Cosmological Particle Data Compression in Practice

Max Zeyen, J. Ahrens, H. Hagen, K. Heitmann, S. Habib
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引用次数: 9

Abstract

In cosmological simulations, trillions of particles are handled and several terabytes of particle data are generated in each time step. Transferring this data directly from memory to disk in an uncompressed way results in a massive load on I/O and storage systems. Hence, one goal of domain scientists is to compress the data before storing it to disk while minimizing the loss of information. In this in situ scenario, the available time for the compression of one time step is limited. Therefore, the evaluation of compression techniques has shifted from only focusing on compression rates to including throughput and scalability. This study aims to evaluate and compare state-of-the-art compression techniques applied to particle data. For the investigated compression techniques, quantitative performance indicators such as compression rates, throughput, scalability, and reconstruction errors are measured. Based on these factors, this study offers a comprehensive analysis of the individual techniques and discusses their applicability for in situ compression. Based on this study, future challenges and directions in the compression of cosmological particle data are identified.
实践中的宇宙粒子数据压缩
在宇宙学模拟中,处理数万亿粒子,每个时间步产生数tb的粒子数据。以未压缩的方式将这些数据直接从内存传输到磁盘会导致I/O和存储系统的巨大负载。因此,领域科学家的一个目标是在将数据存储到磁盘之前压缩数据,同时最大限度地减少信息损失。在这种现场场景中,压缩一个时间步的可用时间是有限的。因此,对压缩技术的评估已经从只关注压缩率转变为包括吞吐量和可伸缩性。本研究旨在评估和比较应用于粒子数据的最新压缩技术。对于所研究的压缩技术,量化的性能指标,如压缩率、吞吐量、可伸缩性和重构误差进行了测量。基于这些因素,本研究对各个技术进行了综合分析,并讨论了它们在原位压缩中的适用性。在此基础上,提出了未来宇宙学粒子数据压缩面临的挑战和方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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