Publications

This page presents the publications about SZ from the core group as well as publications presenting other extensions, optimizations and implementations of SZ. If we missed publications, please contact us.
2024

[FGCS'24] Franck Cappello, Mario Acosta, Emmanuel Agullo, Hartwig Anzt, Jon Calhoun, Sheng Di, Luc Giraud, Thomas Grutzmacher, Sian Jin, Kentaro Sano, Kento Sato, Amarjit Singh, Dingwen Tao, Jiannan Tian, Tomohiro Ueno, Robert Underwood, Federic Vivien, Xavier Yepes, Kazutomo Yoshii, Boyuan Zhang "Multifacets of lossy compression for scientific data in the Joint-Laboratory of Extreme Scale Computing", International Journal of Future Generation Computer Systems (FGCS), 2024.
[DRBSD'24] Tripti Agarwal, Sheng Di, Jiajun Huang, Yafan Huang, Ganesh Gopalakrishnan, Robert Underwood, Kai Zhao, Xin Liang, Guanpeng Li, and Franck Cappello, "SZOps: Scalar Operations for Error-bounded Lossy Compressor for Scientific Data", IEEE/ACM The 10th International Workshop on Data Analysis and Reduction for Big Scientific Data, in conjunction with The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2024),2024.
[DRBSD'24] Thomas Grutzmacher, Robert Underwood, Sheng Di, Franck Cappello, and Hartwig Anzt, "FRSZ2 for In-Register Block Compression Inside GMRES on GPUs", IEEE/ACM The 10th International Workshop on Data Analysis and Reduction for Big Scientific Data, in the conjunction with The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2024), 2024, best paper award.
[SC'24] Yafan Huang, Sheng Di, Guanpeng Li, Franck Cappello, "cuSZp2: A GPU Lossy Compressor with Extreme Throughput and Optimized Compression Ratio", IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2024), 2024, best student paper finalist.
[SC'24] Jiajun Huang, Sheng Di, Xiaodong Yu, Zhaiyu Jia, Jinyang Liu, Zizhe Jian, Xin Liang, Kai Zhao, Xiaoyi Lu, Zizhong Chen, Franck Cappello, Yanfei Guo and Rajeev Thakur, "hZCC: Accelerating Collective Communication with Co-designed Operation-supported Compression", IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2024), 2024.
[SC'24] Jinyang Liu, Jiannan Tian, Shixun Wu, Sheng Di, Boyuan Zhang, Robert Underwood, Yafan Huang, Jiajun Huang, Kai ZHao, Guanpeng Li, Dingwen Tao, Zizhong Chen, and Franck Cappello, "High-ratio Scientific Lossy Compression on GPUs with Optimized Multi-level Interpolation", IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2024), 2024.
[ICPP'24] Tri Nguyen, Md Hasanur Rahman, Sheng Di and Michela Becchi, "CAROL: Significantly Improving Fixed-Ratio Compression Framework for Resource-limited Applications", in 53rd International Conference on Parallel Processing (ACM ICPP2024), 2024.
[ICS'24] Jiajun Huang, Sheng Di, Xiaodong Yu, Zhaiyu Jia, Jinyang Liu, Yafan Huang, Ken Raffenetti, Hui Zhou, Kai Zhao, Xiaoyi Lu, Zizhong Chen, Franck Cappello, Yanfei Guo, Rajeev Thakur, "gZCCL: Compression-Accelerated Collective Communication Framework for GPU Clusters", 38th ACM International Conference on Supercomputing (ACM ICS2024), 2024.
[ICDCS'24] Grant Wilkins, Sheng Di, Jon Calhoun, Zilinghan Li, Kibaek Kim, Robert Underwood, Richard Mortier and Franck Cappello, "FedSZ: Leveraging Floating-Point Lossy Compression for Federated Learning Communications", 44th IEEE International Conference on Distributed Computing Systems (IEEE ICDCS2024).
[HPDC'24] Milan Shah, Xiaodong Yu, Sheng Di, Michela Becchi, Franck Cappello,"A Portable, Fast, DCT-based Compressor for AI Accelerators", in International Symposium on High-Performance Parallel and Distributed Computing (ACM HPDC2024), 2024.
[HPDC'24] Shihui Song, Yafan Huang, Peng Jiang, Xiaodong Yu, Weijian Zheng, Sheng Di, Qinglei Cao, Yunhe Feng, Zhen Xie, Franck Cappello, "CereSZ: Enabling and Scaling Error-bounded Lossy Compression on Cerebras CS-2", in International Symposium on High-Performance Parallel and Distributed Computing (ACM HPDC2024), 2024.
[MSST'24] Md Hasanur Rahman, Sheng Di, Guanpeng Li, Franck Cappello, "A Generic and Efficient Framework for Estimating Lossy Compressibility of Scientific Data", in Proceedings of the 35th International Conference on Massive Storage Systems and Technology (IEEE MSST2024), 2024.
[PPoPP'24 poster] Jiajun Huang, Sheng Di, Xiaodong Yu, Yujia Zhai, Zhaorui Zhang, Jinyang Liu, Xiaoyi Lu, Ken Raffenetti, Hui Zhou, Kai Zhao, Zizhong Chen, Franck Cappello, Yanfei Guo, Rajeev Thakur, "Optimizing Collective Communications with Error-bounded Lossy Compression for GPU Clusters", Principles and Practice of Parallel Programming (PPoPP2024), 2024, poster.
[IPDPS'24] Zizhe Jian, Sheng Di, Jinyang Liu, Kai Zhao, Xin Liang, Haiying Xu, Robert Underwood, Jiajun Huang, Shixun Wu, Zizhong Chen, Franck Cappello, "CliZ: Optimizing Lossy Compression for Climate Datasets with Adaptive Fine-tuned Data Prediction", in Proceedings of the 38th IEEE International Parallel and Distributed Processing Symposium (IEEE IPDPS2024), 2024
[IPDPS'24] Jiajun Huang, Sheng Di, Xiaodong Yu, Yujia Zhai, Zhaorui Zhang, Jinyang Liu, Xiaoyi Lu, Ken Raffenetti, Hui Zhou, Kai Zhao, Zizhong Chen, Franck Cappello, Yanfei Guo, Rajeev Thakur, "An Optimized Error-controlled MPI Collective Framework Integrated with Lossy Compression", in Proceedings of the 38th IEEE International Parallel and Distributed Processing Symposium (IEEE IPDPS2024), 2024.
[ICDE'24] Mingze Xia, Sheng Di, Franck Cappello, Pu Jiao, Kai Zhao, Jinyang Liu, Xuan Wu, Xin Liang, and Hanqi Guo, "Preserving Topological Feature with Sign-of-Determinant Predicates in Lossy Compression: A Case Study of Vector Field Critical Points", Proceedings of the 40th IEEE International Conference on Data Engineering (IEEE ICDE2024), Utrecht, Netherlands, May 13 - 16, 2024.
[SIGMOD'24] Jinyang Liu, Sheng Di, Kai Zhao, Xin Liang, Sian Jin, Zizhe Jian, Jiajun Huang, Shixun Wu, Zizhong Chen, Franck Cappello, "High-performance Effective Scientific Error-bounded Lossy Compression with Auto-tuned Multi-component Interpolation", in ACM Special Interest Group on Management of Data (SIGMOD2024), 2024.
[Eurosys'24] Sian Jin, Sheng Di, Frederic Vivien, Dance Wang, Yves Robert, Dingwen Tao, Franck Cappello, "Concealing Compression-accelerated I/O for HPC Applications through In Situ Task Scheduling", in Eurosys2024, 2024.

