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Error-bounded lossy compression has been effective in significantly reducing the data storage/transfer burden while preserving the reconstructed data fidelity very well.
Compressing molecular dynamics trajectories: Breaking the one-bit-per-sample barrier
Jan Huwald, Stephan Richter, Bashar Ibrahim, and Peter Dittrich. 2016 · 1906
Earlier work this paper cites.
Orthonormal bases of compactly supported wavelets
Ingrid Daubechies. 1988 · 1988
Earlier work this paper cites.
Simulation of simplicity: a technique to cope with degenerate cases in geometric algorithms
Herbert Edelsbrunner and Ernst Peter Mücke. 1990 · 1990
Earlier work this paper cites.
Biorthogonal bases of compactly supported wavelets
A. Cohen, Ingrid Daubechies, and J.-C. Feauveau. 1992 · 1992
Earlier work this paper cites.
GZIP file format specification version 4.3
L Peter Deutsch. 1996 · 1996
Earlier work this paper cites.
Scalable I/O of large-scale molecular dynamics simulations: A data-compression algorithm
Andrey Omeltchenko, Timothy J. Campbell, Rajiv K. Kalia, Xinlian Liu, Aiichiro Nakano, and Priya Vashishta. 2000 · 2000
Earlier work this paper cites.
Efficient, low-complexity image coding with a set-partitioning embedded block coder
W.A. Pearlman, A. Islam, N. Nagaraj, and A. Said. 2004 · 2004
Earlier work this paper cites.
Essential Dynamics: A Tool for Efficient Trajectory Compression and Management
Tim Meyer, Carles Ferrer-Costa, Alberto Pérez, Manuel Rueda, Axel Bidon-Chanal, F. Javier Luque, Charles. A. Laughton, and Modesto Orozco. 2006 · 2006
Earlier work this paper cites.
Massively parallel quantum computer simulator
Koen De Raedt, Kristel Michielsen, H. A. De Raedt, Binh Trieu, Guido Arnold, Marcus Richter, Thomas Lippert, Hiroshi C. Watanabe, and Nobuyasu Ito. 2006 · 2006
Earlier work this paper cites.
Effects of JPEG and JPEG2000 Lossy Compression on Remote Sensing Image Classification for Mapping Crops and Forest Areas. In 2006 IEEE International Symposium on Geoscience and Remote Sensing . 790–793
A. Zabala, X. Pons, R. Diaz-Delgado, F. Garcia, F. Auli-Llinas, and J. Serra-Sagrista. 2006 · 2006
Earlier work this paper cites.
Simulating Quantum Computation by Contracting Tensor Networks
Igor L. Markov and Yaoyun Shi. 2008 · 2008
Earlier work this paper cites.
FPC: A High-Speed Compressor for Double-Precision Floating-Point Data
M. Burtscher and P. Ratanaworabhan. 2009 · 2009
Earlier work this paper cites.
SS: The Future of Seismic Imaging; Reverse Time Migration and Full Wavefield Inversion-Reverse Time Migration Imaging and Model Estimation. In Offshore Technology Conference . OTC, OTC–19879
Paul Farmer, Zheng-Zheng Joe Zhou, and David Jones. 2009 · 2009
Earlier work this paper cites.
GPU implementation of minimal dispersion recursive operators for reverse time migration
Allon Bartana and et al. 2015 · 2011
Earlier work this paper cites.
Compressing the Incompressible with ISABELA: In-situ Reduction of Spatio-temporal Data. In Euro-Par 2011 Parallel Processing , Emmanuel Jeannot, Raymond Namyst, and Jean Roman (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 366–379
Sriram Lakshminarasimhan, Neil Shah, Stephane Ethier, Scott Klasky, Rob Latham, Rob Ross, and Nagiza F. Samatova. 2011 · 2011
Earlier work this paper cites.
