Project Grant DESC0026005

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 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 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 Project Grant award from the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure, under the NSF Computer and Information Science and Engineering (CFDA 47.070) program, aims to develop a new data representation and storage system called LABIOS to address the challenges of storing and accessing massive and complex data sets in data-intensive computing. The $599,999 award to the Illinois Institute of Technology (IIT) will fund research to design and implement LABIOS, a...

This $300,000 Project Grant awarded by the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to the Massachusetts Institute of Technology (MIT) will support the development of advanced machine learning (ML) algorithms and data compression techniques to address the 200 TB/s data rate challenge for the LHCb Upgrade II experiment at CERN's Large Hadron Collider. Specifically, the project will extend the functionality of the HLS4ML software...

This two-year, $500,000 project grant from the National Science Foundation's Office of Advanced Cyberinfrastructure, under the Computer and Information Science and Engineering program (CFDA 47.070), will support Duke University in developing the Flexible Affordable Scalable Technology for Research Storage system. Commonly known as FAST, this shared research storage system utilizes commodity data center hardware and open source Ceph software to provide flexible, high-performance, and...

This $494,701 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 supports research to improve in-situ data analytics capabilities for high-performance computing (HPC) systems. The primary objectives are to develop compression techniques that allow queries to be executed directly on compressed data without decompression, implement these techniques efficiently on...

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...

The National Science Foundation (NSF) awarded a $299,354 Project Grant under the Computer and Information Science and Engineering (CISE) program to The University of Kentucky Research Foundation. This 3-year collaborative research project aims to develop a novel learning-driven framework to mitigate compression artifacts in scientific data compressors. The research will investigate and characterize compression artifacts, design deep learning models to address artifact mitigation, and validate...

This Project Grant award of $174,965.00 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of an intelligent error control framework for progressive data management on multi-tier storage systems. The project aims to advance next-generation data reduction and management techniques to benefit scientific users and expedite discoveries. Specifically, the effort will develop an efficient progressive data management...