In situ visualization for computational science / Hank Childs, Janine C. Bennett, Christoph Garth, editors.
Childs, Hank.; Bennett, Janine.; Garth, Christoph.
2022
QA76.9.I52
Available Online

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Title In situ visualization for computational science / Hank Childs, Janine C. Bennett, Christoph Garth, editors.
ISBN 9783030816278 (electronic bk.)
3030816273 (electronic bk.)
3030816265
9783030816261
DOI https://doi.org/10.1007/978-3-030-81627-8
Imprint Cham : Springer, 2022.
Language English
Description 1 online resource (464 pages)
Other Standard Identifiers 10.1007/978-3-030-81627-8 doi
Call Number QA76.9.I52
Dewey Decimal Classification 001.4/226
Summary This book provides an overview of the emerging field of in situ visualization, i.e. visualizing simulation data as it is generated. In situ visualization is a processing paradigm in response to recent trends in the development of high-performance computers. It has great promise in its ability to access increased temporal resolution and leverage extensive computational power. However, the paradigm also is widely viewed as limiting when it comes to exploration-oriented use cases. Furthermore, it will require visualization systems to become increasingly complex and constrained in usage. As research efforts on in situ visualization are growing, the state of the art and best practices are rapidly maturing. Specifically, this book contains chapters that reflect state-of-the-art research results and best practices in the area of in situ visualization. Our target audience are researchers and practitioners from the areas of mathematics computational science, high-performance computing, and computer science that work on or with in situ techniques, or desire to do so in future.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed May 12, 2022).
Added Author Childs, Hank.
Bennett, Janine.
Garth, Christoph.
Series Mathematics and visualization.
Available in Other Form In Situ Visualization for Computational Science.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
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
Workows 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.

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