Project Grant 2230944
- This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CISE) program, titled "COLLABORATIVE RESEARCH: CNS CORE: SMALL: A COMPILATION SYSTEM FOR MAPPING DEEP LEARNING MODELS TO TENSORIZED INSTRUCTIONS (DELITE)", provides $299,999 in funding to the University Of Georgia Research Foundation, Inc. over a 3-year period from October 1, 2023 through September 30, 2026. The grant supports the development of a compilation system...
- The National Science Foundation (NSF) awarded a $329,183 Project Grant to the College of William & Mary under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant, awarded on October 1, 2023, will fund the development of a framework and methodology to enable researchers and software engineers to better interpret the behavior of AI-powered developer tools that leverage neural language models for source code. The project aims to generate global and local...
- The National Science Foundation (NSF) Division of Computer and Network Systems awarded a $174,178 project grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the President and Board of Trustees of Santa Clara College. The project aims to develop methods and a system for deploying complex machine learning (ML) models on network processing units (NPUs) to enable ultra low-latency performance for modern applications such as self-driving, security threat...
- This $900,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will fund research at Virginia Polytechnic Institute & State University to develop a comprehensive framework for efficient, scalable, and performance-portable tensor applications. The five-year award beginning July 2022 aims to address challenges in sustaining improved computing performance and developer productivity as hardware customization increases due...
- The U.S. National Science Foundation (NSF) awarded a $120,120 CAREER grant under the Computer and Information Science and Engineering (CISE) program to The Johns Hopkins University. The project, titled "DEEPMATTER: A Scalable and Programmable Embedded Deep Neural Network", will develop novel methodologies for optimizing deep neural network (DNN) models to enable their deployment on embedded systems with limited hardware resources and power budgets. The research aims to create new DNN...
- Project Grant Summary Massachusetts Institute of Technology (MIT) received a $600,000 CAREER award from the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective July 1, 2025, through June 30, 2030. The project focuses on developing efficient architectures and algorithms for large language models (LLMs) to reduce computational costs while improving accessibility and...
- The National Science Foundation (NSF) has awarded a $750,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of Wisconsin System for the "COLLABORATIVE RESEARCH: FRAMEWORKS: DIAMOND: DEMOCRATIZING LARGE NEURAL NETWORK MODEL TRAINING FOR SCIENCE" project. This 3-year effort aims to develop the DIAMOND service, which will democratize access to cutting-edge deep learning (DL) methods by abstracting the use of high-performance...
- The National Science Foundation (NSF) awarded a $453,266 Project Grant under the Engineering program (CFDA #47.041) to Wellesley College to develop and test AI-powered programming tools to assist social and natural scientists with computer programming tasks. The goal is to harness AI to make programming more accessible and efficient for scientists, thereby accelerating scientific discovery, lowering research costs, and broadening participation in scientific work. Wellesley College is...
- Federal Grant Award Summary George Mason University received a $274,265 Project Grant from the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to develop DLToolkit, a performance profiling and analysis infrastructure designed for scientific deep learning (DL) workloads. The award, effective June 15, 2025, through May 31, 2028, will deliver three core technical capabilities:...
- This three-year, $276,611 National Science Foundation Project Grant supports research at the University at Albany to develop algorithms and theory for compressing deep neural networks. Funded through NSF's Mathematical and Physical Sciences program (CFDA 47.049), this award will advance knowledge in discrete optimization and machine learning. Key products include new coarse gradient and thresholding algorithms to enable efficient deployment of AI systems on mobile and low-power platforms. By...
The National Science Foundation (NSF) has awarded a $299,999 Project Grant to the College of William & Mary under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant, titled "COLLABORATIVE RESEARCH: CNS CORE: SMALL: A COMPILATION SYSTEM FOR MAPPING DEEP LEARNING MODELS TO TENSORIZED INSTRUCTIONS (DELITE)," will fund research to develop a compilation system that can optimize deep neural network (DNN) workloads for emerging tensorized instruction sets in modern hardware architectures. The key objectives include improving the execution efficiency of DNN operators through local instruction selection, formulating global optimizations to minimize data transformation costs, and addressing challenges with dynamic DNN models and sparse computations. The research will culminate in a reusable system that can generate tensor and LLVM IRs from DNN computational graphs, benefiting areas like high-performance computing, compilers, and AI/ML systems. The project will run from October 1, 2023 to September 30, 2026.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $300.0k | 7/26/23 |