Multifacets of lossy compression for scientific data in the Joint-Laboratory of Extreme Scale Computing

被引：1

作者：

Cappello, Franck ^{[1
]}

Acosta, Mario ^{[10
]}

Agullo, Emmanuel ^{[9
]}

Anzt, Hartwig ^{[12
]}

Calhoun, Jon ^{[7
]}

Di, Sheng ^{[2
]}

Giraud, Luc ^{[9
]}

Gruetzmacher, Thomas ^{[12
]}

Jin, Sian ^{[4
]}

Sano, Kentaro ^{[8
]}

Sato, Kento ^{[8
]}

Singh, Amarjit ^{[8
]}

Tao, Dingwen ^{[5
]}

Tian, Jiannan ^{[6
]}

Ueno, Tomohiro ^{[8
]}

Underwood, Robert ^{[3
]}

Vivien, Frederic ^{[9
]}

Yepes, Xavier ^{[11
]}

Kazutomo, Yoshii ^{[1
]}

Zhang, Boyuan ^{[6
]}

机构：

[1] Argonne Natl Lab, Lemont, IL 60439 USA

[2] Argonne Natl Lab, Math & Comp Sci MCS Div, Lemont, IL USA

[3] Argonne Natl Lab, Math & Comp Sci Div, Lemont, IL USA

[4] Indiana Univ, Bloomington, IN USA

[5] Indiana Univ, HighPerformance Data Analyt & Comp Lab, Bloomington, IN USA

[6] Indiana Univ, Intelligent Syst Engn, Bloomington, IN USA

[7] Clemson Univ, Holcombe Dept Elect & Comp Engn, Clemson, SC USA

[8] RIKEN, Ctr Computat Sci, Kobe, Japan

[9] Natl Res Inst Comp & Automat, Lyon, France

[10] Barcelona Supercomp Ctr, Earth Sci Dept, Computat Grp, Barcelona, Spain

[11] Barcelona Supercomp Ctr, Barcelona, Spain

[12] Karlsruhe Inst Technol, Karlsruhe, Germany

来源：

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2025年 / 163卷

基金：

美国国家科学基金会;

关键词：

Lossy compression; Scientific data; Compression for AI; GPU acceleration; I/O scheduling; EARTH SYSTEM MODEL; GMRES; SIMULATION; I/O;

D O I：

10.1016/j.future.2024.05.022

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The Joint Laboratory on Extreme-Scale Computing (JLESC) was initiated at the same time lossy compression for scientific data became an important topic for the scientific communities. The teams involved in the JLESC played and are still playing an important role in developing the research, techniques, methods, and technologies making lossy compression for scientific data a key tool for scientists and engineers. In this paper, we present the evolution of lossy compression for scientific data from 2015, describing the situation before the JLESC started, the evolution of this discipline in the past 8 years (until 2023) through the prism of the JLESC collaborations on this topic and some of the remaining open research questions.

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页数：27

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