VisIt

VisIt is an Open Source, interactive, scalable, visualization, animation, and analysis tool. From Unix, Windows, or Mac workstations, users can interactively visualize and analyze data ranging in scale from small (<10 core) desktop-sized projects to large (>10,000 core) leadership-class computing facility simulation campaigns.

Distributed Computing: VisIt employs a distributed computing architecture, allowing it to efficiently process and visualize large datasets across multiple computing resources. This enables users to work with extremely large datasets that may not fit into the memory of a single machine.
Interactive Visualization: VisIt provides a highly active visualization environment, allowing users to dynamically explore and manipulate their data. Users can interactively adjust visual properties, apply filters and transformations, and animate their visualizations.
Wide Range of Data Formats: VisIt supports a wide range of data formats commonly used in scientific and engineering domains, including structured and unstructured grids, point clouds, polygonal data, and volumetric data. It also supports various file formats for input and output, making it compatible with other software tools.
Data Processing and Analysis: VisIt offers a rich set of data processing and analysis capabilities. Users can apply filters and transformations to preprocess their data, calculate derived quantities, extract subsets, and perform statistical analyses. It also provides tools for time-dependent data analysis and visualization.
Customizable Workflows: VisIt allows users to create custom workflows by combining different data processing and visualization modules. Users can create complex analysis pipelines using a visual programming interface or by scripting with Python. This flexibility enables users to tailor their workflows to their specific needs.
Collaboration and Remote Visualization: VisIt supports collaboration and remote visualization through client-server architecture. Users can connect to a remote VisIt server, enabling them to work together on the same dataset and visualize results in real-time. This is particularly useful for distributed teams or when working with remote computing resources.