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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.

The SI2 program focuses on supporting robust, reliable and sustainable software that will support and advance sustained scientific innovation and discovery. Thus, proposals are strongly encouraged to describe their approach to quality software development through a defined software engineering process that includes software testing, the appropriate use of analysis tools and capabilities such as those made available through the Software Assurance Marketplace (SWAMP, https://continuousassurance.org/), and collaborations with resources such as Software Carpentry (http://software-carpentry.org/) and the Center for Trustworthy Scientific Cyberinfrastructure (CTSC, http://trustedci.org/), in order to gain access to expertise where needed, such as in software design and engineering, as well as in cybersecurity.

The DoD strives for superiority in a complex operational environment composed of heterogeneous and ever-evolving pieces such as sensors and processing hardware, software, and wired and wireless communications infrastructure. To achieve superiority in this dynamic environment, the DoD invests in fully networked and maximally-capable sensors and platforms at the cutting edge of performance. Software has emerged as a key enabler of capability and flexibility in DoD systems. Software is essential to providing a vast range of military capabilities by playing a fundamental role [1] that deepens, broadens, links, and integrates diverse system elements. A pervasive DoD challenge is the production of software that provides the Warfighter superior and affordable military capability in an environment where hardware and sensor technology is rapidly advancing and systems' performance demands are ever-increasing. The Government Accountability Office has identified the increasing scope of software development as a contributing factor to poor acquisition program outcome [2]. OASD(R&E) has identified the need for advanced software engineering technology to enhance the producibility of software in this environment with the goal of speeding the delivery of affordable capability to the Warfighter and sustaining it.

The SI2 program includes three classes of awards: 1. Scientific Software Elements (SSE): SSE awards target small groups that will create and deploy robust software elements for which there is a demonstrated need that will advance one or more significant areas of science and engineering. 2. Scientific Software Integration (SSI): SSI awards target larger, interdisciplinary teams organized around the development and application of common software infrastructure aimed at solving common research problems. SSI awards will result in a sustainable community software framework serving a diverse community. 3. Scientific Software Innovation Institutes (S2I2): S2I2 awards will focus on the establishment of long-term hubs of excellence in software infrastructure and technologies, which will serve a research community of substantial size and disciplinary breadth.

Software is an integral enabler of computation, experiment and theory and a primary modality for realizing the Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21) vision, as described in http://www.nsf.gov/pubs/2010/nsf10015/nsf10015.jsp. Scientific discovery and innovation are advancing along fundamentally new pathways opened by development of increasingly sophisticated software. Software is also directly responsible for increased scientific productivity and significant enhancement of researchers' capabilities. In order to nurture, accelerate and sustain this critical mode of scientific progress, NSF has established the Software Infrastructure for Sustained Innovation (SI2) program, with the overarching goal of transforming innovations in research and education into sustained software resources that are an integral part of the cyberinfrastructure. SI2 is a long-term investment focused on catalyzing new thinking, paradigms, and practices in developing and using software to understand natural, human, and engineered systems. SI2's intent is to foster a pervasive cyberinfrastructure to help researchers address problems of unprecedented scale, complexity, resolution, and accuracy by integrating computation, data, networking, observations and experiments in novel ways.

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 HPEM Modeling & Effects research and development effort consists of the following areas: understanding the connectivity of infrastructure and mobile targets; understanding the phenomenology of front door effects; developing a predictive effects model; developing a theoretical and empirical basis for HPEM effects ranging from the basic circuit level to the system level effects; empirical effects testing on operational targets as a function of frequency, pulsed duration, and power of the incident HPEM pulse; battle damage assessment; rapid modeling of HPEM system sources and components; improving particle-in-cell code (PIC) capabilities; first principles materials modeling; improving models for electron emission, gas desorption to enhance the predictive capability of virtual prototyping; and developing electromagnetic (EM) algorithms to propagate radio frequency (RF) from platform-specific high power RF systems to targets to assess the performance measures of effective HPEM sources. Sound software engineering and development principles must be employed for all developed software and documentation. Robust software testing, validation, and verification are critical to software development efforts. As appropriate, software must scale to large simulation sizes and be portable to massively parallel computer architecture.