2023

[HiPC'23] Arham Khan, Sheng Di, Kai Zhao, Jinyang Liu, Kyle Chaid, Ian Foster, Franck Cappello, "SECRE: Surrogate-based Error-controlled Lossy Compression Ratio Estimation Framework", in 30th edition of the IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC2023), 2023.

[HiPC'23] Pu Jiao, Sheng Di, Jinyang Liu, Xin Liang, Franck Cappello, "Characterization and Detection of Artifacts for Error-controlled Lossy Compressors", in 30th edition of the IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC2023), 2023.

[SRN'23] Robert Underwood, Chun Hong Yoon, Ali M. Gok, Sheng Di, Franck Cappello, "ROIBIN-SZ: Fast and Science-Preserving Compression for Serial Crystallography", Journal of Synchrotron Radiation News (SRN), 2023.

[IJHPCA'23] Robert Underwood, Julie Bessac, David Krasowska, Jon C Calhoun, Sheng Di, Franck Cappello, "Black-box statistical prediction of lossy compression ratios for scientific data", International Journal of High Performance Computing Applications (IJHPCA2023), 2023, Volume 37, Issue 3-4.

[CLUSTER'23] Arkaprabha Ganguli, Robert Underwood, Julie Bessac, David Krasowska, Jon Calhoun, Sheng Di, Franck Cappello, "A Lightweight, Effective Compressibility Estimation Method for Error-bounded Lossy Compression", in IEEE International Conference on Cluster Computing(IEEE CLUSTER2023), 2023.

[CLUSTER'23 best poster finalist] Arham Khan, Sheng Di, Kai Zhao, Jinyang Liu, Kyle Chard, Ian Foster, Franck Cappello, "An Efficient and Accurate Compression Ratio Estimation Model for SZx", in IEEE International Conference on Cluster Computing(IEEE CLUSTER2023), 2023, [poster].