Interactive Multiscale Tensor Reconstruction for Multiresolution Volume Visualization
Susanne K. Suter, Jose A. Iglesias Guitian, Fabio Marton, Marco Agus, Andreas Elsener, Christoph P.E. Zollikofer, M. Gopi, Enrico Gobbetti, and Renato Pajarola. 2011 · 2011
Earlier work this paper cites.
Quantum computing and the entanglement frontier
John Preskill. 2012 · 2012
Earlier work this paper cites.
ISOBAR hybrid compression-I/O interleaving for large-scale parallel I/O optimization. In Proceedings of the 21st International Symposium on High-Performance Parallel and Distributed Computing (Delft, The Netherlands) (HPDC ’12) . Association for Computing Machinery, New York, NY, USA, 61––72
Eric R. Schendel and et al. 2012 · 2012
Earlier work this paper cites.
Improving I/O Throughput with PRIMACY: Preconditioning ID-Mapper for Compressing Incompressibility. In 2012 IEEE International Conference on Cluster Computing . 209–219
Neil Shah and et al. 2012 · 2012
Earlier work this paper cites.
Nyx: A massively parallel amr code for computational cosmology
Ann S Almgren, John B Bell, Mike J Lijewski, Zarija Lukić, and Ethan Van Andel. 2013 · 2013
Earlier work this paper cites.
HACC: Extreme scaling and performance across diverse architectures. In Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis . 1–10
Salman Habib, Vitali Morozov, Nicholas Frontiere, Hal Finkel, Adrian Pope, and Katrin Heitmann. 2013 · 2013
Earlier work this paper cites.
Auto-encoding variational Bayes
Diederik P Kingma and Max Welling. 2013 · 2013
Earlier work this paper cites.
Compression in Molecular Simulation Datasets. In Intelligence Science and Big Data Engineering . Berlin, Heidelberg, 22–29
Anand Kumar, Xingquan Zhu, Yi-Cheng Tu, and Sagar Pandit. 2013 · 2013
Earlier work this paper cites.
ISABELA for effective in situ compression of scientific data
Sriram Lakshminarasimhan, Neil Shah, Stephane Ethier, Seung-Hoe Ku, Choong-Seock Chang, Scott Klasky, Rob Latham, Rob Ross, and Nagiza F Samatova. 2013 · 2013
Earlier work this paper cites.
Tamresh – tensor approximation multiresolution hierarchy for interactive volume visualization. In Computer Graphics Forum , Vol. 32. Wiley Online Library, 151–160
Susanne K Suter, Maxim Makhynia, and Renato Pajarola. 2013 · 2013
Earlier work this paper cites.
NUMARCK: Machine Learning Algorithm for Resiliency and Checkpointing. In SC ’14: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis . 733–744
Zhengzhang Chen, Seung Woo Son, William Hendrix, Ankit Agrawal, Wei-Keng Liao, and Alok Choudhary. 2014 · 2014
Earlier work this paper cites.
The Earth System Grid Federation: An Open Infrastructure for Access to Distributed Geospatial Data
Luca Cinquini and et al. 2014 · 2014
Earlier work this paper cites.
Fixed-rate compressed floating-point arrays
Peter Lindstrom. 2014 · 2014
Earlier work this paper cites.
1-bit stochastic gradient descent and its application to data-parallel distributed training of speech DNNs. In Fifteenth annual conference of the international speech communication association
Frank Seide, Hao Fu, Jasha Droppo, Gang Li, and Dong Yu. 2014 · 2014
Earlier work this paper cites.
Data Compression for the Exascale Computing Era – Survey
Seung Son, Zhengzhang Chen, William Hendrix, Ankit Agrawal, Weikeng Liao, and Alok Choudhary. 2014 · 2014
Earlier work this paper cites.
Analysis of tensor approximation for compression-domain volume visualization
Rafael Ballester-Ripoll, Susanne K Suter, and Renato Pajarola. 2015 · 2015
Earlier work this paper cites.
Zstandard – Real-time data compression algorithm
Yann Collet. 2015 · 2015
Earlier work this paper cites.
