NSF 21-513: Principles and Practice of Scalable Systems (PPoSS)
Program Solicitation
Document Information
Document History
- Posted: October 13, 2020
- Replaces: NSF 20-534
- Replaced by: NSF 22-507
Program Solicitation NSF 21-513
Full Proposal Deadline(s) (due by 5 p.m. submitter's local time): January 25, 2021 Planning grants and LARGE grants January 24, 2022 Planning grants and LARGE grants January 23, 2023 LARGE grants only January 22, 2024 LARGE grants only Important Information And Revision NotesRestrictions on Who May Serve as PI have been removed. Limits on the number of submissions and the distinction between Planning and LARGE grants have been clarified. Additional Solicitation Specific Review Criteria for LARGE proposals have been clarified and enhanced.
Any proposal submitted in response to this solicitation should be submitted in accordance with the revised NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 20-1), which is effective for proposals submitted, or due, on or after June 1, 2020. Summary Of Program RequirementsGeneral InformationProgram Title:
Synopsis of Program:
Cognizant Program Officer(s): Please note that the following information is current at the time of publishing. See program website for any updates to the points of contact.
Applicable Catalog of Federal Domestic Assistance (CFDA) Number(s):
Award InformationAnticipated Type of Award: Standard Grants and Continuing Grants Estimated Number of Awards: 28 Planning Grants: Approximately 8 awards will be made in FY 2021, and 4 awards in FY 2022, pending availability of funds and quality of proposals received. LARGE Grants: Approximately 4 awards will be made each year in FY 2021, FY 2022, FY 2023, and FY 2024, pending availability of funds and quality of proposals received. Anticipated Funding Amount: $83,000,000 Planning Grants: Up to $250,000 per award with duration up to 1 year. LARGE Grants: Up to $1,000,000 per year with duration up to 5 years. Estimated program budget, number of awards, and average award size/duration are subject to the availability of funds and quality of proposal received. Eligibility InformationWho May Submit Proposals:
Who May Serve as PI:
Limit on Number of Proposals per Organization:
Limit on Number of Proposals per PI or Co-PI: 3
Proposal Preparation and Submission InstructionsA. Proposal Preparation Instructions
B. Budgetary Information
C. Due Dates
Proposal Review Information CriteriaMerit Review Criteria: National Science Board approved criteria. Additional merit review criteria apply. Please see the full text of this solicitation for further information. Award Administration InformationAward Conditions: Standard NSF award conditions apply. Reporting Requirements: Standard NSF reporting requirements apply. I. IntroductionComputing systems have undergone a fundamental transformation from the relatively isolated single-processor systems to large-scale distributed and networked systems within a span of a few decades. During this period, the observations by Gordon Moore about the regular and timely increase in computational capacity and Robert Dennard about the proportional scaling of size and power of transistors have largely held true. With the imminent end of Moore’s Law and Dennard scaling, continued scalability of applications has become a major concern. Furthermore, over the years, the use of parallel and distributed systems has expanded beyond traditional supercomputing applications (i.e., scientific simulation) to providing the essential computing infrastructure that advance artificial intelligence (AI) and machine learning (ML), large-scale communication networks (e.g., social media), smart and connected communities, etc. However, the field of parallel and distributed systems faces a number of existing and emerging challenges that must be overcome to meet the diverse and rapidly increasing computational requirements of new, larger, highly distributed applications. Several reports (see, for example, "Future Directions for NSF Advanced Computing Infrastructure to Support U.S. Science and Engineering in 2017-2020"; "21st Century Computer Architecture"; "The Future of Computing Performance: Game Over or Next Level?"; and "Advanced Computing Infrastructure: Vision and Strategic Plan"), as well as the recent update to the National Strategic Computing Initiative (NSCI), have outlined the need for computational systems that enable emerging, large-scale applications without the benefit of Dennard scaling (the "post-Moore’s Law" era). Furthermore, their conclusions align with Administration and Congressional priorities on basic and applied research investments in computing. These priorities articulate the need to “explore new applications in and support R&D for high performance future paradigms, fabrication, devices, and architectures alongside sustainable and interoperable software; data maintenance and curation; and appropriate security.” The objective of the Principles and Practice of Design of Scalable Systems (PPoSS) program therefore is to build a community of researchers who will work symbiotically across multiple topics to perform basic research on scalability of modern applications, systems, and toolchains. PPoSS expects coordinated progress at the intersection of multiple disciplines including, but not limited to, computer architecture, HPC, programming languages and compilers, security and privacy, systems, and theory and algorithms. Cross-cutting concerns such as performance (including, but not limited to, resource usage and energy efficiency), correctness and accuracy (including, but not limited to, emerging techniques for program analysis, testing, debugging, probabilistic reasoning and inference, verification), security and privacy, domain-specific design, and heterogeneity must be taken into account from the outset in all aspects of systems design and implementation. The intent is that these efforts will foster the development