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Accelerating Deterministic Global Optimization via GPU-parallel Interval Arithmetic
Hongzhen Zhang (Department of Chemical Engineering, KU Leuven, Leuven, Belgium), Tim Kerkenhoff (Institute of Climate and Energy Systems - Energy Systems Engineering), Neil Kichler (Software and Tools for Computational Engineering), Manuel Dahmen (Institute of Climate and Energy Systems - Energy Systems Engineering), Alexander Mitsos (JARA-CSD, Aachen, Germany, Process Systems Enginering, Institute of C…

Accelerating Deterministic Global Optimization via GPU-parallel Interval Arithmetic
Spatial Branch and Bound (B&B) algorithms are widely used for solving nonconvex problems to global optimality, yet they remain computationally expensive. Though some works have been carried out to speed up B&B via CPU parallelization, GPU parallelization is much less explored. In this work, we investigate the design of a spatial B&B algorithm that involves an interval-based GPU-parallel lower bounding solver: The domain of each B&B node is temporarily partitioned into numerous subdomains, then …

Ten simple rules for PIs to integrate Research Software Engineering into their research group
Stuart M. Allen, Neil Chue Hong, Stephan Druskat, Toby Hodges, Daniel S. Katz, Jan Linxweiler, Frank L\"offler, Lars Grunske, Heidi Seibold, Jan Philipp Thiele, Samantha Wittke
https://arxiv.org/abs/2506.20217

Ten simple rules for PIs to integrate Research Software Engineering into their research group
Research Software Engineering (RSEng) is a key success factor in producing high-quality research software, which in turn enables and improves research outcomes. However, as a principal investigator or leader of a research group you may not know what RSEng is, where to get started with it, or how to use it to maximize its benefit for your research. RSEng also often comes with technical complexity, and therefore reduced accessibility to some researchers. The ten simple rules presented in this pap…

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