[SC'23] 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.

[SC'23] 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.

[Bigdata'23] Jinyang Liu, Sheng Di, Sian Jin, Kai Zhao, Xin Liang, Zizhong Chen, Franck Cappello, "Scientific Error-bounded Lossy Compression with Super-resolution Neural Networks", in conjunction with IEEE International Conference on Big Data (IEEE BigData23), 2023.

[IWBDR'23] 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.

[SC'23 poster] 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. [poster].

[SC'23 poster] 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. [poster].

[DRBSD'24] Robert R. Underwood, Sheng Di, Sian Jin, Md Hasanur Rahman, Arham Khan, Franck Cappello, "LibPressio-Predict: Flexible and Fast Infrastructure for Inferring Compression Performance", in Proceedings of the 7th International Workshop on Data Reduction for Big Scientific Data (DRBSD-9), in conjunction with IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2023), 2023.

[ICS'23] Boyuan Zhang, Sheng Di, Xiaodong Yu, Martin Swany, Dingwen Tao, Franck Cappello, "GPULZ: Optimizing LZSS Lossless Compression for Multi-byte Data on Modern GPUs", in International Conference on Supercomputing (ACM ICS2023), 2023.

[ICS'23] Milan Shah, Xiaodong Yu, Sheng Di, Michela Becchi, and Franck Cappello, "Lightweight Huffman Coding for Efficient GPU Compression", in International Conference on Supercomputing (ACM ICS2023), 2023.

[ICS'23 best paper finalist] Jinyang Liu, Sheng Di, Kai Zhao, Xin Liang, Zizhong Chen, Franck Cappello, "FAZ: A flexible auto-tuned modular error-bounded compression framework for scientific data", in International Conference on Supercomputing (ACM ICS2023), 2023.

[ICDCS'23] Yuanjian Liu, Sheng Di, Kyle Chard, Ian Foster, Franck Cappello, "Optimizing Scientific Data Transfer on Globus with Error-bounded Lossy Compression", in 43rd IEEE International Conference on Distributed Computing Systems (IEEE ICDCS2023), 2023.

[HPDC'23] Boyuan Zhang, Jiannan Tian, Sheng Di, Xiaodong Yu, Yunhe Feng, Yunhe Feng, Xin Liang, Dingwen Tao, Franck Cappello, "FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs," in 32nd International Symposium on High-Performance Parallel and Distributed Computing (ACM HPDC2023), 2023.

[CCGrid'23] Yafan Huang, Kai Zhao, Sheng Di, Guanpeng Li, Maxim Dmitriev, Thierry-Laurent D. Tonellot and Franck Cappello, "Towards Improving Reverse Time Migration Performance by High-speed Lossy Compression," in 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (ACM CCGrid2023), 2023.

[IPDPS'23] Milan Shah, Xiaodong Yu, Sheng Di, Danylo Lykov, Yuri Alexeev, Michela Becchi, Franck Cappello, "GPU-Accelerated Error-Bounded Compression Framework for Quantum Circuit Simulations", in Proceedings of the 37th IEEE International Parallel and Distributed Processing Symposium (IPDPS2023), St. Petersburg, Florida, USA, May 15-June 19, 2023.

[VLDB'23] Pu Jiao, Sheng Di, Hanqi Guo, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, Franck Cappello, "Toward Quantity-of-Interest Preserving Lossy Compression for Scientific Data", in 49th International Conference on Very Large Database (VLDB 2023), 2023, Canada.

[ICDE'23] Md Hasanur Rahman, Sheng Di, Kai Zhao, Robert Underwood, Guanpeng Li, Franck Cappello, "A Feature-Driven Fixed-Ratio Lossy Compression Framework for Real-World Scientific Datasets", in Proceeding of the 39th IEEE International Conference on Data Engineering (ICDE2023), 2023.

