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News
- Our paper was nominated as the best paper candidate in HPDC2025.
- We have 4 papers accepted by IEEE/ACM SC 2025.
- Our paper was nominated as the best paper candidate in ICS2025.
- Six papers accepted by IPDPS 2025.
- Our paper received the best paper award in IPDPS 2025.
- Paper: Accelerating Collective Communications with Lossy Compression on GPU
- Paper: AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications
- Paper: cuSZp: An Ultra-fast GPU Error-bounded Lossy Compression Framework with Optimized End-to-End Performance
- Paper: ROI preservation
- Paper: wavelet transform based compression
- Paper: TopoSZ: Preserving Topology in Error-Bounded Lossy Compression
- Annoucing the SZ4 Project
- IU News
- FAZ paper receives the best-paper award nomination
- FZ-GPU paper
- QoZ- Quaility-oriented lossy compressor
- David Krasowska
- SZ new version released
- cuSZ new version released
- SZ selected as 2021 R&D100 Awards Winner!!!
- SZ selected as 2021 R&D100 Awards Finalists.
- MMD-SZ released
- vec-SZ released
- cpSZ released
- Roibin-SZ released
- waveSZ released
- QCAT-1.2 released
- cuSZ new version released
- SZauto-1.0.0 released
- cuSZ-0.2.2 released
- SZ3 new version released
- MMD-SZ paper (aka. MDZ) accepted
- QCAT-1.1 released
- cuSZ-0.1.3 released
- SZ-2.1.11 released
- Interp-SZ paper accepted
- kSZ released
- cuSZ-0.1.2 released
- QCAT-1.0 released
- DeepSZ-0.1 released
- cuSZ paper accepted
- SZauto paper accepted
- WaveSZ paper accepted
- Huffman encoding on GPU paper accepted
- cuSZ selected as 3rd Place Winner of ACM Student Research Competition
- DeepSZ paper accepted
Our paper was nominated as the best paper candidate in HPDC2025.
Our paper, ‘IPComp: Interpolation Based Progressive Lossy Compression for Scientific Applications’ was a best paper candidate at International 34th Symposium on High-Performance Parallel and Distributed Computing (ACM HPDC2025) 2025
- Zhuoxun Yang, Sheng Di, Longtao Zhang, Ruoyu Li, Ximiao Li, Jiajun Huang, Jinyang Liu, Franck Cappello, and Kai Zhao, “IPComp: Interpolation Based Progressive Lossy Compression for Scientific Applications”, in International 34th Symposium on High-Performance Parallel and Distributed Computing (ACM HPDC2025), 2025.
We have 4 papers accepted by IEEE/ACM SC 2025.
The team has have 6 papers accepted by The International Conference for High Performance Computing, Networking, Storage, and Analysis 2025.
- Franck Cappello, Robert Underwood, et al, “What to Support: When You are Compressing: The State of Practice, Gaps, and Opportunities for Scientific Data Compression”, IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2025), 2025, .
- Yafan Huang, Sheng Di, Guanpeng Li, Franck Cappello, “GPU Lossy Compression for HPC Can Be Versatile and Ultra-Fast”, IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2025), 2025, .
- Shixun Wu, Jinwen Pan, Jinyang Liu, Jiannan Tian, Ziwei Qiu, Jiajun Huang, Kai Zhao, Xin Liang, Sheng Di, Zizhong Chen, Franck Cappello, “Boosting Scientific Error-Bounded Lossy Compression through Optimized Synergistic Lossy-Lossless Orchestration”, IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2025), 2025, .
- Yafan Huang, Sheng Di, Robert Underwood, Peco Myint, Miaoqi Chu, Guanpeng Li, Nicholas Schwarz, Franck Cappello, “lsCOMP: Efficient Light Source Compression”, IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2025), 2025, .
The papers are to appear
Our paper was nominated as the best paper candidate in ICS2025.
The paper ‘Pushing the Limits of GPU Lossy Compression: A Hierarchical Delta Approach’, in International Conference on Supercomputing (ACM ICS2025), 2025, recieved a best paper nomination.