Lossless Compression of Climate Data. In Progress in Systems Engineering , Henry Selvaraj, Dawid Zydek, and Grzegorz Chmaj (Eds.). Springer International Publishing, Cham, 391–400
Bharath Chandra Mummadisetty, Astha Puri, Ershad Sharifahmadian, and Shahram Latifi. 2015 · 2015
Earlier work this paper cites.
Exploration of lossy compression for application-level checkpoint/restart. In 2015 IEEE International Parallel and Distributed Processing Symposium . IEEE, 914–922
Naoto Sasaki, Kento Sato, Toshio Endo, and Satoshi Matsuoka. 2015 · 2015
Earlier work this paper cites.
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan and Andrew Zisserman. 2015 · 2015
Earlier work this paper cites.
Evaluating Lossy Data Compression on Climate Simulation Data within a Large Ensemble
Allison H. Baker and et al. 2016 · 2016
Earlier work this paper cites.
Fast error-bounded lossy HPC data compression with SZ. In IEEE International Parallel and Distributed Processing Symposium . 730–739
Sheng Di and Franck Cappello. 2016 · 2016
Earlier work this paper cites.
In situ and in-transit analysis of cosmological simulations
Brian Friesen, Ann Almgren, Zarija Lukić, Gunther Weber, Dmitriy Morozov, Vincent Beckner, and Marcus Day. 2016 · 2016
Earlier work this paper cites.
Deep Learning
Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2016 · 2016
Earlier work this paper cites.
Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 770–778
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
Earlier work this paper cites.
Data Compression for Climate Data
Michael Kuhn, Julian Kunkel, and Thomas Ludwig. 2016 · 2016
Earlier work this paper cites.
EAGE E-Lecture: Reverse Time Migration: How Does It Work, When To Use It
Etienne Robein. November 15, 2016 · 2016
Earlier work this paper cites.
qHiPSTER: The Quantum High Performance Software Testing Environment
Mikhail Smelyanskiy, Nicolas P. D. Sawaya, and Alán Aspuru-Guzik. 2016 · 2016
Earlier work this paper cites.
Bit Grooming: Statistically Accurate Precision-Preserving Quantization with Compression, Evaluated in the netCDF Operators (NCO, v4.4.8+)
Charles S. Zender. 2016 · 2016
Earlier work this paper cites.
Sparse communication for distributed gradient descent
Alham Fikri Aji and Kenneth Heafield. 2017 · 2017
Earlier work this paper cites.
QSGD: Communication-efficient SGD via gradient quantization and encoding
Dan Alistarh, Demjan Grubic, Jerry Li, Ryota Tomioka, and Milan Vojnovic. 2017 · 2017
Earlier work this paper cites.
Toward a Multi-method Approach: Lossy Data Compression for Climate Simulation Data. In High Performance Computing . Springer International Publishing, 30–42
Allison H. Baker, Haiying Xu, Dorit M. Hammerling, Shaomeng Li, and John P. Clyne. 2017 · 2017
Earlier work this paper cites.
Advanced Photon Source Upgrade Project preliminary design report
Thomas E. Fornek. 2017 · 2017
Earlier work this paper cites.
beta-VAE
I. Higgins, Loïc Matthey, A. Pal, C. Burgess, Xavier Glorot, M. Botvinick, S. Mohamed, and Alexander Lerchner. 2017 · 2017
Earlier work this paper cites.
Variational inference of disentangled latent concepts from unlabeled observations
Abhishek Kumar, Prasanna Sattigeri, and Avinash Balakrishnan. 2017 · 2017
Earlier work this paper cites.
Deep gradient compression: Reducing the communication bandwidth for distributed training
Yujun Lin, Song Han, Huizi Mao, Yu Wang, and William J Dally. 2017 · 2017
Earlier work this paper cites.
In-depth exploration of single-snapshot lossy compression techniques for N-body simulations. In 2017 IEEE International Conference on Big Data (Big Data) . IEEE, 486–493
Dingwen Tao, Sheng Di, Zizhong Chen, and Franck Cappello. 2017b · 2017
Earlier work this paper cites.