2022

[TVCG'22] Xin Liang, Sheng Di, Franck Cappello, Mukund Raj, Chunhui Liu, Kenji Ono, Zizhong Chen, Tom Peterka, and Hanqi Guo, "Toward Feature-Preserving Vector Field Compression", IEEE Transactions on Visualization and Computer Graphics (IEEE TVCG), 2022.
[DRBSD'22] Zhaoyuan Su, Sheng Di, Ali Murat Gok, Yue Cheng, Franck Cappello, "Understanding Impact of Lossy Compression on Derivative-related Metrics in Scientific Datasets", in Proceedings of the 7th International Workshop on Data Reduction for Big Scientific Data (DRBSD-8), in conjunction with IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2022), 2022.
[DRBSD'22 best paper] Robert Underwood, Julie Bessac, Sheng Di, Franck Cappello, "Understanding the Effects of Modern Compressors on the Community Earth Science Model", in Proceedings of the 7th International Workshop on Data Reduction for Big Scientific Data (DRBSD-8), in conjunction with IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2022), 2022.
[EAGE'22] Maxim Dmitriev, Thierry Tonellot, Hussain Salim , Sheng Di, "Error-bounded lossy compression in Reverse Time Migration", Sixth EAGE High Performance Computing Workshop (EAGE22), 2022.
[MASCOTS'22] Griffin Dube, Jiannan Tian, Sheng Di, Dingwen Tao, Jon C. Calhoun, Franck Cappello, "Efficient Error-Bounded Lossy Compression for CPU Architectures", 30th International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (IEEE MASCOTS 2022), Nice, France, 2022.
[TBD'22] Xin Liang, Kai Zhao, Sheng Di, Sihuan Li, Robert Underwood, Ali M. Gok, Jiannan Tian, Junjing Deng, Jon C. Calhoun, Dingwen Tao, Zizhong Chen, Franck Cappello, "SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors", IEEE Transactions on Big Data (IEEE TBD), 2022.
[TPDS'22] Yuanjian Liu, Sheng Di, Kai Zhao, Sian Jin, Cheng Wang, Kyle Chard, Dingwen Tao, Ian Foster, Franck Cappello, "Optimizing Error-Bounded Lossy Compression for Scientific Data with Diverse Constraints", in IEEE Transactions on Distributed and Computer Systems (TPDS), 2022.
[CLUSTER'22] Ruiwen Shan, Sheng Di, Jon C. Calhoun, Franck Cappello, "Exploring Light-weight Cryptography for Efficient and Secure Lossy Data Compression", in IEEE CLUSTER2022, 2022.
[SC'22] Sian Jin, Dingwen Tao, Houjun Tang, Sheng Di, Suren Byna, Zarija Lukic, Franck Cappello, "Accelerating Parallel Write via Deeply Integrating Predictive Lossy Compression with HDF5", IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2022), 2022.
[SC'22] Jinyang Liu, Sheng Di, Kai Zhao, Xin Liang, Zizhong Chen, Franck Cappello, "Dynamic Quality Metric Oriented Error Bounded Lossy Compression for Scientific Datasets", IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2022), 2022.
[SC'22-poster-2nd place of ACM SRC award] Milan Shah, Xiaodong Yu, Sheng Di, Franck Cappello, Michela Becchi, "Compressing Quantum Circuit Simulation Tensor Data", IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2022), 2022.
[SC'22-poster-1st place of ACM SRC award] David Krasowska, Robert Underwood, Julie Bessac, Jon Calhoun, Sheng Di, Franck Cappello, "Statistical Prediction of Lossy Compression Ratios for 3D Scientific Data", IEEE/ACM The International Conference for High Performance computing, Networking, Storage and Analysis (IEEE/ACM SC2022), 2022.
[VLDB’22] Sian Jin, Chengming Zhang, Jiannan Tian, Yunhe Feng, Hui Guan, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao. “COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression.” The 48th International Conference on Very Large Data Bases (VLDB), Australia, September 5-9, 2022.
[ICDE’22] Sian Jin, Sheng Di, Suren Byna, Dingwen Tao, Franck Cappello. “Significantly Improving Prediction-Based Lossy Compression via Ratio-Quality Modelin.” 2022 IEEE International Conference on Data Engineering (ICDE), 2022.
[ICDE’22] Kai Zhao, Sheng Di, Danny Perez, Xin Liang, Zizhong Chen, Franck Cappello. “MDZ: An Efficient Error-bounded Lossy Compressor for Molecular Dynamics Simulations of Materials.” 2022 IEEE International Conference on Data Engineering (ICDE), 2022.
[IPDPS’22] Cody Rivera, Sheng Di, Xiaoding Yu, Jiannan Tian, Dingwen Tao, and Franck Cappello. “Optimizing Huffman Decoding for Error-Bounded Lossy Compression on GPUs.” 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2022.
[ICS’22] Chengming Zhang, Sian Jin, Tong Geng, Jiannan Tian, Ang Li, Dingwen Tao. “CEAZ: Accelerating Parallel I/O via Hardware-Algorithm Co-Designed Adaptive Lossy Compression.” The 36th ACM International Conference on Supercomputing (ICS), 2022.
[HPDC’22] Xiaodong Yu, Sheng Di, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, Franck Cappello. “Ultra-fast Error-bounded Lossy Compression for Scientific Dataset.” The 31st ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC), 2022.
[HPDC’22] Daoce Wang, Jesus Pulido, Pascal Grosset, Jiannan Tian, James Ahrens, Dingwen Tao. “Optimizing Error-Bounded Lossy Compression for Three Dimensional Adaptive Mesh Refinement Simulations.” The 31st ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC), 2022.
[SC’22] Sian Jin, Dingwen Tao, Houjun Tang, Sheng Di, Suren Byna, Zarija Lukic, and Franck Cappello. “Accelerating Parallel Write via Deeply Integrating Predictive Lossy Compression with HDF5.” The International Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2022.
[TPDS] Robert Underwood, Jon C. Calhoun, Sheng Di, Amy Apon, Franck Cappello. “OptZConfig: Efficient Parallel Optimization of Lossy Compression Configuration.” IEEE Transactions on Distributed and Computer Systems (TPDS), 2022.
[TPDS] Yuanjian Liu, Sheng Di, Kai Zhao, Sian Jin, Cheng Wang, Kyle Chard, Dingwen Tao, Ian Foster, and Franck Cappello. “Optimizing Error-Bounded Lossy Compression for Scientific Data with Diverse Constraints.” IEEE Transactions on Parallel and Distributed Systems (TPDS), 2022.

