Project Grant 2514036

Award Date 8/1/25
Completion Date 7/31/28
Dollars Obligated $240K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Chicago, IL 60637, USA
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This Project Grant award, with a total funding of $180,000, was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program. The primary awardee is The University Of Kentucky Research Foundation. The objective of this 3-year project, which runs from August 1, 2025 to July 31, 2028, is to develop a user-friendly, high-performance, and portable GPU-accelerated data reduction cyberinfrastructure, called SGCC, for...
This $179,988 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of a user-friendly, high-performance, and portable GPU-accelerated data reduction cyberinfrastructure called SGCC. The University of Houston System, a Hispanic Serving Institution, will build this open-source cyberinfrastructure by porting, extending, and optimizing existing GPU-based data compression...
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 Project Grant award of $299,354 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of a novel learning-driven framework to mitigate artifacts produced by scientific data compressors. The goal is to improve the integrity and quality of lossy-compressed scientific data, facilitating efficient data storage, transmission, and analytics across domains such as climatology, cosmology, fusion energy...
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 $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 $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 $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...
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This $240,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of a user-friendly, high-performance, and portable GPU-accelerated data reduction cyberinfrastructure called the Scientific GPU Compression Cyberinfrastructure (SGCC). The project aims to mitigate data challenges on GPU-equipped supercomputing systems, improve data analysis efficiency, and accelerate scientific discovery. The key products and services to be delivered include:

  1. Porting, extending, and optimizing existing GPU-based data compression capabilities, such as the CUSZ family of error-bounded lossy compressors, GPU-based lossless encoders, and related tools.
  2. Enhancing the usability of the GPU-accelerated data reduction ecosystem by providing high-level language bindings, command line interfaces, and user interfaces integrated with visualization functionality.
  3. Enabling state-of-the-art GPU-accelerated scientific data compressors on multiple heterogeneous computing platforms, including NVIDIA, AMD, and Intel.

The project will continuously contribute to the education and training of graduate students by enhancing computing-related curricula in heterogeneous scientific computing, data management, and visualization. The award has an effective date of August 1, 2025 and a planned completion date of July 31, 2028.

Generated 7/15/25, 10:03 AM