of principles that lead to rigorous and reproducible methodologies for the design and implementation of large-scale systems and that simultaneously streamline reasoning about their correctness and accuracy, security, and privacy. II. Program DescriptionSystems incorporating a variety of specialized components form heterogeneous platforms that are very powerful but also make application development more difficult. While current solutions include a transition to new computational fabrics that may offer future increases in performance, the highest-performance computing systems are still very specialized -- customized in the hardware, algorithms, and abstractions underlying the software -- to fit the exact organization and requirements of the application at hand. This pressure towards application-specific design is compounded by the expansion of computing into new environments and domains, such as digital agriculture, in which applications are highly distributed and decentralized, and involve both localized sensing computations on thousands – or even millions -- of low-power edge devices and predictive simulations at landscape or global scale running in massive data centers. Such applications will challenge future systems to simultaneously compose and orchestrate both small and large devices alike. These applications will also push computing towards new abstractions, algorithms, and systems stacks, such as those integrating sensing and AI/ML, that are of increasing importance to computer science. In addition to seeking only the traditional goals of performance and scalability (latency, throughput, etc.), energy efficiency, and reliability, there is an increased demand for these solutions to facilitate reasoning about accuracy, correctness, security, and privacy, which have become central system goals. The methodology for building these systems may therefore require new automated analyses and correct-by-construction development methods that address these goals from the outset of the design process. In summary, it is expected that the next generation of parallel and distributed computing systems will include domain-specific solutions, and will combine a heterogeneous mix of computational patterns, algorithms, and hardware to achieve a set of goals that go beyond traditional systems aims to meet society's needs for more scalable, energy-efficient, reliable, verifiable, and secure computing systems. A recent NSF workshop brought together researchers from academia, government, and industry to discuss future directions in parallel and distributed computing with an underlying emphasis on sustaining scalable system performance in modern computing environments. The workshop report identifies a variety of challenges in systems design and implementation that have been exacerbated by the rapid evolution and proliferation of machine/deep learning and AI techniques. Large-scale systems that increasingly serve domain-specific applications are distributed (e.g., distributed machine-learning systems), and are composed of heterogeneous computing components [e.g., Graphics Processing Units (GPUs), Tensor Processing Units (TPUs), Field-Programmable Gate Arrays (FPGAs)] and continually changing memory systems (e.g., Non-Volatile Random Access Memories, or NVRAMs). Applications supported by these systems now expand beyond traditional supercomputing applications to encompass, for example, data-driven applications, learning-based applications, and communication networks. The consequent research challenges are complex. Firstly, the post-Moore’s Law era necessitates performance improvement by exploiting heterogeneous hardware accelerators and innovative architectural platforms. Secondly, new abstractions that enable scalability should explore all levels of the hardware/software stack and should simultaneously facilitate reasoning about key systems properties such as correctness and accuracy as well as security and privacy. Thirdly, scalability must be evaluated end-to-end, that is, with respect to the full hardware/software stack because innovations and breakthroughs in specific parts of the hardware/software stack may have effects that percolate throughout the system. With these challenges in mind, the scope of PPoSS includes, but is not limited to, the research areas mentioned below (Section II.A), but projects must ensure that they cover multiple (at least four) areas and have senior personnel with commensurate expertise. Moreover, projects must: (1) describe the targeted distributed applications and systems, and the heterogeneous platforms on which they run; (2) define relevant notions of scale, and describe how scalability will be theoretically and experimentally evaluated with respect to the full hardware/software stack while accounting for cross-cutting concerns such as rigorously-proven correctness and accuracy, security, and privacy; and (3) provide preliminary evidence of end-to-end scalability of one or more of the targeted applications in (1), based on proposed theories and abstractions. II.A. Research Areas Illustrative, but non-exhaustive, research areas are discussed below. As traditional boundaries between the topics get increasingly blurred in the post-Moore’s Law era, there is a clear need for the corresponding communities to meaningfully collaborate. Both the use of AI and ML methods and the interplay between program synthesis and AI and ML will drive the need for more performance and more parallelism in all the research thrusts. Computer Architecture: Recent architecture research has explored point solutions in the form of accelerators for individual computations, but many challenges arise when deploying such specialization and heterogeneity in extreme scale systems where multiple accelerators co-exist. There is a need for principles that guide architectures when considering scaling to full systems that deploy multiple accelerators and application-specializations