What to Support When You’re Compressing: The State of Practice Gaps and Opportunities for Scientific Data Compression
Abstract
Details
- Title: Subtitle
- What to Support When You’re Compressing: The State of Practice Gaps and Opportunities for Scientific Data Compression
- Creators
- Franck Cappello - Argonne National LaboratoryRobert Underwood - Argonne National LaboratoryYuri Alexeev - Argonne National LaboratoryAlison Baker - NSF National Center for Atmospheric ResearchEbru Bozdağ - Colorado School of MinesMartin Burtscher - Texas State UniversityKyle Chard - Argonne National LaboratorySheng Di - Argonne National LaboratoryKyle Gerard Felker - Argonne National LaboratoryPaul Christopher O'Grady - SLAC National Accelerator LaboratoryHanqi Guo - The Ohio State UniversityYafan Huang - University of IowaPeng Jiang - University of IowaSian Jin - Temple UniversityPetter Johansson - KTH Royal Institute of TechnologyShaomeng Li - Nvidia (United States)Xin Liang - University of KentuckyErik Lindahl - Stockholm UniversityPeter Lindstrom - Lawrence Livermore National LaboratoryZarija Lukić - Lawrence Livermore National LaboratoryMagnus Lundborg - KTH Royal Institute of TechnologyDanylo LykovMasaru Nagaso - RIKEN Center for Computational ScienceKento Sato - RIKEN Center for Computational ScienceAmarjit Singh - RIKEN Center for Computational ScienceSeung Woo Son - University of Massachusetts LowellShihui Song - University of IowaWilliam Tang - Princeton Plasma Physics LaboratoryDingwen Tao - Indiana University BloomingtonJiannan Tian - University of KentuckyKazutomo Yoshii - Argonne National LaboratoryKai Zhao - Florida State University
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, pp.1966-1979
- Conference
- SC '25: The International Conference for High Performance Computing, Networking, Storage and Analysis
- Series
- ACM Conferences
- DOI
- 10.1145/3712285.3759856
- Publisher
- ACM
- Grant note
- Exascale Computing Project (ECP): 17-SC-20-SC U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research (ASCR): DE-AC02-06CH11357 National Science Foundation: OAC-2003709/2303064, OAC-2104023/2247080, OAC-2311875/2311876/2311877, OAC-2312673, OAC-2034169, OAC-1751143, OAC-2330367, OAC-2313122, OAC-2311756, OIA-2327266, OAC-2103621 CNRS (LABRI)Universite de Bordeaux, Bordeaux INPConseil Regional d'AquitaineKobe City through the Foundation for Computational ScienceState Research Agency: PID2020-116324RA-I00 U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences: DEAC02-76SF00515 Department of Energy, Office of Science: DE-SC0022223 European Union through 'MDDB: Molecular Dynamics Data Bank: 101094651 Swedish e-Science Research Center
This research was supported by the Exascale Computing Project (ECP), Project Number: 17-SC-20-SC, a collaborative effort of two DOE organizations - the Office of Science and the National Nuclear Security Administration, responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering, and early testbed platforms, to support the nation's exascale computing imperative. The material was supported by the U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research (ASCR), under contract DE-AC02-06CH11357, and supported by the National Science Foundation under Grant OAC-2003709/2303064, OAC-2104023/2247080, OAC-2311875/2311876/2311877, OAC-2312673, OAC-2034169, OAC-1751143, OAC-2330367, OAC-2313122, OAC-2311756, OIA-2327266 and OAC-2103621. We acknowledge the computing resources provided on Bebop (operated by the Laboratory Computing Resource Center at Argonne). Some of the experiments presented in this paper were carried out using the PlaFRIM experimental testbed, supported by Inria, CNRS (LABRI and IMB), Universite de Bordeaux, Bordeaux INP, and Conseil Regional d'Aquitaine (see https://www.plafrim.fr). TEZip's work has been supported by the COE research grant in computational science from Hyogo Prefecture and Kobe City through the Foundation for Computational Science. XIOS-SZ - Mario Acosta and Xavier Yepes-Arbos have received co-funding from the State Research Agency through OEMES (PID2020-116324RA-I00). We thank the Texas Advanced Computing Center (TACC) at the University of Texas at Austin for providing computational resources on the 'Frontera' system [55]. Use of the Linac Coherent Light Source (LCLS), SLAC National Accelerator Laboratory, is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Contract No. DEAC02-76SF00515. This work has been supported in part by the Department of Energy, Office of Science, under Award Number DE-SC0022223, as well as by equipment donations from NVIDIA Corporation. This work has been co-funded by the European Union through 'MDDB: Molecular Dynamics Data Bank. The European Repository for Biosimulation Data [101094651], and The Swedish e-Science Research Center.
- Language
- English
- Date published
- 11/16/2025
- Academic Unit
- Computer Science
- Record Identifier
- 9985027353902771