeneous Architectures (CAPA) aims to address the problem of effective software development for diverse hardware architectures through groundbreaking university research that will lead to a significant, measurable leap in software development productivity by partially or fully automating software development tasks that are currently performed by humans. The main research objectives for CAPA include programmer effectiveness, performance portability, and performance predictability. In order to address these objectives, CAPA seeks research proposals that explore (1) programming abstractions and/or methodologies that separate performance-related aspects of program design from how they are implemented; (2) program synthesis and machine learning approaches for automatic software construction that are demonstrably correct; (3) advanced hardware-based cost models and abstractions to support multi-target code generation and performance predictability for specified heterogeneous hardware architectures; and (4) integration of research results into principled software development practices.

The purpose of this amendment is to correct a typographical error in the abstract details on page 41. See the attached conformed BAA with changes highlighted in yellow. Amendment 01: The purpose of this amendment is to make administrative changes as highlighted in yellow in the attached.Original Synopsis Below:DARPA is soliciting innovative research proposals in the area of novel computing architectures. The Page 3 Architectures thrust of the Electronics Resurgence Initiative (ERI) seeks to demonstrate heterogeneous computing systems that provide the performance advantages of specialized processors, while maintaining the programmability of general purpose processors.The goal of the Software Defined Hardware (SDH) program is to build runtime-reconfigurable hardware and software that enables near ASIC performance without sacrificing programmability for data-intensive algorithms. SDH will create a hardware/software system that allows data-intensive algorithms to run at near ASIC efficiency without the cost, development time or single application limitations associated with ASIC development. The overall goal of the Domain-specific System on Chip (DSSoC) program is to develop a heterogeneous SoC comprised of many cores that mix general-purpose processors, special-purpose processors, hardware accelerators, memory, and input/output (I/O). DSSoC seeks to enable rapid development of multi-application systems through a single programmable device.

Algorithms in the Field encourages closer collaboration between two groups of researchers: (i) theoretical computer science researchers, who focus on the design and analysis of provably efficient and provably accurate algorithms for various computational models; and (ii) other computing and information researchers including a combination of systems and domain experts (very broadly construed - including but not limited to researchers in computer architecture, programming languages and systems, computer networks, cyber-physical systems, cyber-human systems, machine learning, artificial intelligence and its applications, database and data analytics, etc.) who focus on the particular design constraints of applications and/or computing devices. Each proposal must have at least one co-PI interested in theoretical computer science and one interested in any of the other areas typically supported by CISE. Proposals are expected to address the dissemination of both the algorithmic contributions and the resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

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. SPX encompasses all five NSCI Strategic 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. Coordination with industrial efforts that pursue related goals are encouraged.

Algorithms in the Field encourages closer collaboration between two groups of researchers: (i) theoretical computer science researchers, who focus on the design and analysis of provably efficient and provably accurate algorithms for various computational models; and (ii) applied researchers including a combination of systems and domain experts (very broadly construed - including but not limited to researchers in computer architecture, programming languages and systems, computer networks, cyber-physical systems, cyber-human systems, machine learning, database and data analytics, etc.) who focus on the particular design constraints of applications and/or computing devices. Each proposal must have at least one co-PI interested in theoretical computer science and one interested in any of the other areas typically supported by CISE. Proposals are expected to address the dissemination of the algorithmic contributions and resulting applications, tools, languages, compilers, libraries, architectures, systems, data, etc.

