This $500,000 National Science Foundation Project Grant supports research at the University of North Carolina at Chapel Hill to develop efficient implementations of multi-level budget enforcement in complex multithreaded real-time systems running on multicore computers. The research will identify the levels at which budgets must be enforced, examine implications for safety certification of such enforcement, and produce efficient enforcement mechanisms. This work aligns with the goals of the...
This $599,943 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) aims to develop techniques for more efficient and resilient real-time communications in critical cyber-physical systems like aircraft, automobiles, and industrial control networks. The key innovations include creating holistic models, algorithms, and software designs to achieve the scalability, adaptability, and resiliency...
The National Science Foundation awarded a $499,752 Project Grant to The Washington University under the Computer and Information Science and Engineering program. The grant will support research into developing more efficient schedulability analysis algorithms for safety-critical real-time systems. The Principal Investigator will investigate using integer linear program solvers to represent common schedulability analysis problems in a manner that can be solved efficiently. A methodology will be...
This $275,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop and test new scheduling algorithms for improving the performance of modern database systems. The goal is to create models and policies that can efficiently allocate limited hardware resources, such as compute and memory, to handle a stream of parallelizable database queries with varying levels of parallelizability and service...
The National Science Foundation (NSF) awarded a $174,200 Project Grant under its Computer and Information Science and Engineering (CFDA 47.070) program to the University of North Carolina at Chapel Hill (UNC-CH) to develop new resource allocation policies for optimizing the scheduling of parallelizable machine learning (ML) training workloads on shared hardware clusters. The goal is to enable the rapid and efficient training of highly accurate ML models using limited computing resources. This...
This National Science Foundation project grant of $597,585 will fund research into co-designed control and scheduling adaptation for cyber-physical system safety and performance from April 2023 through March 2026. The award is provided through the Computer and Information Science and Engineering program (CFDA 47.070), which supports investigator-initiated research and education in all areas of computing, communications, and information science and engineering. Specifically, a team led by...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support research at the University of California, Santa Cruz (UCSC) to develop new methods for online scheduling algorithms. The $190,473 award, effective July 1, 2025 through June 30, 2026, aims to investigate the effectiveness of online scheduling techniques for a variety of computing problems. The research objectives include developing new...
This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) provides $592,000 to Purdue University to support collaborative research on co-designed control and scheduling adaptation for cyber-physical system safety and performance from April 2023 through March 2026. The award aims to develop new models, analyses, infrastructure and metrics to represent and account for interdependencies between control and scheduling in...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program Project Grant award of $599,084 to The Research Foundation for The State University of New York (RF SUNY) aims to enhance the timeliness and power-efficiency of real-time data services. The 3-year project, beginning October 1, 2023, will investigate novel methodologies to improve the capabilities of cost-efficient real-time embedded databases supporting data-intensive applications like smart...
This Project Grant award of $279,103 from the National Science Foundation's (NSF) Integrative Activities program (CFDA 47.083) supports the University of Kansas Center for Research Inc. in developing an integrated algorithmic and machine learning-based approach to enhance resource scheduling in high-performance computing (HPC) systems. The key goals are to address uncertainty in emerging HPC applications, resource contention, and workflow variations by designing novel scheduling algorithms and...