Correctness for Scientific Computing Systems
Closed Posted
- Opportunity number
- 24-571
- Agency
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National Science Foundation
- Applications due
- Award size
- Not on record
Opportunity facts
- Assistance listings
- Funding instrument
- Grant
- Category
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- Science and Technology and other Research and Development
- Eligible applicants
-
- Other
- Points of contact
- Full announcement
Opportunity details come from Grants.gov. Updated .
About this opportunity
The Correctness for Scientific Computing Systems (CS2) is a joint program between the National Science Foundation (NSF) and the Department of Energy (DOE) focusing on elevating correctness as a fundamental requirement for scientific computing tools and workflows. The program aims to address challenges in scientific computing by ensuring the absence of faulty behaviors such as numerical rounding errors, floating-point exceptions, data races, deadlocks, and memory faults. Key objectives include proving correctness in performant scientific computing systems, with a particular emphasis on developing approaches that can handle inherently statistical applications, probabilistic algorithms, and uncertain data. The evaluation criteria will likely prioritize research proposals that demonstrate innovative methods for verifying system correctness, particularly those that can develop robust static and runtime program analyses. The current grant opportunity is open, with a response deadline of August 11, 2026, providing researchers with an extensive window to develop and submit comprehensive proposals.
While specific award amounts are not explicitly stated in the grant description, the associated federal grant programs (Computer and Information Science and Engineering and Office of Science Financial Assistance Program) typically provide funding ranges between $100,000 and $1,200,000, with project durations spanning 1-5 years. The research is expected to be conducted at academic institutions, national laboratories, or research organizations across the United States, with a focus on collaborative, hypothesis-driven research that can advance scientific computing methodologies. The program emphasizes close collaboration between research teams and requires a comprehensive approach to understanding and proving computational system correctness across various scientific domains.
Synopsis
Correctness for Scientific Computing Systems (CS2) is a joint program of the National Science Foundation (NSF) and the Department of Energy (DOE). The program addresses challenges that are both core to DOE's mission and essential to NSF's mission of ensuring broad scientific progress. The program's overarching goal is to elevate correctness as a fundamental requirement for scientific computing tools and tool chains, spanning low-level libraries through complex multi-physics simulations and emerging scientific workflows. At an elementary level, correctness of a system means that desired behavioral properties will be satisfied during the system's execution. In the context of scientific computing, correctness can be understood, at both the level of software and hardware, as absence of faulty behaviors such as excessive numerical rounding, floating-point exceptions, data races deadlocks, memory faults, violations of specifications at interfaces of system modules, and so on. The CS2 program puts correctness on an equal footing with performance, the focus of current scientific computing research. This program envisions the necessity of proving correctness even in performant scientific computing systems. Such correctness proofs themselves might rely upon multiple factors, including correctness of static and runtime program analyses. Recognizing that many scientific computing applications are inherently statistical, use probabilistic or randomized algorithms, and/or deal with uncertain data, probabilistic notions of correctness may be needed. It is also critical to realize that correctness guarantees are provided with respect to some pre-defined system model. For many reasons, including misspecification, approximation, and defect, the state space allowed by real systems might depart from that model. When this happens, the ability to probe the system to isolate the discrepancy is a key challenge in many domains. CS2 requires close and continuous collaboration between researchers in two complementary areas of expertise. One area is scientific computing, which, for this solicitation, is broadly construed to include: models and simulations of scientific theories; management and analysis of data from scientific simulations, observations, and experiments; libraries for numerical computation; and allied topics. The second area is formal reasoning and mechanized proving of properties of programs, which, for this solicitation, is broadly construed to include automatic/interactive/auto-active verification, runtime verification, type systems, abstract interpretation, programming languages, program analysis, program logic, compilers, concurrency, stochastic reasoning, static and dynamic testing, property-based testing, and allied topics.
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