Project Grant 2344717
Award Date
9/1/23
Completion Date
7/31/27
Dollars Obligated
$540K
Federal Agency
Office of Advanced Cyberinfrastructure
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Tallahassee, FL 32306, USA
Similar Awards
This National Science Foundation (NSF) award under the Computer and Information Science and Engineering program (CFDA 47.070) provides $579,943 to The Ohio State University to develop a comprehensive cyberinfrastructure framework called FZ to streamline the creation of specialized lossy data compression software for scientific applications. The key products and services include: Creating programming interfaces and a compressor generator to enable the development of new lossy compressors from...
This $198,234 Project Grant awarded by the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure (CFDA 47.070 - Computer and Information Science and Engineering) supports research and development of advanced lossy data compression techniques that preserve topological features in scientific data. The project aims to develop algorithms to effectively reduce the size of large-scale scientific simulation data, such as from fusion and climate modeling, while preserving critical...
This Project Grant from the National Science Foundation's Office of Advanced Cyberinfrastructure, under the Computer and Information Science and Engineering federal grant program (CFDA 47.070), provides $203,483 to Indiana University to develop an objective-driven adaptive hybrid lossy compression framework for extreme-scale scientific applications. The framework aims to automatically construct the best-fit compression strategy for diverse user objectives in data-intensive scientific research....
This $199,989 project grant, awarded by the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CFDA 47.070) program, aims to research and develop advanced lossy data compression techniques that preserve topological features in large-scale scientific data. The project at The Ohio State University will tackle the data compression, analysis, and visualization needs of extreme-scale scientific simulations by creating a...
This National Science Foundation (NSF) Project Grant award for $599,999 supports research at Cornell University from June 15, 2023 to May 31, 2026. The objective is to develop a "modern theory of data compression" to explain the performance of artificial neural network-based compression algorithms and identify avenues for future improvements. The research aims to advance the field of data compression, which has important implications for enabling more realistic and immersive...
This National Science Foundation (NSF) Project Grant awarded under the Computer and Information Science and Engineering program (CFDA 47.070) provides $399,998 to the University of Hawaii at Manoa to support collaborative research on developing fundamental theory and methods for learning-based lossless and lossy data compression. The research aims to understand how machine learning algorithms can be used to compress data more efficiently, with applications in reducing wireless spectrum usage and...
This $200,000 Project Grant award from the National Science Foundation (NSF) Division of Computing and Communication Foundations, under CFDA 47.070 "Computer and Information Science and Engineering", funds research to develop fundamental theory and performance bounds for using machine learning approaches to enable more efficient data compression for applications like wireless communications and mobile devices. The key products and services to be delivered include: 1) Investigating...
The National Science Foundation (NSF) awarded a $175,000 Computer and Information Science and Engineering (CISE) Program grant to The Trustees of the Stevens Institute of Technology to develop a compressor-assisted collective communication framework for large-scale deep learning on GPU-based systems. The two-year project aims to address challenges with the communication overhead of training massive deep learning models by investigating efficient lossy compression techniques for gradient data and...
This $350,000 Project Grant from the National Science Foundation Office of Advanced Cyberinfrastructure, under the Computer and Information Science and Engineering program (CFDA 47.070), will fund the development of a systematic approach to minimize compression error propagation in high-performance computing applications. Specifically, the University of Iowa will receive funding from August 2022 through July 2025 to create an accurate and efficient fault injection infrastructure integrated...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) for $299,354 provides funding to develop a novel learning-driven framework to mitigate artifacts produced by scientific data compressors. The project aims to improve the integrity and quality of lossy-compressed scientific data, facilitating more efficient data storage, transmission, and analytics across domains including climatology, cosmology, fusion energy...