Boyuan Zhang, Yafan Huang, Sheng Di, Fengguang Song, Guanpeng Li, and Franck Cappello, “Pushing the Limits of GPU Lossy Compression: A Hierarchical Delta Approach”, in International Conference on Supercomputing (ACM ICS2025), 2025, .best paper nomination.
Six papers accepted by IPDPS 2025.
The team contributed to 6 papers that were accepted by The International Parallel and Distributed Processing Symposium
- Pu Jiao, Sheng Di, Mingze Xia, Xuan Wu, Jinyang Liu, Xin Liang, and Franck Cappello, “Improving the Efficiency of Interpolation-Based Scientific Data Compressors with Adaptive Quantization Index Prediction”, in Proceedings of the 39th IEEE International Parallel and Distributed Processing Symposium (IEEE IPDPS2025), 2025, .
- Shihui Song, Robert Underwood, Sheng Di, Yafan Huang, Peng Jiang, Franck Cappello, “A Memory-efficient and Computation-balanced Lossy Compressor on Wafer-Scale Engine”, in Proceedings of the 39th IEEE International Parallel and Distributed Processing Symposium (IEEE IPDPS2025), 2025, .
- Alexandra Poulos, Robert Underwood, Jon C. Calhoun, Sheng Di, and Franck Cappello, “Sensitivity and Impacts on Parallel Compression of Prediction of Lossy Compression Ratios for Scientific Data”, in Proceedings of the 39th IEEE International Parallel and Distributed Processing Symposium (IEEE IPDPS2025), 2025, .
- Alex Fallin, Noushin Azami, Sheng Di, Franck Cappello, Martin Burtscher, “Fast and Effective Lossy Compression on GPUs and CPUs with Guaranteed Error Bounds”, in Proceedings of the 39th IEEE International Parallel and Distributed Processing Symposium (IEEE IPDPS2025), 2025, .
- Grant Wilkins, Sheng Di, Robert Underwood, Jon C. Calhoun, and Franck Cappello, “To Compress or Not To Compress: Energy and Runtime Trade-Offs in Lossy Compressed I/O”, in Proceedings of the 39th IEEE International Parallel and Distributed Processing Symposium (IEEE IPDPS2025), 2025, .
- Xuan Wu, Sheng Di, Congrong Ren, Pu Jiao, Mingze Xia, Cheng Wang, Hanqi Guo, Xin Liang, and Franck Cappello, “Enabling Efficient Error-controlled Lossy Compression for Unstructured Scientific Data”, in Proceedings of the 39th IEEE International Parallel and Distributed Processing Symposium (IEEE IPDPS2025), 2025, .best paper award.
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Our paper received the best paper award in IPDPS 2025.
Xuan Wu, Sheng Di, Congrong Ren, Pu Jiao, Mingze Xia, Cheng Wang, Hanqi Guo, Xin Liang, and Franck Cappello, “Enabling Efficient Error-controlled Lossy Compression for Unstructured Scientific Data”, in Proceedings of the 39th IEEE International Parallel and Distributed Processing Symposium (IEEE IPDPS2025), 2025.
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Paper: Accelerating Collective Communications with Lossy Compression on GPU
Jiajun Huang, Sheng Di, Xiaodong Yu, Zizhong Chen, Franck Cappello, Yanfei Guo, and Rajeev Thakur, “Accelerating Collective Communications with Lossy Compression on GPU”, in IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2023), 2023. (1st place of ACM SRC award – Graduates)
Jiajun Huang, Sheng Di, Xiaodong Yu, Zizhong Chen, Franck Cappello, Yanfei Guo, and Rajeev Thakur, "Accelerating Collective Communications with Lossy Compression on GPU", in IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2023), 2023. (1st place of ACM SRC award -- Graduates)
Paper: AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications
Daoce Wang, Jesus Pulido, Jiannan Tian, Sian Jin, Houjun Tang, Jean Sexton, Sheng Di, Kai Zhao, Bo Fang, Zarija Lukic, Franck Cappello, James Ahrens, Dingwen Tao, “AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications”, IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2023), 2023.