Significantly improving lossy compression for scientific data sets based on multidimensional prediction and error-controlled quantization. In 2017 IEEE International Parallel and Distributed Processing Symposium . IEEE, 1129–1139
Dingwen Tao, Sheng Di, Zizhong Chen, and Franck Cappello. 2017c · 2017
Earlier work this paper cites.
Ilya Tolstikhin, Olivier Bousquet, Sylvain Gelly, and Bernhard Schoelkopf. 2017 · 2017
Earlier work this paper cites.
Analysis and modeling of the end-to-end I/O performance on OLCF’s Titan supercomputer. In 2017 IEEE 19th International Conference on High Performance Computing and Communications; IEEE 15th International Conference on Smart City; IEEE 3rd International Conference on Data Science and Systems (HPCC/SmartCity/DSS) . IEEE, 1–9
Lipeng Wan, Matthew Wolf, Feiyi Wang, Jong Youl Choi, George Ostrouchov, and Scott Klasky. 2017a · 2017
Earlier work this paper cites.
Comprehensive measurement and analysis of the user-perceived I/O performance in a production leadership-class storage system. In 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) . IEEE, 1022–1031
Lipeng Wan, Matthew Wolf, Feiyi Wang, Jong Youl Choi, George Ostrouchov, and Scott Klasky. 2017b · 2017
Earlier work this paper cites.
Terngrad: Ternary gradients to reduce communication in distributed deep learning
Wei Wen, Cong Xu, Feng Yan, Chunpeng Wu, Yandan Wang, Yiran Chen, and Hai Li. 2017 · 2017
Earlier work this paper cites.
Infovae: Information maximizing variational autoencoders
Shengjia Zhao, Jiaming Song, and Stefano Ermon. 2017 · 2017
Earlier work this paper cites.
Multilevel techniques for compression and reduction of scientific data—the univariate case
Mark Ainsworth, Ozan Tugluk, Ben Whitney, and Scott Klasky. 2018 · 2018
Earlier work this paper cites.
signSGD: Compressed optimisation for non-convex problems. In International Conference on Machine Learning . PMLR, 560–569
Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, and Animashree Anandkumar. 2018 · 2018
Earlier work this paper cites.
Log Hyperbolic Cosine Loss Improves Variational Auto-Encoder
Pengfei Chen, Guangyong Chen, and Shengyu Zhang. 2018 · 2018
Earlier work this paper cites.
Optimization of Error-Bounded Lossy Compression for Hard-to-Compress HPC Data
Sheng Di and Franck Cappello. 2018 · 2018
Earlier work this paper cites.
Efficient lossy compression for scientific data based on pointwise relative error bound
Sheng Di, Dingwen Tao, Xin Liang, and Franck Cappello. 2018 · 2018
Earlier work this paper cites.
PaSTRI: Error-Bounded Lossy Compression for Two-Electron Integrals in Quantum Chemistry. In 2018 IEEE International Conference on Cluster Computing (CLUSTER) . 1–11
A. M. Gok, S. Di, Y. Alexeev, D. Tao, V. Mironov, X. Liang, and F. Cappello. 2018 · 2018
Earlier work this paper cites.
Image compression techniques: A survey in lossless and lossy algorithms
A.J. Hussain, Ali Al-Fayadh, and Naeem Radi. 2018 · 2018
Earlier work this paper cites.
Sliced Wasserstein auto-encoders. In International Conference on Learning Representations
Soheil Kolouri, Phillip E Pope, Charles E Martin, and Gustavo K Rohde. 2018 · 2018
Earlier work this paper cites.
VAPOR Github
Shaomeng Li. 2018 · 2018
Cited alongside, same era.
Algorithmic regularization in over-parameterized matrix sensing and neural networks with quadratic activations. In Conference on Learning Theory . PMLR, 2–47
Yuanzhi Li, Tengyu Ma, and Hongyang Zhang. 2018 · 2018
Cited alongside, same era.
