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ParaView : ウィキペディア英語版
ParaView

ParaView is an open source multiple-platform application for interactive, scientific visualization. It has a client–server architecture to facilitate remote visualization of datasets, and generates level of detail (LOD) models to maintain interactive frame rates for large datasets. It is an application built on top of the Visualization Tool Kit (VTK) libraries. Where VTK is a set of libraries that provide visualization services for data, task, and pipeline parallelism, ParaView is an application designed for data parallelism on shared-memory or distributed-memory multicomputers and clusters. It can also be run as a single-computer application.
== Summary ==
ParaView is an open source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities.
ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data.
ParaView is an application framework as well as a turn-key application. The ParaView code base is designed in such a way that all of its components can be reused to quickly develop vertical applications. This flexibility allows ParaView developers to quickly develop applications that have specific functionality for a specific problem domain.
ParaView runs on distributed and shared memory parallel and single processor systems. It has been successfully tested on Windows, Mac OS X, Linux, IBM Blue Gene, Cray Xt3 and various Unix workstations, clusters and supercomputers. Under the hood, ParaView uses Visualization Tool Kit (VTK) as the data processing and rendering engine and has a user interface written using Qt.
The goals of the ParaView team include the following:
* Develop an open-source, multi-platform visualization application.
* Support distributed computation models to process large data sets.
* Create an open, flexible, and intuitive user interface.
* Develop an extensible architecture based on open standards.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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