In Situ Visualization for Computational Science

In Situ Visualization for Computational Science: Background and Foundational Topics.- Data Reduction Techniques.- Sampling for Scientific Data Analysis and Reduction.- In Situ Wavelet Compression on Supercomputers for Post Hoc Exploration.- In Situ Statistical Distribution-based Data Summarization and Visual Analysis.- Exploratory Time-Dependent Flow Visualization via In Situ Extracted Lagrangian Representations.- Work ows and Scheduling.- Unlocking Large Scale Uncertainty Quantification with In Transit Iterative Statistics.- Decaf: Decoupled Dataflows for In Situ Workflows.- Parameter Adaptation In Situ: Design Impacts and Trade-offs.- Resource-aware Optimal Scheduling of In Situ Analysis.- Tools.- Leveraging Production Visualization Tools In Situ.- The Adaptable IO System (ADIOS).- Ascent: A Flyweight In Situ Library for Exascale Simulations.- The SENSEI Generic In Situ Interface: Tool and Processing Portability at Scale.- In Situ Solutions with CinemaScience.- New Research Results and Looking Forward.- Deep Learning-based Upscaling for In Situ Volume Visualization.- Scalable CPU Ray Tracing for In Situ Visualization Using OSPRay.- Multivariate Functional Approximation of Scientific Data.- A Simulation-Oblivious Data Transport Model for Flexible In Transit Visualization.- Distributed Multi-tenant In Situ Analysis using Galaxy.- Proximity Portability and In Transit, M-to-N Data Partitioning and Movement in SENSEI.