2021

[IPDPS’21] Jiannan Tian, Cody Rivera, Sheng Di, Jieyang Chen, Xin Liang, Dingwen Tao, and Franck Cappello. “Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures.” 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 881-891, 2021.
[ICDE’21] Kai Zhao, Sheng Di, Maxim Dmitriev, Thierry-Laurent D. Tonellot, Zizhong Chen, and Franck Cappello. “Optimizing Error-Bounded Lossy Compression for Scientiﬁc Data by Dynamic Spline Interpolation.” 2021 IEEE International Conference on Data Engineering (ICDE), Chania, Crete, Greece, pp. 1643-1654, 2021.
[PPoPP’21] Sian Jin, Guanpeng Li, Shuaiwen Leon Song, Dingwen Tao. “A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy Compression.” The 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), pp. 485-487, 2021.
[HPDC’21] Sian Jin, Jesus Pulido, Pascal Grosset, Jiannan Tian, Dingwen Tao, and James Ahrens. “Adaptive Configuration of In Situ Lossy Compression for Cosmology Simulations via Fine-Grained Rate-Quality Modeling.” The 30th ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC), pp. 45-56. 2021.
[HPDC’21] Dakota Fulp, Alexandra Poulos, Robert Underwood, and Jon C. Calhoun. “ARC: An Automated Approach to Resiliency for Lossy Compressed Data via Error Correcting Codes.” The 30th International Symposium on High-Performance Parallel and Distributed Computing (HPDC), pp. 57–68. 2021.
[SC’21] Sihuan Li, Sheng Di, Kai Zhao, Xin Liang, Zizhong Chen, and Franck Cappello. “Resilient Error-bounded Lossy compressor for Data Transfer.” The 33rd ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC), St. Louis, Missouri, USA, pp. 1-14, 2021.
[CLUSTER’21] Jiannan Tian, Sheng Di, Xiaodong Yu, Cody Rivera, Kai Zhao, Sian Jin, Yunhe Feng, Xin Liang, Dingwen Tao, Franck Cappello. “Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs.” 2021 IEEE International Conference on Cluster Computing (CLUSTER), pp. 283-203, 2021.
[CLUSTER’21] Jinyang Liu, Sheng Di, Kai Zhao, Sian Jin, Dingwen Tao, Xin Liang, Zizhong Chen, Franck Cappello. “Exploring Autoencoder-Based Error-Bounded Compression for Scientific Data.” In 2021 IEEE International Conference on Cluster Computing (CLUSTER), pp. 294-306, 2021.
[CLUSTER’21] Xiaodong Yu, Sheng Di, Ali Murat Gok, Dingwen Tao, Franck Cappello. “cuZ-Checker: A GPU-Based Ultra-Fast Assessment System for Lossy Compressions.” 2021 IEEE International Conference on Cluster Computing (Cluster), pp. 307-319, 2021.
[HPEC’21] Ruiwen Shan, Sheng Di, Jon C. Calhoun, Franck Cappello. “Towards Combining Error-bounded Lossy Compression and Cryptography for Scientific Data.” in 2021 IEEE High Performance Extreme Computing (HPEC), pp. 1-7, 2021.
[HiPC’21] Yuanjian Liu, Sheng Di, Kai Zhao, Sian Jin, Cheng Wang, Kyle Chard, Ian Foster, Dingwen Tao, Frank Cappello. “Optimizing Multi-Range based Error-Bounded Lossy Compression for Scientific Datasets.” 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics (HiPC), 2021.
[DRBSD-7] David Krasowska, Julie Bessac, Robert Underwood, Jon C. Calhone, Sheng Di, Franck Cappello. “Exploring Lossy Compressibility through Statistical Correlations of Scientific Datasets.” The 7th International Workshop on Data Reduction for Big Scientific Data (DRBSD-7), in conjunction with IEEE/ACM 29th The International Conference for High Performance computing, Networking, Storage and Analysis (SC), 2021.
[DRBSD-7] Yuanjian Liu, Sheng Di, Kai Zhao, Sian Jin, Cheng Wang, Kyle Chard, Dingwen Tao, Ian Foster, Franck Cappello. “Understanding Effectiveness of Multi-error-bounded Lossy Compression for Preserving Ranges of Interest in Scientific Analysis.” The 7th International Workshop on Data Reduction for Big Scientific Data (DRBSD-7), in conjunction with IEEE/ACM 29th The International Conference for High Performance computing, Networking, Storage and Analysis (SC), 2021.
[DRBSD-7] Robert Underwood, Victoriana Malvoso, Jon C. Calhone, Sheng Di, Franck Cappello. “Productive and Performant Generic Lossy Data Compression with LibPressio.” The 7th International Workshop on Data Reduction for Big Scientific Data (DRBSD-7), in conjunction with IEEE/ACM 29th The International Conference for High Performance computing, Networking, Storage and Analysis (SC), 2021.