In order to nurture, accelerate and sustain this critical mode of scientific progress, NSF has established the Software Infrastructure for Sustained Innovation (SI2) program, with the overarching goal of transforming innovations in research and education into sustained software resources that are an integral part of the cyberinfrastructure.SI2 is a long-term investment focused on catalyzing new thinking, paradigms, and practices in developing and using software to understand natural, human, and engineered systems. SI2's intent is to foster a pervasive cyberinfrastructure to help researchers address problems of unprecedented scale, complexity, resolution, and accuracy by integrating computation, data, networking, observations and experiments in novel ways. NSF expects that its SI2 investment will result in robust, reliable, usable and sustainable software infrastructure that is critical to achieving the CIF21 vision and will transform science and engineering while contributing to the education of next generation researchers and creators of future cyberinfrastructure. 

Advancements in data-driven scientific research depend on trustworthy and reliable cyberinfrastructure. Researchers rely on a variety of networked technologies and software tools to achieve their scientific goals. These may include local or remote instruments, wireless sensors, software programs, operating systems, database servers, high-performance computing, large-scale storage arrays, and other critical infrastructure connected by high-speed networking. This complex, distributed, interconnected global cyberinfrastructure ecosystem presents unique cybersecurity challenges. NSF-funded scientific instruments are specialized, highly visible assets that present attractive targets for both unintentional errors and malicious activity; untrustworthy software or a loss of integrity of the data collected by a scientific instrument may mean corrupt, skewed or incomplete results. Furthermore, often data-driven research, e.g., in the medical field or in the social sciences, requires access to private information, and exposure of such data may cause financial, reputational and/or other damage. Therefore, an increasing area of focus for NSF is the development and deployment of hardware and software technologies and techniques to protect research cyberinfrastructure across every stage of the scientific workflow.

Advancements in data-driven scientific research depend on trustworthy and reliable cyberinfrastructure. Researchers rely on a variety of networked technologies and software tools to achieve their scientific goals. These may include local or remote instruments, wireless sensors, software programs, operating systems, database servers, high-performance computing, large-scale storage, and other critical infrastructure connected by high-speed networking. This complex, distributed, interconnected global cyberinfrastructure ecosystem presents unique cybersecurity challenges. NSF-funded scientific instruments, sensors and equipment are specialized, highly-visible assets that present attractive targets for both unintentional errors and malicious activity; untrustworthy software or a loss of integrity of the data collected by a scientific instrument may mean corrupt, skewed or incomplete results. Furthermore, often data-driven research, e.g., in the medical field or in the social sciences, requires access to private information, and exposure of such data may cause financial, reputational and/or other damage.

Projects can be small to mid-scale - the key here is to show how we can involve the global research and development community in furthering science on the web, while testing what the right level of engagement is.  Any research-oriented software development project is eligible, with special consideration given to projects that further open, collaborative, reproducible research, and reusable tools and technology for open science. Candidate research projects should: Have a clearly stated and specific goal to achieve or problem to solve in software. Be directly relevant to your ongoing or shortly upcoming research. Require code that is sharable and reusable, with preference given to open source projects. Science team should be prepared to communicate regularly with the software team.

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.

In a new effort to support open source software for science, the Chan Zuckerberg Initiative (CZI) seeks applications for software projects that are essential to biomedical research, have already demonstrated impact, and can show potential for continued improvement. Grants will be for a one-year period with the potential to apply for renewal in future cycles. With this program, we aim to provide projects with resources to support their tools and the communities behind them. Whether it's hiring an additional developer, improving documentation, addressing usability, improving compatibility, onboarding contributors, or convening a community, we hope our support can help make the computational foundations of biological research more usable and robust.

The Pizzigati Prize welcomes applications from-and nominations for-single individuals. Those nominated for the prize should have developed a software product that is open source, as defined by the Open Source Initiative, and easily and widely available. This software must have already demonstrated its value to at least one nonprofit organization. Additionally, it should be a product that can be a value to multiple nonprofit organizations.

The Cyberinfrastructure for Sustained Scientific Innovation (CSSI) umbrella program encompasses the long-running Data Infrastructure Building Blocks (DIBBs) and Software Infrastructure for Sustained Innovation (SI2) programs, as NSF seeks to enable funding opportunities that are flexible and responsive to the evolving and emerging needs in data and software cyberinfrastructure.

