![]() Kitware offers advanced ParaView support and customization services to help you achieve your goals. Learn how to efficiently and effectively use ParaView from the developers behind the platform. If you are looking to maximize ParaView’s capabilities, contact Kitware. Examples will require elementary knowledge of Python and C++. For general ParaView help, visit the Resources page. Attendees can follow along, execute some tutorial examples using Jupyter Notebooks, and deploy two example mini-apps (mesh- and particle-based) to illustrate the ideas presented. The two environments described are part of very active project developments by large teams with committed resources for future developments. No particular knowledge of the implementation details of the data model used by the two libraries are required to follow the tutorial and to adopt the concepts learned. They will have a brief overview of the current landscape of in-situ processing solutions, before focusing on two specific implementations. We will cover how to describe simulation data with Conduit and how Ascent or Catalyst can transform data, render images, and export results, discussing the pros and cons of both implementations.ĭomain scientists and code developers and visualization practitioners in HPC will benefit from this tutorial by understanding the needs and advantages of integrating an in-situ visualization support into their code. Both packages share a common project, called Conduit, which provides an intuitive model for describing hierarchical scientific data in C++, C, Fortran, and Python. Figure 1 shows This time includes both simulation and post-processing simulation time. goal is to reduce the time to gaining insight into the problem being simulated. This full-day tutorial introduces ParaView Catalyst and Ascent, two open-source implementations enabling in-situ processing. When using ParaView Catalyst in support of in situ data analysis and visualization without Damaris, the instrumented simulation starts loading a set of. Using ParaView Catalyst is a fundamental change in to the way that simulation results are obtained. In-situ processing helps mitigate these I/O bottlenecks, enabling simulation and visualization calculations to run in-memory, at higher spatial and temporal resolution, avoiding the transfer of raw data to disks. In recent years though, this paradigm has been stressed by an ever-diverging rate of growth between I/O and compute speeds. ![]() For decades, the dominant paradigm has been post-hoc visualization simulation codes iterate and save files to disk, giving the domain scientists the opportunity to read the data back at a later time for analysis. Scientific visualization and analysis are key ingredients in HPC simulation workflows. ![]()
0 Comments
Leave a Reply. |