BeyondPlanck III. Commander3

TL;DR

BeyondPlanck's Commander3 provides a comprehensive Bayesian framework for analyzing CMB data, addressing computational challenges and detailing resource requirements, with open-source code for community use.

Contribution

This paper introduces Commander3, a new computational infrastructure for Bayesian CMB analysis, including code design, computational solutions, and resource assessments.

Findings

Requires 1.5 TB RAM for analysis

Full Gibbs sampling takes 170 CPU-hours

Code is publicly available under GPL license

Abstract

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.