The Cyberinfrastructure for Sustained Scientific Innovation (CSSI) umbrella program encompasses the long-running Data Infrastructure Building Blocks (DIBBs) and Software Infrastructure for Sustained Innovation (SI2) programs, as NSF seeks to enable funding opportunities that are flexible and responsive to the evolving and emerging needs in data and software cyberinfrastructure.

A. Proposals for the development of novel collaborative perception algorithms that will enable heterogeneous teams of UxS (specifically unmanned air and ground systems) to share knowledge and perform joint target search and tracking autonomously. While existing distributed data fusion methods have looked at probabilistic representations for fusing detections at a decision level, work is needed to investigate shared perceptual features that exist across unmanned air and ground systems to enable the performance of collaborative tasks.  B. Development of a new Rigid Body Dynamics Software Library for Mathematical and Physics-Based Modeling and Simulation. The basic research proposed here would involve the development of a new software library for the temporal (time) integration of the governing equations of rigid body dynamics. The temporal integration technique employed in this new library involves the application of the Runge-Kutta method of various orders and possibly other finite-difference-type techniques to a system of equations consisting of kinematic equations (arising from the Lie Group structure of the group of rotation transformations) which define the first and second time derivatives of the rotation transformation in terms of angular velocity and angular acceleration together with the equations of motion (balance of momentum and balance of angular momentum) of a rigid body. C. Robustness of the Use of Botanical DNA Materials as Anti-Counterfeit Markers for Electronic Components - The project will solicit academic laboratory participation for doing testing that demonstrates the 'robustness' of the use of Botanical DNA material as anti-counterfeit markers for electronic components. Request analysis of candidate DNA marker materials utilizing current DNA manipulation technology. This would be done especially in light of results from (1) above.

The goal of the National Robotics Initiative (NRI) is to support fundamental research that will accelerate the development and use of robots in the United States that work beside or cooperatively with people. The original NRI program focused on innovative robotics research that emphasized the realization of collaborative robots (co-robots) working in symbiotic relationships with human partners. The NRI-2.0 program significantly extends this theme to focus on issues of scalability: how teams of multiple robots and multiple humans can interact and collaborate effectively; how robots can be designed to facilitate achievement of a variety of tasks in a variety of environments, with minimal modification to the hardware and software; how robots can learn to perform more effectively and efficiently, using large pools of information from the cloud, other robots, and other people; and how the design of the robots’ hardware and software can facilitate large-scale, reliable operation

The goal of the National Robotics Initiative (NRI) is to support fundamental research that will accelerate the development and use of robots in the United States that work beside or cooperatively with people. The original NRI program focused on innovative robotics research that emphasized the realization of collaborative robots (co-robots) working in symbiotic relationships with human partners. The NRI-2.0 program significantly extends this theme to focus on issues of scalability: how teams of multiple robots and multiple humans can interact and collaborate effectively; how robots can be designed to facilitate achievement of a variety of tasks in a variety of environments, with minimal modification to the hardware and software; how robots can learn to perform more effectively and efficiently, using large pools of information from the cloud, other robots, and other people; and how the design of the robots' hardware and software can facilitate large-scale, reliable operation. In addition, the program supports innovative approaches to establish and infuse robotics into educational curricula, advance the robotics workforce through education pathways, and explore the social, behavioral, and economic implications of our future with ubiquitous collaborative robots. Collaboration between academic, industry, non-profit, and other organizations is encouraged to establish better linkages between fundamental science and engineering and technology development, deployment and use. Well-justified international collaborations that add significant value to the proposed research and education activities will also be considered.

The Space/Time Analysis for Cybersecurity (STAC) program seeks to enable analysts to identify algorithmic resource usage vulnerabilities in software at levels of scale and speed great enough to support a methodical search for them in the software upon which the U.S. government, military, and economy depend. Proposed research should investigate innovative approaches that enable revolutionary advances in science, devices, or systems. Specifically excluded is research that primarily results in evolutionary improvements to the existing state of practice. See the full DARPA-BAA-14-60 document attached.