An efficient transformation scheme for lossy data compression with point-wise relative error bound. In 2018 IEEE International Conference on Cluster Computing (CLUSTER) . IEEE, 179–189
Xin Liang, Sheng Di, Dingwen Tao, Zizhong Chen, and Franck Cappello. 2018a · 2018
Cited alongside, same era.
Error-Controlled Lossy Compression Optimized for High Compression Ratios of Scientific Datasets. In 2018 IEEE International Conference on Big Data . IEEE
Xin Liang, Sheng Di, Dingwen Tao, Sihuan Li, Shaomeng Li, Hanqi Guo, Zizhong Chen, and Franck Cappello. 2018b · 2018
Cited alongside, same era.
Understanding and modeling lossy compression schemes on HPC scientific data. In 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS) . IEEE, 348–357
Designing High-Performance MPI Libraries with On-the-fly Compression for Modern GPU Clusters. In 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS) . 444–453
Q. Zhou, C. Chu, N. S. Kumar, P. Kousha, S. M. Ghazimirsaeed, H. Subramoni, and D. K. Panda. 2021 · 2021
Later among the works it cites.
IBM Unveils 400 Qubit-Plus Quantum Processor and Next-Generation IBM Quantum System Two
[n. d.] · 2022
Later among the works it cites.
DSSIM: A Structural Similarity Index for Floating-Point Data
Allison H. Baker, Alexander Pinard, and Dorit M. Hammerling. 2022a · 2022
Later among the works it cites.
An Algorithmic and Software Pipeline for Very Large Scale Scientific Data Compression with Error Guarantees. In 2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC) . IEEE, 226–235
Tania Banerjee, Jong Choi, Jaemoon Lee, Qian Gong, Ruonan Wang, Scott Klasky, Anand Rangarajan, and Sanjay Ranka. 2022 · 2022
Later among the works it cites.
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Tao Lu, Qing Liu, Xubin He, Huizhang Luo, Eric Suchyta, Jong Choi, Norbert Podhorszki, Scott Klasky, Mathew Wolf, Tong Liu, et al · 2018
Cited alongside, same era.
Topologically Controlled Lossy Compression. In IEEE Pacific Visualization Symposium, PacificVis 2018, Japan, 2018 . IEEE Computer Society, 46–55
Maxime Soler, Mélanie Plainchault, Bruno Conche, and Julien Tierny. 2018 · 2018
Cited alongside, same era.
Improving performance of iterative methods by lossy checkponting. In Proceedings of the 27th International Symposium on High-Performance Parallel and Distributed Computing . 52–65
Dingwen Tao, Sheng Di, Xin Liang, Zizhong Chen, and Franck Cappello. 2018 · 2018
Cited alongside, same era.
GAMESS: Enabling GAMESS for exascale computing in chemistry and materials
[n. d.] · 2019
Cited alongside, same era.
EXAALT: Malecular Dynamics at the Exascale
2020 · 2019
Cited alongside, same era.
Multilevel techniques for compression and reduction of scientific data—the multivariate case
Mark Ainsworth, Ozan Tugluk, Ben Whitney, and Scott Klasky. 2019a · 2019
Cited alongside, same era.
Multilevel techniques for compression and reduction of scientific data-quantitative control of accuracy in derived quantities
Mark Ainsworth, Ozan Tugluk, Ben Whitney, and Scott Klasky. 2019b · 2019
Cited alongside, same era.
Evaluating Image Quality Measures to Assess the Impact of Lossy Data Compression Applied to Climate Simulation Data
A. H. Baker, D. M. Hammerling, and T. L. Turton. 2019 · 2019
Cited alongside, same era.
Deep learning approaches for video compression: a bibliometric analysis
Ranjeet Vasant Bidwe, Sashikala Mishra, Shruti Patil, Kailash Shaw, Deepali Rahul Vora, Ketan Kotecha, and Bhushan Zope. 2022 · 2022
Later among the works it cites.