2020

[PPoPP’20] Jiannan Tian, Sheng Di, Chengming Zhang, Xin Liang, Sian Jin, Dazhao Cheng, Dingwen Tao, and Franck Cappello. “waveSZ: a hardware-algorithm co-design of efficient lossy compression for scientific data.” The 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, pp. 74-88. 2020. https://github.com/szcompressor/SZ_HLS
[HPDC’20] Kai Zhao, Sheng Di, Xin Liang, Sihuan Li, Dingwen Tao, Zizhong Chen, and Franck Cappello. “Significantly improving lossy compression for hpc datasets with second-order prediction and parameter optimization.” The 29th International Symposium on High-Performance Parallel and Distributed Computing (HPDC), pp. 89-100. 2020. https://github.com/szcompressor/SZauto
[PacificVis’20] Xin Liang, Hanqi Guo, Sheng Di, Franck Cappello, Mukund Raj, Chunhui Liu, Kenji Ono, Zizhong Chen, and Tom Peterka. “Toward Feature-Preserving 2D and 3D Vector Field Compression.” The 13th IEEE Pacific Visualization Symposium (PacificVis), pp. 81-90. 2020. https://github.com/szcompressor/cpSZ
[IPDPS’20] Robert Underwood, Sheng Di, Jon Calhoun, and Franck Cappello. “FRaZ: A Generic High-Fidelity Fixed-Ratio Lossy Compression Framework for Scientific Floating-point Data.” 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 567-577. IEEE, 2020.
[IPDPS’20] Sian Jin, Pascal Grosset, Christopher M Biwer, Jesus Pulido, Jiannan Tian, Dingwen Tao, and James Ahrens. “Understanding GPU-Based Lossy Compression for Extreme-Scale Cosmological Simulations.” 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 105-115. IEEE, 2020.
[PACT’20] Jiannan Tian, Sheng Di, Kai Zhao, Cody Rivera, Megan Hickman, Robert Underwood, Sian Jin, Xin Liang, Jon Calhoun, Dingwen Tao, and Franck Cappello. “cuSZ: An Efficient GPU Based Error-Bounded Lossy Compression Framework for Scientific Data.” The 29th International Conference on Parallel Architectures and Compilation Techniques (PACT), 2020. https://github.com/szcompressor/cuSZ
[SMC’20] Franck Cappello, Sheng Di, Ali M. Gok. “Fulfilling the Promises of Lossy Compression forScientific Applications.” Smoky Mountain Computational Science and Engineering Conference (SMC), 2020.
[ICPP’20] Zhenbo Hu, Xiangyu Zou, Wen Xia, Sian Jin, Dingwen Tao, Yang Liu, Weizhe Zhang, and Zheng Zhang. “Delta-DNN: Efficiently Compressing Deep Neural Networks via Exploiting Floats Similarity.” The 49th International Conference on Parallel Processing (ICPP), Article 40, 1–12. ACM, 2020.
[CLUSTER’20] Sihuan Li, Sheng Di, Kai Zhao, Xin Liang, Zizhong Chen, and Franck Cappello. “Towards End-to-end SDC Detection for HPC Applications Equipped with Lossy Compression.” 2020 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 2019.
[TPDS] Xiangyu Zou, Tao Lu, Wen Xia, Xuan Wang, Weizhe Zhang, Haijun Zhang, Sheng Di, Dingwen Tao, and Franck Cappello. “Performance Optimization for Relative-Error-Bounded Lossy Compression on Scientific Data.” IEEE Transactions on Parallel and Distributed Systems 31, no. 7 (2020): 1665-1680.
[BioRxiv] Chandak, Shubham, Kedar Tatwawadi, Srivatsan Sridhar, and Tsachy Weissman. “Impact of lossy compression of nanopore raw signal data on basecall and consensus accuracy.” BioRxiv (2020).
[Neurocomputing] Azar, Joseph, Abdallah Makhoul, Raphaël Couturier, and Jacques Demerjian. “Robust IoT Time Series Classification with Data Compression and Deep Learning.” Neurocomputing (2020).
[TACO] Eldstål-Ahrens, Albin, and Ioannis Sourdis. “MemSZ: Squeezing Memory Traffic with Lossy Compression.” ACM Transactions on Architecture and Code Optimization (TACO) 17, no. 4 (2020): 1-25.

