Project Grant 2313124
- 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 $540,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program aims to develop a comprehensive framework called FZ to enable scientific users to intuitively research, compose, implement, and test specialized lossy data compression techniques. The project will build on existing capabilities from various open-source data compression tools to create an intuitive cyberinfrastructure for the composition of specialized...
- This $299,999 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support a collaborative research initiative aimed at mitigating data compression artifacts in scientific data. The project, led by Miami University, will develop a novel learning-driven framework to improve the integrity and quality of lossy-compressed scientific data, facilitating more efficient data storage, transmission, and analytics...
- This $299,999 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program, with a period of performance from July 1, 2025 to June 30, 2028, will fund the development of a cyberinfrastructure that seamlessly and adaptively integrates lossy data compression into deep learning pipelines for scientific applications. This integration is intended to reduce memory usage and communication overhead, enabling AI-powered scientific applications...
- This Project Grant award from the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CFDA 47.070) program provides $201,765 to The University Of Kentucky Research Foundation (the Research Foundation) to develop advanced lossy compression techniques and software that preserve topological features in scientific data for in situ and post hoc analysis and visualization at extreme scales. The project aims to tackle...
- This $300,000 Project Grant award from the National Science Foundation's (CFDA 47.070) Computer and Information Science and Engineering program will support the development of a cyberinfrastructure that seamlessly integrates lossy compression into deep learning pipelines within scientific applications. The goal is to reduce memory usage and communication overhead, enabling AI-powered scientific applications to scale to massive datasets across disciplines like weather forecasting, astronomy,...
- 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 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) Project Grant award of $272,992 will support a collaborative research project at Texas State University titled "SCIOPT: Toward Certifiable Compression-Aware SCIML Systems." The project aims to develop techniques to reduce the volume of data exchanged in high-performance scientific computing and scientific machine learning (SCIML) applications without...
- 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 $819,000 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) will fund a collaborative research project titled "SCIOPT: Toward Certifiable Compression-Aware SCIML Systems" at the University of Utah. The project aims to develop techniques to reduce the volume of data exchanged in high-performance scientific simulations and scientific machine learning (SCIML) applications without sacrificing accuracy. Key...
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 features for analysis and visualization. The resulting compression software and algorithms will be integrated into curricula and shared through workshops to advance the research cyberinfrastructure for exascale computing systems and enable more efficient data processing across multiple scientific disciplines.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $198.2k | 8/24/23 |