On the Opportunities and Risks of Foundation Models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, and et al. 2022 · 2022
Later among the works it cites.
Flash-X: A multiphysics simulation software instrument
Anshu Dubey and et al. 2022 · 2022
Later among the works it cites.
DE-ZFP: An FPGA implementation of a modified ZFP compression/decompression algorithm
Mahmoud Habboush, Aiman H. El-Maleh, Muhammad E.S. Elrabaa, and Saleh AlSaleh. 2022 · 2022
Later among the works it cites.
Coordnet: Data generation and visualization generation for time-varying volumes via a coordinate-based neural network
Jun Han and Chaoli Wang. 2022 · 2022
Later among the works it cites.
Compressing multidimensional weather and climate data into neural networks
Langwen Huang and Torsten Hoefler. 2022 · 2022
Later among the works it cites.
Toward Quantity-of-Interest Preserving Lossy Compression for Scientific Data
Pu Jiao, Sheng Di, Hanqi Guo, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, and Franck Cappello. 2022 · 2022
Later among the works it cites.
Accelerating parallel write via deeply integrating predictive lossy compression with HDF5. In SC22: International Conference for High Performance Computing, Networking, Storage and Analysis . IEEE, 1–15
Sian Jin, Dingwen Tao, Houjun Tang, Sheng Di, Suren Byna, Zarija Lukic, and Franck Cappello. 2022 · 2022
Later among the works it cites.
Error-bounded learned scientific data compression with preservation of derived quantities
Jaemoon Lee, Qian Gong, Jong Choi, Tania Banerjee, Scott Klasky, Sanjay Ranka, and Anand Rangarajan. 2022 · 2022
Later among the works it cites.
Research progress on seismic imaging technology
Zhen-Chun Li and Ying-Ming Qu. 2022 · 2022
Later among the works it cites.
Optimizing Error-Bounded Lossy Compression for Scientific Data With Diverse Constraints
Yuanjian Liu, Sheng Di, Kai Zhao, Sian Jin, Cheng Wang, Kyle Chard, Dingwen Tao, Ian Foster, and Franck Cappello. 2022a · 2022
Later among the works it cites.
Deep architectures for image compression: a critical review
Dipti Mishra, Satish Kumar Singh, and Rajat Kumar Singh. 2022 · 2022
Later among the works it cites.
Seismic Data Compression: A Survey. In Advances in Geophysics, Tectonics and Petroleum Geosciences . Springer International Publishing, Cham, 253–255
Hilal Nuha, Mohamed Mohandes, Bo Liu, and Ali Al-Shaikhi. 2022 · 2022
Later among the works it cites.
Survey on Deep Learning-based Point Cloud Compression
Maurice Quach, Jiahao Pang, Dong Tian, Giuseppe Valenzise, and Frédéric Dufaux. 2022 · 2022
Later among the works it cites.
Understanding the Effects of Modern Compressors on the Community Earth Science Model. In 2022 IEEE/ACM 8th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD) . IEEE, Dallas, TX, USA, 1–10
Robert Underwood, Julie Bessac, Sheng Di, and Franck Cappello. 2022 · 2022
Later among the works it cites.
TAC: Optimizing Error-Bounded Lossy Compression for Three-Dimensional Adaptive Mesh Refinement Simulations. In Proceedings of the 31st International Symposium on High-Performance Parallel and Distributed Computing . 135–147
Daoce Wang, Jesus Pulido, Pascal Grosset, Sian Jin, Jiannan Tian, James Ahrens, and Dingwen Tao. 2022 · 2022
Later among the works it cites.
Ultrafast error-bounded lossy compression for scientific datasets. In Proceedings of the 31st International Symposium on High-Performance Parallel and Distributed Computing . 159–171
Xiaodong Yu, Sheng Di, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, and Franck Cappello. 2022 · 2022
Later among the works it cites.
Momentum-driven adaptive synchronization model for distributed DNN training on HPC clusters
Zhaorui Zhang, Zhuoran Ji, and Choli Wang. 2022 · 2022
Later among the works it cites.
