Visualization is an indispensable tool for understanding the growing amounts of data being generated by simulation and experimental facilities. In this session we will discuss the challenges of visualizing data and tools that are useful for data exploration from laptops to supercomputing facilities. One of the biggest recent changes in high-performance computing is the increasing use of accelerators. Accelerators contain processing cores that independently are inferior to a core in a typical CPU, but these cores are replicated and grouped such that their aggregate execution provides a very high computation rate at a much lower power. Current and future CPU processors also require much more explicit parallelism. Each successive version of the hardware packs more cores into each processor, and technologies like hyperthreading and vector operations require even more parallel processing to leverage each core’s full potential.
VTK-m is a toolkit of scientific visualization algorithms for emerging processor architectures.
VTK-m supports the fine-grained concurrency for data analysis and visualization algorithms required to drive extreme scale computing by providing abstract models for data and execution that can be applied to a variety of algorithms across many different processor architectures.
ParaView is the world’s leading open-source post-processing visualization tool.
It integrates with existing tools and workflows, allowing visualizations to be easily built. With its open, flexible, and intuitive user interface, users can analyze extremely large datasets interactively in 3D or programmatically using ParaView’s batch processing.
ParaView uses VTK-m internally to accelerate visualization routines.
Dr. David Pugmire will introduce the concepts behind VTK-m and ParaView and provide demonstrations and examples of how to use each.
Both will make use of data from ADIOS to perform the visualizations. Tutorial attendees are encouraged to bring their visualization and analysis challenges for discussion.