Neuroth, TysonSauer, FranzMa, Kwan-LiuGleicher, Michael and Viola, Ivan and Leitte, Heike2019-06-022019-06-0220191467-8659https://doi.org/10.1111/cgf.13690https://diglib.eg.org:443/handle/10.1111/cgf13690We introduce a visual analysis system with GPU acceleration techniques for large sets of trajectories from complex dynamical systems. The approach is based on an interactive Boolean combination of subsets into a Focus+Context phase-space visualization. We achieve high performance through efficient bitwise algorithms utilizing runtime generated GPU shaders and kernels. This enables a higher level of interactivity for visualizing the large multivariate trajectory data. We explain how our design meets a set of carefully considered analysis requirements, provide performance results, and demonstrate utility through case studies with many-particle simulation data from two application areas.Humancentered computingScientific visualization10.1111/cgf.13690297-309