in compute, memory, communications, and storage for a large number of application domains. In tandem, there is a need to develop principles that guide the design of the hardware so that it is amenable to easily programmable software interfaces. Models of special-purpose architectures that will result in general-purpose design methodologies and tools without the inefficiencies associated with today’s general-purpose architectures and that can quickly and cheaply transform an application, domain, or algorithm specification to the required hardware and software stack must also be investigated. High-Performance Computing: In modern usage, HPC is interpreted broadly to mean the scale-up of virtually any computational process. HPC techniques are used to scale not only traditional simulations, but also applications in which learning, data analytics, and simulation are combined. There is a need to develop principles of design and implementation to bestow such applications with high performance and extreme scalability, while simultaneously optimizing their power footprints and permitting a broad range of resource usage behaviors that may differ across components of the applications and phases of their workflows. Increasing irregularity of workloads and platforms poses a formidable challenge to performance and scalability, in addition to the cross-cutting concerns mentioned above. Irregularity may arise, for instance, from multiple sources within advanced scientific applications and the cause of irregular workloads may vary across applications -- it may arise owing to the need to run multiple dissimilar operations in parallel, or it may arise owing to trends in modern computer architectures, such as dynamic power management, heterogeneous nodes (e.g., some with GPUs or other accelerators), and deep memory hierarchies. The improvement of scalability of HPC applications that can be gained by utilizing technologies such as deep learning (e.g., to prune the parameter search space in ensembles or potentially replacing parts of the modeling workflow) should also be explored. Programming Languages and Compilers: Heterogeneity is one of the thorniest emerging challenges for programming languages and compilers research and takes at least two forms: domain heterogeneity and systems heterogeneity. The former encompasses applications that themselves span many problem domains and associated computation styles. The latter encompasses systems that themselves consist of a set of devices, each with unique computing interfaces (e.g., CPU versus GPU versus FPGA) and unique physical locations in the overall system, with unique programming interfaces and attributes (e.g., efficiency, reliability, memory consistency models). A fundamental challenge in this context is to understand interoperability across applications and across devices, its semantics in the presence of extreme variations in abstractions, and how the semantics can be engineered within programming languages and compilers to obtain scalability across the full hardware/software stack. Security and Privacy: The techniques used to develop extreme scale systems often neglect safety, security, and privacy concerns in favor of performance and scalability. Emerging domains like edge computing, confidential cloud computing, and secure distributed computation introduce new security vulnerabilities and privacy concerns especially when designed explicitly for, and operated at, extreme scale. Massive-scale edge computing applications (e.g., sensor or video monitoring) require sophisticated computations but cannot centralize the gathered data due to communication costs. A difficult challenge is to develop extreme-scale algorithms that can address the security and privacy issues involved. In the context of cloud computing, there are significant concerns about security and privacy. New ideas in cryptography and system/hardware design are enabling much more efficient confidential computing methods, some of which are already being adopted by cloud providers. Research should explore how to run extreme-scale applications in these environments and how to use extreme scale to accelerate confidential computing techniques. Finally, in the context of distributed computations, there are many techniques that are capable of providing strong security and privacy guarantees even if some users or servers are compromised. Research should therefore explore new algorithms and system features that can enable secure and privacy-preserving distributed computation at scale. Systems: The increasing heterogeneity of hardware platforms and the shift towards more domain-specific systems are creating new challenges at all levels of the systems stack, including networks and operating systems. First, with changes in hardware platforms, correctness, robustness, and accuracy have become major concerns: programs often give unexpected results on new platforms owing to differences in hardware semantics (such as various memory types and memory consistency models). Second, the rise of heterogeneous hardware and domain-specific libraries means that applications are increasingly composed of many separately-designed, domain-specific components. Optimizing across components is increasingly important to achieve scalability across the full hardware/software stack. Third, security is an understudied aspect of extreme-scale systems that is critical in de-centralized or privacy-sensitive settings such as edge computing and the public cloud. Security, in this specific context, is aligned with correctness to ensure that existing applications behave well in the presence of adversary-controlled input data. Research should aim to reduce principles of large-scale system design that enable use of components that come from multiple, possibly untrusted third parties, yet also enable performance, portability, correctness, accuracy, and other desirable properties. Theory and Algorithms: