论文标题

超越普兰克三世。 Commander3

BeyondPlanck III. Commander3

论文作者

Galloway, M., Andersen, K. J., Aurlien, R., Banerji, R., Bersanelli, M., Bertocco, S., Brilenkov, M., Carbone, M., Colombo, L. P. L., Eriksen, H. K., Foss, M. K., Franceschet, C., Fuskeland, U., Galeotta, S., Gerakakis, S., Gjerløw, E., Hensley, B., Herman, D., Iacobellis, M., Ieronymaki, M., Ihle, H. T., Jewell, J. B., Karakci, A., Keihänen, E., Keskitalo, R., Maggio, G., Maino, D., Maris, M., Paradiso, S., Partridge, B., Reinecke, M., Suur-Uski, A. -S., Svalheim, T. L., Tavagnacco, D., Thommesen, H., Watts, D. J., Wehus, I. K., Zacchei, A.

论文摘要

我们描述了BeyondPlanck协作实施的端到端贝叶斯CMB分析的计算基础架构。该代码称为Commander3,并为CMB和微波观测的全局分析提供了一个统计上一致的框架,并且对于广泛的遗产,当前和未来的实验可能很有用。该论文有三个主要目标。首先,我们提供了现有代码库的高级概述,旨在指导希望根据自己的需求扩展和调整代码的读者,或以不同的编程语言从头开始重新将其重新完成。其次,我们讨论了在任何全局CMB分析框架中都会出现的一些关键计算挑战,例如时间序的数据,FFT优化以及并行化和负载平衡的内存压缩。第三,我们量化了当前超越Planck分析的CPU和RAM要求,并发现有效分析总共需要1.5 tb的RAM,并且完整GIBBS样本的总成本为170 CPU-HRS,包括低级处理和高级组件分离和高级组件分离,并且在当前低级计算设备的功能中很好。现有的代码库可根据GNU通用公共图书馆(GPL)许可证公开获得。

We describe the computational infrastructure for end-to-end Bayesian CMB analysis implemented by the BeyondPlanck collaboration. This code is called commander3, and provides a statistically consistent framework for global analysis of CMB and microwave observations, and may be useful for a wide range of legacy, current, and future experiments. The paper has three main goals. Firstly, we provide a high-level overview of the existing code base, aiming to guide readers who wish to extend and adapt the code according to their own needs, or to reimplement it from scratch in a different programming language. Secondly, we discuss some critical computational challenges that arise within any global CMB analysis framework, for instance in-memory compression of time-ordered data, FFT optimization, and parallelization and load-balancing. Thirdly, we quantify the CPU and RAM requirements for the current BeyondPlanck analysis, and find that a total of 1.5 TB of RAM is required for efficient analysis, and the total cost of a full Gibbs sample is 170 CPU-hrs, including both low-level processing and high-level component separation, which is well within the capabilities of current low-cost computing facilities. The existing code base is made publicly available under a GNU General Public Library (GPL) license.

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