cuSZ

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cuSZ is an error-bounded lossy compression algorithm for scientific datasets on GPUs. I have contributed to this project by implementing fast Huffman codebook construction as well as fast Huffman decoding algorithms for cuSZ.

High-Performance Computing
Cody Rivera
Cody Rivera
Computer Science Ph.D. Student (he/him)

Cody Rivera is a Ph.D. student at the University of Illinois Urbana-Champaign, where he is doing research in programming languages and formal methods.

Publications

Optimizing Huffman Decoding for Error-Bounded Lossy Compression on GPUs
More and more HPC applications require fast and effective compression techniques to handle large volumes of data in storage and …
Cody Rivera, Sheng Di, Jiannan Tian, Xiaodong Yu, Dingwen Tao, Franck Cappello
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Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs
Error-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. With ever-emerging …
Jiannan Tian, Sheng Di, Xiaodong Yu, Cody Rivera, Kai Zhao, Sian Jin, Yunhe Feng, Xin Liang, Dingwen Tao, Franck Cappello
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Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures
Today’s high-performance computing (HPC) applications are producing vast volumes of data, which are challenging to store and …
Jiannan Tian, Cody Rivera, Sheng Di, Jieyang Chen, Xin Liang, Dingwen Tao, Franck Cappello
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cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data
Error-bounded lossy compression is a state-of-the-art data reduction technique for HPC applications because it not only significantly …
Jiannan Tian, Sheng Di, Kai Zhao, Cody Rivera, Megan Hickman Fulp, Robert Underwood, Sian Jin, Xin Liang, Jon Calhoun, Dingwen Tao, Franck Cappello
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