Project Grant 2503641
- This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $160,465 to Iowa State University to research techniques for mitigating the effects of stragglers (slow or failed workers) in distributed matrix computations. The project aims to develop coded computation methods that can handle sparse input matrices and leverage partial computations from slow workers, enabling more efficient large-scale matrix computations critical for modern...
- This Project Grant award of $299,996 from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) supports collaborative research by Trustees of Boston University on developing novel algorithms and frameworks for efficient distributed processing of large datasets. The key technical focus is on enhancing the Approximate Message Passing framework to enable asynchronous, stochastic, and distributed data processing while maintaining strong performance...
- This federal Project Grant award of $203,796.00 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) program supports collaborative research to accelerate the execution of large graph problems on large, distributed computing systems. The key objectives are to develop new algorithms for graph clustering, graph construction, and applying machine learning techniques to these complex graph computations. The project also seeks to create a...
- This Project Grant award, valued at $600,000.00, was provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The award, with a performance period from January 1, 2026 to December 31, 2028, is supporting research by the Regents of the University of Michigan in the areas of extremal combinatorics and the analysis of algorithms. The primary goals are to solve basic classification questions in the theory of...
- This $256,710 National Science Foundation award under the Computer and Information Science and Engineering (CFDA 47.070) program supports a collaborative research project led by the University of Texas at Austin. The project investigates full-stack implementation methodologies for developing expressive programming systems that bridge the gap between high-level specifications and high-performance implementations of complex reasoning tasks at scale. Key focus areas include extending declarative...
- This federal Project Grant award, titled "A Scalable, Polymorphic, and Efficient Architecture for Irregular and Sparse Computations (APEX)", was awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The $104,155 award, effective March 1, 2025 through February 28, 2030, supports research to address challenges in accelerating sparse and irregular computations prevalent in applications such as...
- This $174,666 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) program supports the development of a "Scalable and Efficient Adaptive Mixed-Precision Framework for Scientific and AI Workloads on GPUs" (SEAM). The project, led by Saint Louis University, aims to create an adaptive mixed-precision framework to optimize performance for scientific and artificial intelligence workloads across heterogeneous computing...
- This Project Grant award from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) provides $286,991 to Georgia Tech Research Corporation to develop new theoretical frameworks, analyses, and techniques for distributed computing and machine learning. The key goals are to: (i) accelerate computation time by overcoming system bottlenecks, (ii) ensure accurate computation in the presence of hardware errors and faults, and (iii) enable data-processing...
- This $325,000 federal Project Grant was awarded by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program. The goal of the project is to develop techniques that leverage accelerators and preconditioners to speed up the training of large artificial intelligence (AI) models, with a focus on exploiting insights from numerical methods. The investigators will explore the relationship between mini-batching and its impact on the convergence speed and...
- This federal Project Grant award of $150,000.00 was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports collaborative research focused on the "structure vs randomness" paradigm, which aims to identify structured properties in mathematical objects and leverage randomness for their analysis and algorithm design. The key goals are to develop a versatile theoretical framework and apply it...
This federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $128,479.00 to The University of Akron for collaborative research on techniques to mitigate the effect of stragglers (slow or failed workers) in distributed matrix computations. The research aims to develop coded computation approaches that are better suited for sparse input matrices, and leverage partial computations from slow workers. This work will provide training for students on cloud platform usage and create outreach activities for mathematics tutoring and K-12 computer science modules. The award period runs from October 1, 2025 to September 30, 2028. The research seeks to advance scientific knowledge and technological innovation in areas critical to modern technologies like deep learning, large language models, and scientific computing.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $128.5k | 8/26/25 |