Daoce Wang, Jesus Pulido, Jiannan Tian, Sian Jin, Houjun Tang, Jean Sexton, Sheng Di, Kai Zhao, Bo Fang, Zarija Lukic, Franck Cappello, James Ahrens, Dingwen Tao, "AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications", IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2023), 2023.
Paper: cuSZp: An Ultra-fast GPU Error-bounded Lossy Compression Framework with Optimized End-to-End Performance
Yafan Huang, Sheng Di, Xiaodong Yu, Guanpeng Li, Franck Cappello, “cuSZp: An Ultra-fast GPU Error-bounded Lossy Compression Framework with Optimized End-to-End Performance”, in IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2023), 2023.
Yafan Huang, Sheng Di, Xiaodong Yu, Guanpeng Li, Franck Cappello, "cuSZp: An Ultra-fast GPU Error-bounded Lossy Compression Framework with Optimized End-to-End Performance", in IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2023), 2023.
Paper: ROI preservation
Avinash Kethineedi, Jon C. Calhoun, Robert Underwood, Sheng Di, Franck Cappello, “ROI Preservation in Streaming Lossy Compression”, IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2023), 2023
Avinash Kethineedi, Jon C. Calhoun, Robert Underwood, Sheng Di, Franck Cappello, "ROI Preservation in Streaming Lossy Compression", IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2023), 2023
Paper: wavelet transform based compression
Jiajun Huang, Jinyang Liu, Sheng Di, Yujia Zhai, Shixun Wu, Kai Zhao, Zizhong Chen, Yanfei Guo, Franck Cappello, “Exploring Wavelet Transform Usages for Error-bounded Scientific Data Compression”, International Workshop on Big Data Reduction (IEEE IWBDR23) in conjunction with IEEE International Conference on Big Data (IEEE BigData23), 2023
Jiajun Huang, Jinyang Liu, Sheng Di, Yujia Zhai, Shixun Wu, Kai Zhao, Zizhong Chen, Yanfei Guo, Franck Cappello, "Exploring Wavelet Transform Usages for Error-bounded Scientific Data Compression", International Workshop on Big Data Reduction (IEEE IWBDR23) in conjunction with IEEE International Conference on Big Data (IEEE BigData23), 2023
Paper: TopoSZ: Preserving Topology in Error-Bounded Lossy Compression
Researchers at Ohio State have advanced compression for visualization of topologies
abstract …
mention the figure
Annoucing the SZ4 Project
We’ve created the SZ4 project
We are thrilled to announce the launch of the new generation of the SZ lossy compression framework–SZ4, along with its official website! SZ4 is highly modularized, flexible, and easy to customize for specialized use cases, catering to a broad spectrum of scientific applications.
IU News
IU part of $3.2 million grant for cyberinfrastructure research
Indiana University will receive $580,000 of a $3.2 million grant for its collaboration in a National Science Foundation Cyberinfrastructure for Science Innovation project. Dingwen Tao, associate professor of Intelligent Systems Engineering for the Luddy School of Informatics, Computing, and Engineering, is IU’s primary investigator.
The University of Chicago, Ohio State University and the University of Alabama also are collaborating on the project, which aims to develop sustainable computer software to support science research and discovery.
FAZ paper receives the best-paper award nomination
Our [FAZ paper] receives the best-paper award nomination in ICS2023.
QoZ- Quaility-oriented lossy compressor
QoZ: Quaility-oriented lossy compressor is released.
Github link
David Krasowska
David Krasowska won the 1st Place Winnder of the ACM Student Research Competition (Graduate) at SC22.
SZ selected as 2021 R&D100 Awards Winner!!!
SZ has been selected as a winner of 2021 R&D100 Awards!
Link to the R&D website
SZ selected as 2021 R&D100 Awards Finalists.
SZ has been selected as one of 2021 R&D100 Awards Finalists!
Link to the R&D website
Huffman encoding on GPU paper accepted
Our Huffman encoding on GPU paper has been accepted by IPDPS’21.
Link to the paper
cuSZ selected as 3rd Place Winner of ACM Student Research Competition
cuSZ has been selected as the 3rd Place Winner of the ACM Student Research Competition (Graduate) at SC21!