One of the biggest challenges is to develop appropriate computational models for the many new features of modern large-scale systems. These features include complicated memory hierarchies, new memory technologies, heterogeneity, support for remote direct memory access, frequency scaling, smart memories, energy-saving modes, and application-specific hardware. A second challenge involves providing fault tolerance in extreme-scale distributed systems. As systems get larger, it becomes impractical to ensure that all components continuously function without faults. The challenge is to develop a theory of reliability that addresses different kinds of faults. A third challenge is to consider environments with changing resources and multiple shared users. Much existing theory on parallel algorithms assumes full control over a fixed collection of resources, but this assumption can limit applicability in the context of cloud resources, faults, and more dynamic workloads. Existing theories of distributed, parallel, streaming, and sublinear algorithms should be adapted and extended as necessary and appropriate to address the challenges listed above. II.B. Planning and LARGE Projects The purpose of a Planning Project is to develop the team, research infrastructure, and community needed to demonstrate and establish readiness for a LARGE project. While a Planning Proposal is required to have at least four focus areas along with an overarching vision, it may not have expertise in all four, instead aiming at establishing the full team during the execution of the project. Planning activities might include, but are not limited to, workshops, team-building, establishing outside collaborations, as well as preliminary research and proofs of concept. In contrast, a LARGE Proposal is expected to present a full-scale research project that offers the required expertise for all of its focus areas, along with synergy across the team. LARGE projects must provide: A Management and Coordination plan (3-page limit, to be submitted as a Supplementary Document): Every LARGE proposal must contain a clearly labeled “Management and Coordination Plan”, which includes: 1) the specific roles of the PI, co-PIs, other senior personnel, and paid consultants at all organizations involved to demonstrate that the project personnel have distinct but complementary expertise at different levels of the hardware/software stack, and in at least four of the program’s focus areas; 2) how the project will be managed across organizations and expertise; 3) identification of the specific coordination mechanisms that will enable cross-organization and/or cross-expertise scientific integration and achieve synergy within the team; and 4) pointers to the budget line items that support these management and coordination mechanisms. III. Award InformationAnticipated Type of Award: Standard Grants and Continuing Grants Estimated Number of Awards: 28 Planning Grants: Approximately 8 awards will be made in FY 2021, and 4 awards in FY 2022, pending availability of funds and quality of proposals received. LARGE Grants: Approximately 4 awards will be made each year in FY 2021, FY 2022, FY 2023, and FY 2024, pending availability of funds and quality of proposals received. Anticipated Funding Amount: $83,000,000 Planning Grants: Up to $250,000 per award with duration up to 1 year. LARGE Grants: Up to $1,000,000 per year with duration up to 5 years. Estimated program budget, number of awards, and average award size/duration are subject to the availability of funds and quality of proposal received. IV. Eligibility InformationWho May Submit Proposals:
Who May Serve as PI:
Limit on Number of Proposals per Organization:
Limit on Number of Proposals per PI or Co-PI: 3
V. Proposal Preparation And Submission InstructionsA. Proposal Preparation InstructionsFull Proposal Preparation Instructions: Proposers may opt to submit proposals in response to this Program Solicitation via FastLane, Research.gov, or Grants.gov.
In determining which method to utilize in the electronic preparation and submission of the proposal, please note the following: Collaborative Proposals. All collaborative proposals submitted as separate submissions from multiple organizations must be submitted via the NSF FastLane system. PAPPG Chapter II.D.3 provides additional information on collaborative proposals. See PAPPG Chapter II.C.2 for guidance on the required sections of a full research proposal submitted to NSF. Please note that the proposal preparation instructions provided in this program solicitation may deviate from the PAPPG instructions. Proposal titles: Proposal titles must indicate the PPoSS program followed by a colon and indicate the type of proposal, “Planning” or “LARGE”, followed by a colon, then the title of the project. For example, PPoSS: Planning: Title or PPoSS: LARGE: Title. For proposals submitted as part of a set of collaborative proposals, all participating institutions should use the same title, which should begin with "Collaborative Research:" for example, Collaborative Research: PPoSS: LARGE: Title. For proposals from PIs in institutions that have RUI (Research in Undergraduate Institutions) eligibility, the title should include the keyword RUI, e.g. PPoSS: Planning: RUI: Title or PPoSS: Planning: RUI: Collaborative Research: Title. Project Summary: The Project Summary consists of an overview, a statement on the intellectual merit of the proposed activity, and a statement on the broader impacts of the proposed activity. Please provide between 2 and 6 keywords at the end of the overview in the Project Summary. CISE personnel will use this information in implementing the merit review process. The keywords should describe the main scientific/engineering areas explored in the proposal. Keywords should be prefaced with "Keywords" followed by a colon, and the keywords should be separated by semi-colons. Keywords should be of the type used