Abstract
Iterated Runge-Kutta (IRK) methods are a class of explicit solution methods for initial value problems of ordinary differential equations (ODEs) which possess a considerable potential for parallelism across the method and the ODE system. In this paper, we consider the sequential and parallel implementation of IRK methods with the main focus on the optimization of the locality behavior. We introduce different implementation variants for sequential and shared-memory computer systems and analyze their runtime and cache performance on two modern supercomputer systems.
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Korch, M., Rauber, T. (2007). Locality Optimized Shared-Memory Implementations of Iterated Runge-Kutta Methods. In: Kermarrec, AM., Bougé, L., Priol, T. (eds) Euro-Par 2007 Parallel Processing. Euro-Par 2007. Lecture Notes in Computer Science, vol 4641. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74466-5_78
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DOI: https://doi.org/10.1007/978-3-540-74466-5_78
Publisher Name: Springer, Berlin, Heidelberg
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