SoftwareInfrastructure for Sustained Innovation (SI2) is a long-term investment focused on realizing a portion of the Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21, http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504730) vision and catalyzing new thinking, paradigms and practices in science and engineering. CIF21 envisions a linked cyberinfrastructure architecture that integrates large-scale computing, high-speed networks, massive data archives, instruments and major facilities, observatories, experiments, and embedded sensors and actuators, across the nation and the world, and that enables research at unprecedented scales, complexity, resolution, and accuracy by integrating computation, data, and experiments in novel ways. Software is a primary modality through which CIF21 innovation and discovery will be realized. It permeates all aspects and layers of cyberinfrastructure (from application codes and frameworks, programming systems, libraries and system software, to middleware, operating systems, networking and the low-level drivers). The CIF21 software infrastructure must address the complexity of this cyberinfrastructure, accommodating: disruptive hardware trends; ever-increasing data volumes; data integrity, privacy, and confidentiality; security; complex application structures and behaviors; and emerging concerns such as fault-tolerance and energy efficiency. The programs must focus on building robust, reliable and sustainable software that will support and advance sustained scientific innovation and discovery.
 The Division of Advanced Cyberinfrastructure in the Computer & Information Science & Engineering Directorate (CISE/ACI) is partnering with Directorates and Offices across the NSF to support SI2, a long-term comprehensive program focused on realizing a sustained software infrastructure that is an integral part of CIF21.

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.

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.

he intent of this solicitation is to request proposals from organizations willing to serve as service providers (SPs) within the NSF Innovative High-Performance Computing (HPC) program to provide advanced cyberinfrastructure (CI) capabilities and/or services in production operations to support the full range of computational- and data-intensive research across all of science and engineering (S&E). The current solicitation is intended to complement previous NSF investments in advanced computational infrastructure by provisioning resources, broadly defined in this solicitation to include systems and/or services, in two categories: Category I, Capacity Systems: production computational resources maximizing the capacity provided to support the broad range of computation and data analytics needs in S&E research; and Category II, Innovative Prototypes/Testbeds: innovative forward-looking capabilities deploying novel technologies, architectures, usage modes, etc., and exploring new target applications, methods, and paradigms for S&E discoveries.

Cyber-physical systems (CPS) are engineered systems that are built from, and depend upon, the seamless integration of computational algorithms and physical components. Advances in CPS will enable capability, adaptability, scalability, resiliency, safety, security, and usability that will far exceed the simple embedded systems of today. CPS technology will transform the way people interact with engineered systems -- just as the Internet has transformed the way people interact with information. New smart CPS will drive innovation and competition in sectors such as agriculture, energy, transportation, building design and automation, healthcare, and manufacturing. The December 2010 report of the President's Council of Advisors on Science and Technology (PCAST) titled Designing a Digital Future: Federally Funded Research and Development in Networking and Information Technologycalls for continued investment in CPS research because of its scientific and technological importance as well as its potential impact on grand challenges in a number of sectors critical to U.S. security and competitiveness such as the ones noted above. These challenges and technology gaps are further described in aCPS Vision Statementpublished in 2012 by the federal Networking and Information Technology Research and Development (NITRD) CPS Senior Steering Group. Tremendous progress has been made in advancing CPS technology over the last five-plus years. We have explored foundational technologies that have spanned an ever-growing set of application domains, enabling breakthrough achievements in many of these fields. At the same time, the demand for innovation in these domains continues to grow, and is driving the need to accelerate fundamental research to

On January 16, 2018, The Department of Transportation will post a request for letters of interest to perform and document the statewide Systems Engineering Analysis for Autonomous/Connected Vehicle (SEA AV/CV) projects in conformance with 23 CFR 940 and Section 1300 of the Traffic Engineering Manual. Included with this effort will be a review, and recommendations of necessary updates, to the existing statewide and MPO Regional ITS Architectures to ensure consistency with the developed SEA AV/CV document. The goal of this effort is to create the statewide framework to guide current and future AV/CV deployments. The requirements of 23 CFR 940 will be handled at the program level to the extent possible via this effort rather than on a project-by-project basis.