2019

[HPDC’19] Sian Jin, Sheng Di, Xin Liang, Jiannan Tian, Dingwen Tao, and Franck Cappello. “Deepsz: A novel framework to compress deep neural networks by using error-bounded lossy compression.” The 28th International Symposium on High-Performance Parallel and Distributed Computing (HPDC), pp. 159-170. 2019. https://github.com/szcompressor/deepsz
[MSST’19] Xiangyu Zou, Tao Lu, Wen Xia, Xuan Wang, Weizhe Zhang, Sheng Di, Dingwen Tao, and Franck Cappello. “Accelerating relative-error bounded lossy compression for hpc datasets with precomputation-based mechanisms.” The 35th Symposium on Mass Storage Systems and Technologies (MSST), pp. 65-78. IEEE, 2019.
[FCCM’19] Xiong, Qingqing, Rushi Patel, Chen Yang, Tong Geng, Anthony Skjellum, and Martin C. Herbordt. “Ghostsz: A transparent fpga-accelerated lossy compression framework.” The 27th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), pp. 258-266. IEEE, 2019.
[CLUSTER’19] Xin Liang, Sheng Di, Dingwen Tao, Sihuan Li, Bogdan Nicolae, Zizhong Chen, and Franck Cappello. “Improving performance of data dumping with lossy compression for scientific simulation.” In 2019 IEEE International Conference on Cluster Computing (CLUSTER), pp. 1-11. IEEE, 2019.
[CLUSTER’19] Pavlo Triantafyllides, Tasmia Reza, and Jon C. Calhoun. “Analyzing the Impact of Lossy Compressor Variability on Checkpointing Scientific Simulations.” 2019 IEEE International Conference on Cluster Computing (CLUSTER), pp. 1-5. IEEE, 2019.
[SC’19] Xin Liang, Sheng Di, Sihuan Li, Dingwen Tao, Bogdan Nicolae, Zizhong Chen, and Franck Cappello. “Significantly improving lossy compression quality based on an optimized hybrid prediction model.” The International Conference for High Performance Computing, Networking, Storage and Analysis (SC), pp. 1-26. 2019.
[SC’19] Xin-Chuan Wu, Sheng Di, Emma Maitreyee Dasgupta, Franck Cappello, Hal Finkel, Yuri Alexeev, and Frederic T. Chong. “Full-state quantum circuit simulation by using data compression.” The International Conference for High Performance Computing, Networking, Storage and Analysis (SC), pp. 1-24. 2019.
[HPCC’19] Zou, Xiangyu, Tao Lu, Sheng Di, Dingwen Tao, Wen Xia, Xuan Wang, Weizhe Zhang, and Qing Liao. “Accelerating Lossy Compression on HPC datasets via Partitioning Computation for Parallel Processing.” 2019 IEEE 21st International Conference on High Performance Computing and Communications(HPCC), pp. 1791-1797. IEEE, 2019.
[TPDS] Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, and Franck Cappello. “Optimizing lossy compression rate-distortion from automatic online selection between sz and zfp.” IEEE Transactions on Parallel and Distributed Systems 30, no. 8 (2019): 1857-1871.
[IJHPCA] Franck Cappello, Sheng Di, Sihuan Li, Xin Liang, Ali Murat Gok, Dingwen Tao, Chun Hong Yoon, Xin-Chuan Wu, Yuri Alexeev, and Frederic T. Chong. “Use cases of lossy compression for floating-point data in scientific data sets.” The International Journal of High Performance Computing Applications 33, no. 6 (2019): 1201-1220.
[DRBSD-5] Tasmia Reza, Kristopher Keipert, Sheng Di, Xin Liang, Jon C. Calhoun, Franck Cappello. “Analyzing the Performance and Accuracy of LossyCheckpointing on Sub-iteration of NWChem.” The 5th International Workshop on Data Reduction for Big Scientific Data (DRBSD-5), in conjunction with the International Conference for High Performance computing, Networking, Storage and Analysis (SC).

