English
Related papers

Related papers: A Survey on Error-Bounded Lossy Compression for Sc…

200 papers

Error-bounded lossy compression is becoming an indispensable technique for the success of today's scientific projects with vast volumes of data produced during simulations or instrument data acquisitions. Not only can it significantly…

Machine Learning · Computer Science 2023-10-24 Jinyang Liu , Sheng Di , Kai Zhao , Sian Jin , Dingwen Tao , Xin Liang , Zizhong Chen , Franck Cappello

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…

Today's scientific simulations, for example in the high-performance exascale sector, produce huge amounts of data. Due to limited I/O bandwidth and available storage space, there is the necessity to reduce scientific data of high…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-25 N. Böing , J. Holke , C. Hergl , L. Spataro , G. Gassner , A. Basermann

Data compression plays a key role in reducing storage and I/O costs. Traditional lossy methods primarily target data on rectilinear grids and cannot leverage the spatial coherence in unstructured mesh data, leading to suboptimal compression…

Lossy compressors are increasingly adopted in scientific research, tackling volumes of data from experiments or parallel numerical simulations and facilitating data storage and movement. In contrast with the notion of entropy in lossless…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-05-16 Robert Underwood , Julie Bessac , David Krasowska , Jon C. Calhoun , Sheng Di , Franck Cappello

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

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

Today's HPC applications are producing extremely large amounts of data, such that data storage and analysis are becoming more challenging for scientific research. In this work, we design a new error-controlled lossy compression algorithm…

Information Theory · Computer Science 2017-06-14 Dingwen Tao , Sheng Di , Zizhong Chen , Franck Cappello

Rapidly increasing data sizes in scientific computing are the driving force behind the need for lossy compression. The main drawback of lossy data compression is the introduction of error. This paper explains why many error-bounded…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-23 Alex Fallin , Martin Burtscher

Error-bounded lossy compression has been a critical technique to significantly reduce the sheer amounts of simulation datasets for high-performance computing (HPC) scientific applications while effectively controlling the data distortion…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-08-23 Tripti Agarwal , Sheng Di , Jiajun Huang , Yafan Huang , Ganesh Gopalakrishnan , Robert Underwood , Kai Zhao , Xin Liang , Guanpeng Li , Franck Cappello

Error-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. With ever-emerging heterogeneous high-performance computing (HPC) architecture, GPU-accelerated error-bounded compressors (such as…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-07 Jiannan Tian , Sheng Di , Xiaodong Yu , Cody Rivera , Kai Zhao , Sian Jin , Yunhe Feng , Xin Liang , Dingwen Tao , Franck Cappello

The increasing volume and velocity of science data necessitate the frequent movement of enormous data volumes as part of routine research activities. As a result, limited wide-area bandwidth often leads to bottlenecks in research progress.…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-07-12 Yuanjian Liu , Sheng Di , Kyle Chard , Ian Foster , Franck Cappello

With the ever-increasing execution scale of high performance computing (HPC) applications, vast amounts of data are being produced by scientific research every day. Error-bounded lossy compression has been considered a very promising…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-10-24 Jinyang Liu , Sheng Di , Kai Zhao , Xin Liang , Zizhong Chen , Franck Cappello

Lossy compression plays a growing role in scientific simulations where the cost of storing their output data can span terabytes. Using error bounded lossy compression reduces the amount of storage for each simulation; however, there is no…

Applications · Statistics 2021-11-30 David Krasowska , Julie Bessac , Robert Underwood , Jon C. Calhoun , Sheng Di , Franck Cappello

This paper presents error-bounded lossy compression tailored for particle datasets from diverse scientific applications in cosmology, fluid dynamics, and fusion energy sciences. As today's high-performance computing capabilities advance,…

Information Theory · Computer Science 2024-04-05 Congrong Ren , Sheng Di , Longtao Zhang , Kai Zhao , Hanqi Guo

Efficient error-controlled lossy compressors are becoming critical to the success of today's large-scale scientific applications because of the ever-increasing volume of data produced by the applications. In the past decade, many lossless…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-04 Kai Zhao , Sheng Di , Xin Liang , Sihuan Li , Dingwen Tao , Julie Bessac , Zizhong Chen , 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

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

Error-bounded lossy compression is one of the most effective techniques for scientific data reduction. However, the traditional trial-and-error approach used to configure lossy compressors for finding the optimal trade-off between…

Databases · Computer Science 2022-05-09 Sian Jin , Sheng Di , Jiannan Tian , Suren Byna , Dingwen Tao , Franck Cappello

In scientific simulations, observations, and experiments, the cost of transferring data to and from disk and across networks has become a significant bottleneck that particularly impacts subsequent data analysis and visualization. To…

Databases · Computer Science 2023-08-24 Victor A. P. Magri , Peter Lindstrom
‹ Prev 1 2 3 10 Next ›