A key focus of the design of modern computing systems is performance and scalability, particularly in light of the limits of Moore's Law and Dennard scaling. To this end, systems are increasingly being implemented by composing heterogeneous computing components and continually changing memory systems as novel, performant hardware surfaces. Applications fueled by rapid strides in machine learning, data analysis, and extreme-scale simulation are becoming more domain-specific and highly distributed. In this scenario, traditional boundaries between hardware-oriented and software-oriented disciplines increasingly are blurred. Achieving scalability of systems and applications will therefore require coordinated progress in multiple disciplines such as computer architecture, high-performance computing (HPC), programming languages and compilers, security and privacy, systems, theory, and algorithms. Cross-cutting concerns such as performance (including, but not limited to, time, space, and communication resource usage and energy efficiency), correctness and accuracy (including, but not limited to, emerging techniques for program analysis, testing, debugging, probabilistic reasoning and inference, and verification), security and privacy, robustness and reliability, domain-specific design, and heterogeneity must be taken into account from the outset in all aspects of systems and application design and implementation.

A key focus of the design of modern computing systems is performance and scalability, particularly in light of the limits of Moore's Law and Dennard scaling. To this end, systems are increasingly being implemented by composing heterogeneous computing components and continually changing memory systems as novel, performant hardware surfaces. Applications fueled by rapid strides in machine learning, data analysis, and extreme-scale simulation are becoming more domain-specific and highly distributed. In this scenario, traditional boundaries between hardware-oriented and software-oriented disciplines increasingly are blurred. Achieving scalability of systems and applications will therefore require coordinated progress in multiple disciplines such as computer architecture, high-performance computing (HPC), programming languages and compilers, security and privacy, systems, theory, and algorithms. Cross-cutting concerns such as performance (including, but not limited to, time, space, and communication resource usage and energy efficiency), correctness and accuracy (including, but not limited to, emerging techniques for program analysis, testing, debugging, probabilistic reasoning and inference, and verification), security and privacy, robustness and reliability, domain-specific design, and heterogeneity must be taken into account from the outset in all aspects of systems and application design and implementation.

There is a consensus across the many industries touched by our ubiquitous computing infrastructure that future performance improvements across the board are now severely limited by the amount of energy it takes to manipulate, store, and critically, transport data. While the limits and tradeoffs for this performance-energy crisis vary across the full range of application platforms, they have all reached a point at which evolutionary approaches to addressing this challenge are no longer adequate. Truly disruptive breakthroughs are now required, and not just from any one segment of the technology stack. Rather, due to the complexity of the challenges, revolutionary new approaches are needed at each level in the hierarchy. Furthermore, simultaneous co-optimization across all levels is essential for the creation of new, sustainable computing platforms. These simultaneous technical and organizational challenges have never been as complex or as critically important as they are now. The urgency of solving the multi-disciplinary technical challenges will require new methods of collaboration and organization among researchers. Therefore, a comprehensive and collaborative approach must be undertaken to maximize the potential for successfully identifying and implementing revolutionary solutions to break through the bottleneck of energy-constrained computational performance. Programmers, system architects, circuit designers, chip processing engineers, material scientists, and computational chemists must all explore these new paths together to co-design an optimal solution path.

The Board of Regents is seeking high quality, focused cooperative education and internship program proposals from Ohio institutions of higher education and their partners. This program has been funded  through one-time casino licensing fees; it is expected that the funds will be awarded to build systems to sustain co-ops and internships beyond the direct investment from the State and to ensure these workbased learning opportunities are relevant to the needs of students and businesses. Funds will be awarded to build the capability and capacity of programs to engage more students, more businesses,  and more faculty members in co-op and internship programs. The programs should address the talent needs of JobsOhio key industries.

The following programs have due dates that fall between October 1 - 25, 2013, and these dates are being revised due to the Federal  government shutdown. These revised dates apply whether the proposal is being submitted via the NSF FastLane System or  Grants.gov. Due to compressed proposal deadlines resulting from the shutdown, proposers are advised that they may experience a  delay when contacting IT Help Central with technical support questions. Frequently asked questions regarding these date changes  are available on the Resumption of Operations page on the NSF website at: http://www.nsf.gov/bfa/dias/policy/postshutdown.jsp.