Gander, Martin J.Martin J.GanderLunet, ThibautThibautLunetRuprecht, DanielDanielRuprechtSpeck, RobertRobertSpeck2022-04-262022-04-262023-10SIAM Journal on Scientific Computing 45 (5): A2275-A2303 (2023-10)http://hdl.handle.net/11420/12370Parallel-in-time integration has been the focus of intensive research efforts over the past two decades due to the advent of massively parallel computer architectures and the scaling limits of purely spatial parallelization. Various iterative parallel-in-time (PinT) algorithms have been proposed, like Parareal, PFASST, MGRIT, and Space-Time Multi-Grid (STMG). These methods have been described using different notations and the convergence estimates that are available for some of them are difficult to compare. We describe Parareal, PFASST, MGRIT and STMG for the Dahlquist model problem using a common notation and give precise convergence estimates using generating functions. This allows us, for the first time, to directly compare their convergence. We prove that all four methods eventually converge super-linearly and compare them directly numerically. Our framework also allows us to find new methods.en1064-8275SIAM Journal on Scientific Computing20235A2275A2303http://rightsstatements.org/vocab/InC/1.0/Mathematics - Numerical AnalysisMathematics - Numerical AnalysisComputer Science - Computational Engineering; Finance; and ScienceComputer Science - Numerical AnalysisMathematikA unified analysis framework for iterative parallel-in-time algorithmsJournal Article10.15480/882.431010.1137/22M148716310.15480/882.43102203.16069v1Journal Article