English
Related papers

Related papers: Fixed-PSNR Lossy Compression for Scientific Data

200 papers

The fast growth of computational power and scales of modern super-computing systems have raised great challenges for the management of exascale scientific data. To maintain the usability of scientific data, error-bound lossy compression is…

Machine Learning · Computer Science 2023-11-08 Jinyang Liu , Sheng Di , Sian Jin , Kai Zhao , Xin Liang , Zizhong Chen , Franck Cappello

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

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 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

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

We explore an error-bounded lossy compression approach for reducing scientific data associated with 2D/3D unstructured meshes. While existing lossy compressors offer a high compression ratio with bounded error for regular grid data,…

Graphics · Computer Science 2024-04-04 Congrong Ren , Xin Liang , Hanqi Guo

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

Lossy compression is one of the most effective methods for reducing the size of scientific data containing multiple data fields. It reduces information density through prediction or transformation techniques to compress the data. Previous…

Machine Learning · Computer Science 2024-09-30 Youyuan Liu , Wenqi Jia , Taolue Yang , Miao Yin , Sian Jin

Error-bounded lossy compression has been effective in significantly reducing the data storage/transfer burden while preserving the reconstructed data fidelity very well. Many error-bounded lossy compressors have been developed for a wide…

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

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

As high-performance computing architectures evolve, more scientific computing workflows are being deployed on advanced computing platforms such as GPUs. These workflows can produce raw data at extremely high throughputs, requiring urgent…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-03 Shixun Wu , Jinwen Pan , Jinyang Liu , Jiannan Tian , Ziwei Qiu , Jiajun Huang , Kai Zhao , Xin Liang , Sheng Di , Zizhong Chen , Franck Cappello

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

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

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

With ever-increasing volumes of scientific data produced by HPC applications, significantly reducing data size is critical because of limited capacity of storage space and potential bottlenecks on I/O or networks in writing/reading or…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-01-08 Dingwen Tao , Sheng Di , Xin Liang , Zizhong Chen , Franck Cappello

Error-bounded lossy compression is essential for managing the massive data volumes produced by large-scale HPC simulations. While state-of-the-art compressors such as SZ and ZFP provide strong numerical error guarantees, they often fail to…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-20 Tripti Agarwal , Sheng Di , Xin Liang , Zhaoyuan Su , Yuxiao Li , Ganesh Gopalakrishnan , Hanqi Guo , Franck Cappello

Because of vast volume of data being produced by today's scientific simulations and experiments, lossy data compressor allowing user-controlled loss of accuracy during the compression is a relevant solution for significantly reducing the…

Other Computer Science · Computer Science 2017-11-15 Dingwen Tao , Sheng Di , Hanqi Guo , Zizhong Chen , Franck Cappello

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

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
‹ Prev 1 2 3 10 Next ›