to describe research in a journal submission. They should be included at the end of the overview in the project summary and might appear, for example, as Keywords: energy-aware computing; formal logic; computer graphics; sensor networks; information visualization; privacy. Project Description: Describe the research and education activities to be undertaken in up to 15 pages. Describe curriculum development activities, if any, in a separate heading (included in these page limits) titled "Curriculum Development Activities." All proposals should seek to break and re-define traditional or prevailing abstractions. The Project Description must contain, as a separate section within the narrative, a section labeled, “Focus Areas” that must (a) explicitly state at least four areas covered along with senior personnel with commensurate expertise; (b) describe the targeted distributed applications and systems, and the heterogeneous platforms on which they run; (c) define relevant notions of scale, and describe how scalability will be theoretically and experimentally evaluated with respect to the full hardware/software stack while accounting for cross-cutting concerns such as rigorously-proven correctness and accuracy, security, and privacy; and (d) provide preliminary evidence of end-to-end scalability of one or more of the targeted applications in (b), based on proposed theories and abstractions. Proposals that do not include a section titled “Focus Areas” will be returned without review. Supplementary Documents: In the Supplementary Documents Section, upload the following information where relevant: 1. List of Project Personnel and Partner Organizations (required) (Note: In collaborative proposals, the lead organization should provide this information for all participants): Provide current, accurate information for all personnel and organizations involved in the project. NSF staff will use this information in the merit review process to manage reviewer selection. The list should include all PIs, co-PIs, Senior Personnel, paid/unpaid Consultants or Collaborators, Subawardees, Postdoctoral Researchers, and project-level advisory committee members. This list should be numbered and include (in this order) Full name, Organization(s), and Role in the project, with each item separated by a semi-colon. Each person listed should start a new numbered line. For example:
2. Data Management Plan (required): Proposals must include a Supplementary Document of no more than two pages labeled "Data Management Plan". This Supplementary Document should describe how the proposal will conform to NSF policy on the dissemination and sharing of research results. See Chapter II.C.2.j of the PAPPG for full policy implementation. For additional information on the Dissemination and Sharing of Research Results, see: https://www.nsf.gov/bfa/dias/policy/dmp.jsp. For specific guidance for Data Management Plans submitted to the Directorate for Computer and Information Science and Engineering (CISE) see: https://www.nsf.gov/cise/cise_dmp.jsp. 3. Management and Coordination Plans (required): Every LARGE proposal must contain a clearly labeled “Management and Coordination Plan”, which includes: 1) the specific roles of the PI, co-PIs, other senior personnel, and paid consultants at all organizations involved to demonstrate that the project personnel have distinct but complementary expertise at different levels of the hardware/software stack, and in at least four of the program’s focus areas; 2) how the project will be managed across organizations and expertise; 3) identification of the specific coordination mechanisms that will enable cross-organization and/or cross-expertise scientific integration and achieve synergy within the team; and 4) pointers to the budget line items that support these management and coordination mechanisms. If a LARGE proposal does not include a Management and Coordination Plan of up to 3 pages, the proposal will be returned without review. 4. Documentation of Collaborative Arrangements of Significance to the Proposal: Any substantial collaboration with individuals not included in the budget should be described in the Facilities, Equipment and Other Resources section of the proposal (see Chapter II.C.2.i of the PAPPG) and documented in a letter of collaboration from each collaborator. Such letters should be provided in the Supplementary Documentation section and follow the format instructions specified in Chapter II.C.2.j. Collaborative activities that are identified in the budget should follow the instructions in Chapter II.D.3. 5. Other Specialized Information: RUI Proposals: PIs from predominantly undergraduate institutions should include a Research in Undergraduate Institutions (RUI) Impact Statement and Certification of RUI Eligibility in this section. No other Supplementary Documents, except as permitted by the NSF PAPPG, are allowed. Single Copy Documents: Collaborators and Other Affiliations Information: Proposers should follow the guidance specified in Chapter II.C.1.e of the NSF PAPPG. Note the distinction to item (1) under Supplementary Documents above: the listing of all project participants is collected by the project lead and entered as a Supplementary Document, which is then automatically included with all proposals in a project. The Collaborators and Other Affiliations are entered for each participant within each proposal and, as Single Copy Documents, are available only to NSF staff. Submission Checklist: In an effort to assist proposal preparation, the following checklist is provided as a reminder of some important items that should be checked before submitting a proposal to this solicitation. For the items marked with (RWR), the proposal will be returned without review if the required item is non-compliant at the submission deadline. Note that these are requirements unique to this solicitation; for other return without review requirements, see the PAPPG.