2018

[HPDC’18] Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, and Franck Cappello. “Improving performance of iterative methods by lossy checkponting.” The 27th International Symposium on High-Performance Parallel and Distributed Computing (HPDC), pp. 52-65. 2018.
[BigData’18] Xin Liang, Sheng Di, Dingwen Tao, Sihuan Li, Shaomeng Li, Hanqi Guo, Zizhong Chen, and Franck Cappello. “Error-controlled lossy compression optimized for high compression ratios of scientific datasets.” 2018 IEEE International Conference on Big Data (BigData), pp. 438-447. IEEE, 2018.
[BigData’18] Sihuan Li, Sheng Di, Xin Liang, Zizhong Chen, Franck Cappello. “Optimizing Lossy Compression with Adjacent Snapshots for N-body Simulation.” 2018 IEEE International Conference on Big Data (BigData), pp. 428-437. IEEE, 2018.
[CLUSTER’18] Ali Murat Gok, Sheng Di, Yuri Alexeev, Dingwen Tao, Vladimir Mironov, Xin Liang, and Franck Cappello. “Pastri: Error-bounded lossy compression for two-electron integrals in quantum chemistry.” 2018 IEEE international conference on cluster computing (CLUSTER), pp. 1-11. IEEE, 2018. Best Paper Award
[CLUSTER’18] Xin Liang, Sheng Di, Dingwen Tao, Zizhong Chen, and Franck Cappello. “An efficient transformation scheme for lossy data compression with point-wise relative error bound.” 2018 IEEE International Conference on Cluster Computing (CLUSTER), pp. 179-189. IEEE, 2018. Best Area Paper Award
[CLUSTER’18] Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, and Franck Cappello. “Fixed-psnr lossy compression for scientific data.” 2018 IEEE International Conference on Cluster Computing (CLUSTER), pp. 314-318. IEEE, 2018.
[PMES’18] Xin-Chuan Wu, Sheng Di, Franck Cappello, Hal Finkel, Yuri Alexeev, Frederic T. Chong. “Memory-Efficient Quantum Circuit Simulation by Using Lossy Data Compression.” The 3rd International Workshop on Post-Moore Era Supercomputing (PMES), in conjunction with the International Conference for High Performance computing, Networking, Storage and Analysis (SC).
[TPDS] Sheng Di, Dingwen Tao, Xin Liang, and Franck Cappello. “Efficient lossy compression for scientific data based on pointwise relative error bound.” IEEE Transactions on Parallel and Distributed Systems 30, no. 2 (2018): 331-345.
[DRBSD-4] Xin Liang, Sheng Di, Dingwen Tao, Sihuan Li, Zizhong Chen, Franck Cappello. “Improving In-situ Lossy Compression with Spatio-Temporal Decimation based on SZ Model.” The 4th International Workshop on Data Reduction for Big Scientific Data (DRBSD-4), in conjunction with the International Conference for High Performance computing, Networking, Storage and Analysis (SC).
[DRBSD-4] Xin-Chuan Wu, Sheng Di, Franck Cappello, Hal Finkel, Yuri Alexeev, Frederic T. Chong. “Amplitude-Aware Lossy Compression for Quantum Circuit Simulation.” The 4th International Workshop on Data Reduction for Big Scientific Data (DRBSD-4), in conjunction with the International Conference for High Performance computing, Networking, Storage and Analysis (SC).

2017

[IPDPS’17] Dingwen Tao, Sheng Di, Zizhong Chen, and Franck Cappello. “Significantly improving lossy compression for scientific data sets based on multidimensional prediction and error-controlled quantization.” 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 1129-1139. IEEE, 2017.
[BigData’17] Dingwen Tao, Sheng Di, Zizhong Chen, and Franck Cappello. “In-Depth Exploration of Single-Snapshot Lossy Compression Techniques for N-Body Simulations.” 2017 IEEE International Conference on Big Data (BigData), Boston, MA, USA, December 11 - 14, 2017.
[DRBSD-1] Dingwen Tao, Sheng Di, Zizhong Chen, and Franck Capello. “Exploration of Pattern-Matching Techniques for Lossy Compression on Cosmology Simulation Data Sets.” The 1st International Workshop on Data Reduction for Big Scientific Data (DRBSD-11) in Conjunction with ISC’17, Frankfurt, Germany, June 22, 2017.
[TPDS] Sheng Di and Franck Cappello. “Optimization of Error-Bounded Lossy Compression for Hard-to-Compress HPC Data.” IEEE Transactions on Parallel and Distributed System 29, no. 1 (2017): 129-143.

2016

[IPDPS’16] Sheng Di and Franck Cappello. “Fast error-bounded lossy HPC data compression with SZ.” 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 730-739. IEEE, 2016.