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This paper introduces a novel technique to preserve spectral features in lossy compression based on a novel fast Fourier correction algorithm\added{ for regular-grid data}. Preserving both spatial and frequency representations of data is…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-06 Congrong Ren , Robert Underwood , Sheng Di , Emrecan Kutay , Zarija Lukic , Aylin Yener , Franck Cappello , Hanqi Guo

Error-bounded lossy compression is one of the most efficient solutions to reduce the volume of scientific data. For lossy compression, progressive decompression and random-access decompression are critical features that enable on-demand…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-03 Daoce Wang , Pascal Grosset , Jesus Pulido , Jiannan Tian , Tushar M. Athawale , Jinda Jia , Baixi Sun , Boyuan Zhang , Sian Jin , Kai Zhao , James Ahrens , Fengguang Song

Increasing data volumes from scientific simulations and instruments (supercomputers, accelerators, telescopes) often exceed network, storage, and analysis capabilities. The scientific community's response to this challenge is scientific…

The growing volume of scientific simulation data presents a significant challenge for storage and transfer. Error-bounded lossy compression has emerged as a critical solution for mitigating these challenges, providing a means to reduce data…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-29 Arshan Khan , Rohit Deshmukh , Ben O'Neill

Existing auto-regressive mesh generation approaches suffer from ineffective topology preservation, which is crucial for practical applications. This limitation stems from previous mesh tokenization methods treating meshes as simple…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Gaochao Song , Zibo Zhao , Haohan Weng , Jingbo Zeng , Rongfei Jia , Shenghua Gao

Lossy compression is one of the most important strategies to resolve the big science data issue, however, little work was done to make it resilient against silent data corruptions (SDC). In fact, SDC is becoming non-negligible because of…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-08 Sihuan Li , Sheng Di , Kai Zhao , Xin Liang , Zizhong Chen , Franck Cappello

Because of the vast volume of data being produced by today's scientific simulations, lossy compression allowing user-controlled information loss can significantly reduce the data size and the I/O burden. However, for large-scale cosmology…

Information Theory · Computer Science 2017-08-08 Dingewn Tao , Sheng Di , Zizhong Chen , Franck Cappello

Scientific discoveries are increasingly constrained by limited storage space and I/O capacities. For time-series simulations and experiments, their data often need to be decimated over timesteps to accommodate storage and I/O limitations.…

With ever-increasing volumes of scientific floating-point data being produced by high-performance computing applications, significantly reducing scientific floating-point data size is critical, and error-controlled lossy compressors have…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-01-20 Robert Underwood , Sheng Di , Jon C. Calhoun , Franck Cappello

Compression of floating-point data will play an important role in high-performance computing as data bandwidth and storage become dominant costs. Lossy compression of floating-point data is powerful, but theoretical results are needed to…

Numerical Analysis · Mathematics 2024-07-03 James Diffenderfer , Alyson Fox , Jeffrey Hittinger , Geoffrey Sanders , Peter Lindstrom

Modern scientific simulations generate massive volumes of data, creating significant challenges for I/O and storage systems. Error-bounded lossy compression (EBLC) offers a solution by reducing data set sizes while preserving data quality…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-06-16 Grant Wilkins , Sheng Di , Jon C. Calhoun , Robert Underwood , Franck Cappello

Error-controlled lossy compression has been studied for years because of extremely large volumes of data being produced by today's scientific simulations. None of existing lossy compressors, however, allow users to fix the peak…

Information Theory · Computer Science 2018-07-17 Dingwen Tao , Sheng Di , Xin Liang , Zizhong Chen , Franck Cappello

Topological methods, including persistent homology, are powerful tools for analysis of high-dimensional data sets but these methods rely almost exclusively on thresholding techniques. In noisy data sets, thresholding does not always allow…

Computational Geometry · Computer Science 2016-09-08 Jennifer Kloke , Gunnar Carlsson

Today's scientific high performance computing (HPC) applications or advanced instruments are producing vast volumes of data across a wide range of domains, which introduces a serious burden on data transfer and storage. Error-bounded lossy…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-02-01 Xiaodong Yu , Sheng Di , Kai Zhao , jiannan Tian , Dingwen Tao , Xin Liang , Franck Cappello

Error-bounded lossy compression has been identified as a promising solution for significantly reducing scientific data volumes upon users' requirements on data distortion. For the existing scientific error-bounded lossy compressors, some of…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-09-26 Jinyang Liu , Sheng Di , Kai Zhao , Xin Liang , Sian Jin , Zizhe Jian , Jiajun Huang , Shixun Wu , Zizhong Chen , Franck Cappello

The generation of voluminous scientific data poses significant challenges for efficient storage, transfer, and analysis. Recently, error-bounded lossy compression methods emerged due to their ability to achieve high compression ratios while…

Machine Learning · Computer Science 2025-05-13 Guozhong Li , Muhannad Alhumaidi , Spiros Skiadopoulos , Ibrahim Hoteit , Panos Kalnis

The rapid expansion of computational capabilities and the ever-growing scale of modern HPC systems present formidable challenges in managing exascale scientific data. Faced with such vast datasets, traditional lossless compression…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-04-23 Wenqi Jia , Sian Jin , Jinzhen Wang , Wei Niu , Dingwen Tao , Miao Yin

The amount of data generated and gathered in scientific simulations and data collection applications is continuously growing, putting mounting pressure on storage and bandwidth concerns. A means of reducing such issues is data compression;…

Numerical Analysis · Mathematics 2025-05-15 Alyson Fox , Peter Lindstrom

Today's scientific simulations require a significant reduction of data volume because of extremely large amounts of data they produce and the limited I/O bandwidth and storage space. Error-bounded lossy compressor has been considered one of…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-15 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

Error-controlled lossy compressors have been widely used in scientific applications to reduce the unprecedented size of scientific data while keeping data distortion within a user-specified threshold. While they significantly mitigate the…

Databases · Computer Science 2026-03-27 Xuan Wu , Sheng Di , Tripti Agarwal , Kai Zhao , Xin Liang , Franck Cappello