MIPD: An adaptive gradient sparsification framework for distributed DNNs training
Zhaorui Zhang and Choli Wang. 2022 · 2022
Later among the works it cites.
MDZ: An Efficient Error-bounded Lossy Compressor for Molecular Dynamics. In 2022 IEEE 38th International Conference on Data Engineering (ICDE) . 27–40
Kai Zhao, Sheng Di, Danny Perez, Xin Liang, Zizhong Chen, and Franck Cappello. 2022 · 2022
Later among the works it cites.
Accelerating MPI All-to-All Communication With Online Compression On Modern GPU Clusters. In High Performance Computing: 37th International Conference, ISC High Performance 2022, Hamburg, Germany, May 29 – June 2, 2022, Proceedings (Hamburg, Germany). Springer-Verlag, Berlin, Heidelberg, 3––25
Qinghua Zhou and et al. 2022 · 2022
Later among the works it cites.
Rohan Anil, Andrew M. Dai, Orhan Firat, and et al. 2023 · 2023
Later among the works it cites.
Algorithm 1036: ATC, An Advanced Tucker Compression Library for Multidimensional Data
Wouter Baert and Nick Vannieuwenhoven. 2023 · 2023
Later among the works it cites.
Reverse Time Migration with Lossy and Lossless Wavefield Compression. In 2023 IEEE 35th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) . IEEE, 192–201
Carlos HS Barbosa and Alvaro LGA Coutinho. 2023 · 2023
Later among the works it cites.
Time Series Compression Survey
Giacomo Chiarot and Claudio Silvestri. 2023 · 2023
Later among the works it cites.
MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring
Qian Gong, Jieyang Chen, Ben Whitney, Xin Liang, Viktor Reshniak, Tania Banerjee, Jaemoon Lee, Anand Rangarajan, Lipeng Wan, Nicolas Vidal, et al · 2023
Later among the works it cites.
KD-INR: Time-Varying Volumetric Data Compression via Knowledge Distillation-based Implicit Neural Representation
Jun Han, Hao Zheng, and Chongke Bi. 2023 · 2023
Later among the works it cites.
Compressing multidimensional weather and climate data into neural networks
Langwen Huang and Torsten Hoefler. 2023 · 2023
Later among the works it cites.
Towards Improving Reverse Time Migration Performance by High-speed Lossy Compression. In 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid) . IEEE, 651–661
Yafan Huang, Kai Zhao, Sheng Di, Guanpeng Li, Maxim Dmitriev, Thierry-Laurent D Tonellot, and Franck Cappello. 2023c · 2023
Later among the works it cites.
Learning-driven lossy image compression: A comprehensive survey
Sonain Jamil, Md Jalil Piran, MuhibUr Rahman, and Oh-Jin Kwon. 2023 · 2023
Later among the works it cites.
Lossy scientific data compression with SPERR. In 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS) . IEEE, 1007–1017
Shaomeng Li, Peter Lindstrom, and John Clyne. 2023 · 2023
Later among the works it cites.
Toward Feature-Preserving Vector Field Compression
Xin Liang, Sheng Di, Franck Cappello, Mukund Raj, Chunhui Liu, Kenji Ono, Zizhong Chen, Tom Peterka, and Hanqi Guo. 2023 · 2023
Later among the works it cites.
Scientific Error-bounded Lossy Compression with Super-resolution Neural Networks. In 2023 IEEE International Conference on Big Data (BigData) . IEEE, 229–236
Jinyang Liu, Sheng Di, Sian Jin, Kai Zhao, Xin Liang, Zizhong Chen, and Franck Cappello. 2023b · 2023
Later among the works it cites.
Optimizing Scientific Data Transfer on Globus with Error-Bounded Lossy Compression. In 2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS) . 703–713
Yuanjian Liu, Sheng Di, Kyle Chard, Ian Foster, and Franck Cappello. 2023a · 2023
Later among the works it cites.
