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Toward a Multi-method Approach: Lossy Data Compression for Climate Simulation Data

机译：迈向多方法方法：气候模拟数据的有损数据压缩

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Earth System Model (ESM) simulations are increasingly constrained by the amount of data that they generate rather than by computational resources. The use of lossy data compression on model output can reduce storage costs and data transmission overheads, but care must be taken to ensure that science results are not impacted. Choosing appropriate compression algorithms and parameters is not trivial given the diversity of data produced by ESMs and requires an understanding of both the attributes of the data and the properties of the chosen compression methods. Here we discuss the properties of two distinct approaches for lossy compression in the context of a well-known ESM, demonstrating the different strengths of each, to motivate the development of an automated multi-method approach for compression of climate model output.

机译：地球系统模型（ESM）模拟越来越受到它们生成的数据量而不是计算资源的约束。在模型输出上使用有损数据压缩可以减少存储成本和数据传输开销，但是必须注意确保科学结果不受影响。考虑到ESM产生的数据的多样性，选择合适的压缩算法和参数并不是一件容易的事，并且需要了解数据的属性和所选压缩方法的属性。在这里，我们讨论了在著名的ESM上下文中两种不同的有损压缩方法的特性，展示了每种方法的不同优势，以激励开发一种自动多方法压缩气候模型输出的方法。

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来源
《High performance computing》|2017年|30-42|共13页
会议地点 Frankfurt(DE)
作者
Allison H. Baker; Haiying Xu; Dorit M. Hammerling; Shaomeng Li; John P. Clyne;
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The National Center for Atmospheric Research, Boulder, CO 80305, USA;

The National Center for Atmospheric Research, Boulder, CO 80305, USA;

The National Center for Atmospheric Research, Boulder, CO 80305, USA;

The National Center for Atmospheric Research, Boulder, CO 80305, USA;

The National Center for Atmospheric Research, Boulder, CO 80305, USA;

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专利

1. Evaluating image quality measures to assess the impact of lossy data compression applied to climate simulation data [J] . Baker A. H., Hammerling D. M., Turton L. Computer Graphics Forum: Journal of the European Association for Computer Graphics . 2019,第3期

机译：评估图像质量措施，以评估有损数据压缩的影响应用于气候模拟数据
2. Evaluating lossy data compression on climate simulation data within a large ensemble [J] . Baker Allison H., Hammerling Dorit M., Mickelson Sheri A., Geoscientific Model Development Discussions . 2016,第12期

机译：在大范围内评估气候模拟数据的有损数据压缩
3. Pointwise redundancy in lossy data compression and universal lossy data compression [J] . Kontoyiannis I. IEEE Transactions on Information Theory . 2000,第1期

机译：有损数据压缩和通用有损数据压缩中的逐点冗余
4. Toward a Multi-method Approach: Lossy Data Compression for Climate Simulation Data [C] . Allison H. Baker, Haiying Xu, Dorit M. Hammerling, ISC High Performance Conference . 2017

机译：朝多种方法方法：气候模拟数据的有损数据压缩
5. Optimizing DCT-Based Lossy Compression for Scientific Datasets [D] . ?Chen, Jiaxi 2020

机译：优化基于DCT的科学数据集的损耗压缩
6. Performance evaluation of lossy quality compression algorithms for RNA-seq data [O] . Rongshan Yu, Wenxian Yang, Shun Wang 2020

机译：RNA-SEQ数据有损质量压缩算法的性能评估
7. Evaluating image quality measures to assess the impact of lossy data compression applied to climate simulation data [O] . A. H. Baker, D. M. Hammerling, T. L. Turton 2019

机译：评估图像质量措施，以评估有损数据压缩的影响应用于气候模拟数据
8. Simple, Low Overhead Data Compression Algorithm for Converting Lossy Compression Processes to Lossless. [R] . Abbott, W. D. 1993

机译：用于将有损压缩过程转换为无损耗的简单低开销数据压缩算法。

Toward a Multi-method Approach: Lossy Data Compression for Climate Simulation Data

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