B. Budgetary InformationCost Sharing: Inclusion of voluntary committed cost sharing is prohibited. Other Budgetary Limitations: Proposal budgets must not exceed $5,000,000 for LARGE grants. Proposal budgets must not exceed $250,000 for Planning grants. Budget Preparation Instructions: PI meetings will be held every year for LARGE project awardees at locations in the continental United States, between FY 2022 and FY 2027. The proposal budget should include yearly funds for travel for one PI (or co-PI) of every collaborative project for the duration of the project between FY 2022 and FY 2027. C. Due Dates
D. FastLane/Research.gov/Grants.gov RequirementsFor Proposals Submitted Via FastLane or Research.gov:
For Proposals Submitted Via Grants.gov:
Proposers that submitted via FastLane or Research.gov may use Research.gov to verify the status of their submission to NSF. For proposers that submitted via Grants.gov, until an application has been received and validated by NSF, the Authorized Organizational Representative may check the status of an application on Grants.gov. After proposers have received an e-mail notification from NSF, Research.gov should be used to check the status of an application. VI. NSF Proposal Processing And Review ProceduresProposals received by NSF are assigned to the appropriate NSF program for acknowledgement and, if they meet NSF requirements, for review. All proposals are carefully reviewed by a scientist, engineer, or educator serving as an NSF Program Officer, and usually by three to ten other persons outside NSF either as ad hoc reviewers, panelists, or both, who are experts in the particular fields represented by the proposal. These reviewers are selected by Program Officers charged with oversight of the review process. Proposers are invited to suggest names of persons they believe are especially well qualified to review the proposal and/or persons they would prefer not review the proposal. These suggestions may serve as one source in the reviewer selection process at the Program Officer's discretion. Submission of such names, however, is optional. Care is taken to ensure that reviewers have no conflicts of interest with the proposal. In addition, Program Officers may obtain comments from site visits before recommending final action on proposals. Senior NSF staff further review recommendations for awards. A flowchart that depicts the entire NSF proposal and award process (and associated timeline) is included in PAPPG Exhibit III-1. A comprehensive description of the Foundation's merit review process is available on the NSF website at: https://www.nsf.gov/bfa/dias/policy/merit_review/. Proposers should also be aware of core strategies that are essential to the fulfillment of NSF's mission, as articulated in Building the Future: Investing in Discovery and Innovation - NSF Strategic Plan for Fiscal Years (FY) 2018 – 2022. These strategies are integrated in the program planning and implementation process, of which proposal review is one part. NSF's mission is particularly well-implemented through the integration of research and education and broadening participation in NSF programs, projects, and activities. One of the strategic objectives in support of NSF's mission is to foster integration of research and education through the programs, projects, and activities it supports at academic and research institutions. These institutions must recruit, train, and prepare a diverse STEM workforce to advance the frontiers of science and participate in the U.S. technology-based economy. NSF's contribution to the national innovation ecosystem is to provide cutting-edge research under the guidance of the Nation's most creative scientists and engineers. NSF also supports development of a strong science, technology, engineering, and mathematics (STEM) workforce by investing in building the knowledge that informs improvements in STEM teaching and learning. NSF's mission calls for the broadening of opportunities and expanding participation of groups, institutions, and geographic regions that are underrepresented in STEM disciplines, which is essential to the health and vitality of science and engineering. NSF is committed to this principle of diversity and deems it central to the programs, projects, and activities it considers and supports. A. Merit Review Principles and CriteriaThe National Science Foundation strives to invest in a robust and diverse portfolio of projects that creates new knowledge and enables breakthroughs in understanding across all areas of science and engineering research and education. To identify which projects to support, NSF relies on a merit review process that incorporates consideration of both the technical aspects of a proposed project and its potential to contribute more broadly to advancing NSF's mission "to promote the progress of science; to advance the national health, prosperity, and welfare; to secure the national defense; and for other purposes." NSF makes every effort to conduct a fair, competitive, transparent merit review process for the selection of projects. 1. Merit Review Principles These principles are to be given due diligence by PIs and organizations when preparing proposals and managing projects, by reviewers when reading and evaluating proposals, and by NSF program staff when determining whether or not to recommend proposals for funding and while overseeing awards. Given that NSF is the primary federal agency charged with nurturing and supporting excellence in basic research and education, the following three principles apply:
With respect to the third principle, even if assessment of Broader Impacts outcomes for particular projects is done at an aggregated level, PIs are expected to be accountable for carrying out the activities described in the funded project. Thus, individual projects should include clearly stated goals, specific descriptions of the activities that the PI intends to do, and a plan in place to document the outputs of those activities. These three merit review principles provide the basis for the merit review criteria, as well as a context within which the users of the criteria can better understand their intent. 2. Merit Review Criteria All NSF proposals are evaluated through use of the two National Science Board approved merit review criteria. In some instances, however, NSF will employ additional criteria as required to highlight the specific objectives of certain programs and activities. The two merit review criteria are listed below. Both criteria are to be given full consideration during the review and decision-making processes; each criterion is necessary but neither, by itself, is sufficient. Therefore, proposers must fully address both criteria. (PAPPG Chapter II.C.2.d(i). contains additional information for use by proposers in development of the Project Description section of the proposal). Reviewers are strongly encouraged to review the criteria, including PAPPG Chapter II.C.2.d(i), prior to the review of a proposal. When evaluating NSF proposals, reviewers will be asked to consider what the proposers want to do, why they want to do it, how they plan to do it, how they will know if they succeed, and what benefits could accrue if the project is successful. These issues apply both to the technical aspects of the proposal and the way in which the project may make broader contributions. To that end, reviewers will be asked to evaluate all proposals against two criteria:
The following elements should be considered in the review for both criteria:
Broader impacts may be accomplished through the research itself, through the activities that are directly related to specific research projects, or through activities that are supported by, but are complementary to, the project. NSF values the advancement of scientific knowledge and activities that contribute to achievement of societally relevant outcomes. Such outcomes include, but are not limited to: full participation of women, persons with disabilities, and underrepresented minorities in science, technology, engineering, and mathematics (STEM); improved STEM education and educator development at any level; increased public scientific literacy and public engagement with science and technology; improved well-being of individuals in society; development of a diverse, globally competitive STEM workforce; increased partnerships between academia, industry, and others; improved national security; increased economic competitiveness of the United States; and enhanced infrastructure for research and education. Proposers are reminded that reviewers will also be asked to review the Data Management Plan and the Postdoctoral Researcher Mentoring Plan, as appropriate. Additional Solicitation Specific Review Criteria Planning Proposals All proposals must clearly address the following solicitation-specific review criteria through well-identified proposal elements.