ZFP-X: Efficient Embedded Coding for Accelerating Lossy Floating Point Compression. In 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS) . 1041–1050
Bing Lu, Yida Li, Junqi Wang, Huizhang Luo, and Kenli Li. 2023 · 2023
Later among the works it cites.
ADT-FSE: A New Encoder for SZ. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (Denver, CO, USA) (SC ’23) . Association for Computing Machinery, New York, NY, USA, Article 45, 13 pages
Tao Lu and et al. 2023 · 2023
Later among the works it cites.
OpenAI, :, Josh Achiam, Steven Adler, and et al. 2023 · 2023
Later among the works it cites.
A Feature-Driven Fixed-Ratio Lossy Compression Framework for Real-World Scientific Datasets. In 2023 IEEE 39th International Conference on Data Engineering (ICDE) . 1461–1474
Md Hasanur Rahman and et al. 2023 · 2023
Later among the works it cites.
GPU-Accelerated Error-Bounded Compression Framework for Quantum Circuit Simulations. In 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS) . 757–767
Milan Shah, Xiaodong Yu, Sheng Di, Danylo Lykov, Yuri Alexeev, Michela Becchi, and Franck Cappello. 2023 · 2023
Later among the works it cites.
Black-box statistical prediction of lossy compression ratios for scientific data
Robert Underwood, Julie Bessac, David Krasowska, Jon C Calhoun, Sheng Di, and Franck Cappello. 2023a · 2023
Later among the works it cites.
ROIBIN-SZ: Fast and Science-Preserving Compression for Serial Crystallography
Robert Underwood, Chunhong Yoon, Ali Gok, Sheng Di, and Franck Cappello. 2023b · 2023
Later among the works it cites.
Efficient Communication in Federated Learning Using Floating-Point Lossy Compression
Grant Wilkins, Sheng Di, Jon C. Calhoun, Kibaek Kim, Robert Underwood, Richard Mortier, and Franck Cappello. 2023 · 2023
Later among the works it cites.
TopoSZ: Preserving Topology in Error-Bounded Lossy Compression
Lin Yan, Xin Liang, Hanqi Guo, and Bei Wang. 2023. Early Access · 2023
Later among the works it cites.
FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs. In Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing (Orlando, FL, USA) (HPDC ’23) . Association for Computing Machinery, New York, NY, USA, 129–142
Boyuan Zhang, Jiannan Tian, Sheng Di, Xiaodong Yu, Yunhe Feng, Xin Liang, Dingwen Tao, and Franck Cappello. 2023 · 2023
Later among the works it cites.
Compression for Scientific Data
Franck Cappello, Peter Lindstrom, Sheng Di, Hanqi Guo, Dingwen Tao, Robert Underwood, Xin Liang, and Kai Zhao. 2024 · 2024
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Closest in time.
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Jiajun Huang and et al. 2024a · 2024
Closest in time.
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Closest in time.
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Closest in time.
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Hieu Trung Le, Hernan Santos, and Jian Tao. 2024 · 2024
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Jaemoon Lee, Ki Sung Jung, Qian Gong, Xiao Li, Scott Klasky, Jacqueline Chen, Anand Rangarajan, and Sanjay Ranka. 2024 · 2024
Closest in time.
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Closest in time.
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Jinyang Liu and et al. 2024 · 2024
Closest in time.
Significantly Improving Fixed-Ratio Compression Framework for Resource-limited Applications. In Proceedings of the 53rd International Conference on Parallel Processing (Gotland, Sweden) (ICPP ’24) . Association for Computing Machinery, New York, NY, USA, 845–855
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Closest in time.
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Closest in time.
The effect of lossy compression of numerical weather prediction data on data analysis: a case study using enstools-compression 2023.11
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Closest in time.
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Closest in time.
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Closest in time.
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Haotian Xu, Zhaorui Zhang, Sheng Di, Benben Liu, Khalid Ayed Alharthi, and Jiannong Cao. 2024 · 2024
Closest in time.