LARGE Proposals All proposals must clearly address the following solicitation-specific review criteria through well-identified proposal elements.
B. Review and Selection ProcessProposals submitted in response to this program solicitation will be reviewed by Ad hoc Review and/or Panel Review. Reviewers will be asked to evaluate proposals using two National Science Board approved merit review criteria and, if applicable, additional program specific criteria. A summary rating and accompanying narrative will generally be completed and submitted by each reviewer and/or panel. The Program Officer assigned to manage the proposal's review will consider the advice of reviewers and will formulate a recommendation. After scientific, technical and programmatic review and consideration of appropriate factors, the NSF Program Officer recommends to the cognizant Division Director whether the proposal should be declined or recommended for award. NSF strives to be able to tell applicants whether their proposals have been declined or recommended for funding within six months. Large or particularly complex proposals or proposals from new awardees may require additional review and processing time. The time interval begins on the deadline or target date, or receipt date, whichever is later. The interval ends when the Division Director acts upon the Program Officer's recommendation. After programmatic approval has been obtained, the proposals recommended for funding will be forwarded to the Division of Grants and Agreements for review of business, financial, and policy implications. After an administrative review has occurred, Grants and Agreements Officers perform the processing and issuance of a grant or other agreement. Proposers are cautioned that only a Grants and Agreements Officer may make commitments, obligations or awards on behalf of NSF or authorize the expenditure of funds. No commitment on the part of NSF should be inferred from technical or budgetary discussions with a NSF Program Officer. A Principal Investigator or organization that makes financial or personnel commitments in the absence of a grant or cooperative agreement signed by the NSF Grants and Agreements Officer does so at their own risk. Once an award or declination decision has been made, Principal Investigators are provided feedback about their proposals. In all cases, reviews are treated as confidential documents. Verbatim copies of reviews, excluding the names of the reviewers or any reviewer-identifying information, are sent to the Principal Investigator/Project Director by the Program Officer. In addition, the proposer will receive an explanation of the decision to award or decline funding. VII. Award Administration InformationA. Notification of the AwardNotification of the award is made to the submitting organization by a Grants Officer in the Division of Grants and Agreements. Organizations whose proposals are declined will be advised as promptly as possible by the cognizant NSF Program administering the program. Verbatim copies of reviews, not including the identity of the reviewer, will be provided automatically to the Principal Investigator. (See Section VI.B. for additional information on the review process.) B. Award ConditionsAn NSF award consists of: (1) the award notice, which includes any special provisions applicable to the award and any numbered amendments thereto; (2) the budget, which indicates the amounts, by categories of expense, on which NSF has based its support (or otherwise communicates any specific approvals or disapprovals of proposed expenditures); (3) the proposal referenced in the award notice; (4) the applicable award conditions, such as Grant General Conditions (GC-1)*; or Research Terms and Conditions* and (5) any announcement or other NSF issuance that may be incorporated by reference in the award notice. Cooperative agreements also are administered in accordance with NSF Cooperative Agreement Financial and Administrative Terms and Conditions (CA-FATC) and the applicable Programmatic Terms and Conditions. NSF awards are electronically signed by an NSF Grants and Agreements Officer and transmitted electronically to the organization via e-mail. *These documents may be accessed electronically on NSF's Website at https://www.nsf.gov/awards/managing/award_conditions.jsp?org=NSF. Paper copies may be obtained from the NSF Publications Clearinghouse, telephone (703) 292-8134 or by e-mail from nsfpubs@nsf.gov. More comprehensive information on NSF Award Conditions and other important information on the administration of NSF awards is contained in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) Chapter VII, available electronically on the NSF Website at https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg. C. Reporting RequirementsFor all multi-year grants (including both standard and continuing grants), the Principal Investigator must submit an annual project report to the cognizant Program Officer no later than 90 days prior to the end of the current budget period. (Some programs or awards require submission of more frequent project reports). No later than 120 days following expiration of a grant, the PI also is required to submit a final project report, and a project outcomes report for the general public. Failure to provide the required annual or final project reports, or the project outcomes report, will delay NSF review and processing of any future funding increments as well as any pending proposals for all identified PIs and co-PIs on a given award. PIs should examine the formats of the required reports in advance to assure availability of required data. PIs are required to use NSF's electronic project-reporting system, available through Research.gov, for preparation and submission of annual and final project reports. Such reports provide information on accomplishments, project participants (individual and organizational), publications, and other specific products and impacts of the project. Submission of the report via Research.gov constitutes certification by the PI that the contents of the report are accurate and complete. The project outcomes report also must be prepared and submitted using Research.gov. This report serves as a brief summary, prepared specifically for the public, of the nature and outcomes of the project. This report will be posted on the NSF website exactly as it is submitted by the PI. More comprehensive information on NSF Reporting Requirements and other important information on the administration of NSF awards is contained in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) Chapter VII, available electronically on the NSF Website at https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg. VIII. Agency ContactsPlease note that the program contact information is current at the time of publishing. See program website for any updates to the points of contact. General inquiries regarding this program should be made to:
For questions related to the use of FastLane or Research.gov, contact:
For questions relating to Grants.gov contact:
IX. Other InformationThe NSF website provides the most comprehensive source of information on NSF Directorates (including contact information), programs and funding opportunities. Use of this website by potential proposers is strongly encouraged. In addition, "NSF Update" is an information-delivery system designed to keep potential proposers and other interested parties apprised of new NSF funding opportunities and publications, important changes in proposal and award policies and procedures, and upcoming NSF Grants Conferences. Subscribers are informed through e-mail or the user's Web browser each time new publications are issued that match their identified interests. "NSF Update" also is available on NSF's website. Grants.gov provides an additional electronic capability to search for Federal government-wide grant opportunities. NSF funding opportunities may be accessed via this mechanism. Further information on Grants.gov may be obtained at https://www.grants.gov. About The National Science FoundationThe National Science Foundation (NSF) is an independent Federal agency created by the National Science Foundation Act of 1950, as amended (42 USC 1861-75). The Act states the purpose of the NSF is "to promote the progress of science; [and] to advance the national health, prosperity, and welfare by supporting research and education in all fields of science and engineering." NSF funds research and education in most fields of science and engineering. It does this through grants and cooperative agreements to more than 2,000 colleges, universities, K-12 school systems, businesses, informal science organizations and other research organizations throughout the US. The Foundation accounts for about one-fourth of Federal support to academic institutions for basic research. NSF receives approximately 55,000 proposals each year for research, education and training projects, of which approximately 11,000 are funded. In addition, the Foundation receives several thousand applications for graduate and postdoctoral fellowships. The agency operates no laboratories itself but does support National Research Centers, user facilities, certain oceanographic vessels and Arctic and Antarctic research stations. The Foundation also supports cooperative research between universities and industry, US participation in international scientific and engineering efforts, and educational activities at every academic level. Facilitation Awards for Scientists and Engineers with Disabilities (FASED) provide funding for special assistance or equipment to enable persons with disabilities to work on NSF-supported projects. See the NSF Proposal & Award Policies & Procedures Guide Chapter II.E.6 for instructions regarding preparation of these types of proposals. The National Science Foundation has Telephonic Device for the Deaf (TDD) and Federal Information Relay Service (FIRS) capabilities that enable individuals with hearing impairments to communicate with the Foundation about NSF programs, employment or general information. TDD may be accessed at (703) 292-5090 and (800) 281-8749, FIRS at (800) 877-8339. The National Science Foundation Information Center may be reached at (703) 292-5111.
Privacy Act And Public Burden StatementsThe information requested on proposal forms and project reports is solicited under the authority of the National Science Foundation Act of 1950, as amended. The information on proposal forms will be used in connection with the selection of qualified proposals; and project reports submitted by awardees will be used for program evaluation and reporting within the Executive Branch and to Congress. The information requested may be disclosed to qualified reviewers and staff assistants as part of the proposal review process; to proposer institutions/grantees to provide or obtain data regarding the proposal review process, award decisions, or the administration of awards; to government contractors, experts, volunteers and researchers and educators as necessary to complete assigned work; to other government agencies or other entities needing information regarding applicants or nominees as part of a joint application review process, or in order to coordinate programs or policy; and to another Federal agency, court, or party in a court or Federal administrative proceeding if the government is a party. Information about Principal Investigators may be added to the Reviewer file and used to select potential candidates to serve as peer reviewers or advisory committee members. See System of Record Notices, NSF-50, "Principal Investigator/Proposal File and Associated Records," and NSF-51, "Reviewer/Proposal File and Associated Records.” Submission of the information is voluntary. Failure to provide full and complete information, however, may reduce the possibility of receiving an award. An agency may not conduct or sponsor, and a person is not required to respond to, an information collection unless it displays a valid Office of Management and Budget (OMB) control number. The OMB control number for this collection is 3145-0058. Public reporting burden for this collection of information is estimated to average 120 hours per response, including the time for reviewing instructions. Send comments regarding the burden estimate and any other aspect of this collection of information, including suggestions for reducing this burden, to: Suzanne H. Plimpton |
