A prototype framework for parallel visualization of large flow data. (April 2019)

• Record Type: Journal Article
• Authors: Liu, Zhanping
• Is Part Of: Advances in engineering software. Volume 130(2019)
• Page Start: 14
• Page End: 23
• Publication Date: 2019-04
• Subjects: Scientific visualization -- Flow visualization -- Parallel visualization -- Data analysis -- Streamlines -- Pathlines; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2019.02.004
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: In this paper, we present a prototype integrated framework for parallel visualization of large flow data. Still with direct access to MPI functionalities, it adopts DIY (Do it yourself) as the primary parallel computing platform, which is a layer on top of MPI to offer a set of components and mechanisms amenable to data visualization. This framework takes OSUFlow, a suite of geometry-based flow visualization algorithms, as the vector field visualization engine. The DIY-OSUFlow combination supports parallel visualization of flow data defined on Cartesian, rectilinear, and curvilinear grids, specifically in creating streamlines and pathlines. Furthermore, the framework exploits VTK (Visualization Toolkit) for versatile data input, advanced graphics rendering, and flexible scene interaction. In this way, the broad user community of VTK can take advantage of a variety of parallel flow visualization capabilities of DIY-OSUFlow (e.g., a stream surface as a triangulated connection of a collection of streamlines originating from seeds along a rake line). Preliminary results show that this framework is capable of exploiting the horsepower of processors to accelerate data processing and visualization for explorative analysis of massive steady/unsteady volume flows. Abstract: Scientific visualization seeks to provide deep insight into the complex pattern underlying big data, while flow visualization plays a crucial role in oceanographic-atmospheric modeling and computational fluid dynamics simulation. As an increasingly important strategy, parallel visualization incorporates data visualization with parallel computing by means of MPI (Message Passing Interface) to achieve efficient visual analysis to facilitate scientific study. This paper presents a prototype framework for parallel visualization of large flow data, involving MPI as the low-level parallel computing paradigm, DIY (Do It Yourself) as a block-oriented data-parallel programming library on top of MPI, OSUFlow as a geometry-based flow visualization engine, and VTK (Visualization Toolkit) for data input, graphics rendering, and scene interaction. It exposes the combined power of DIY and OSUFlow, including parallel yet seamless generation of streamlines as well as pathlines from vector data defined on Cartesian, rectilinear, and curvilinear grids, to a broad community of high-performance flow visualization through VTK. Preliminary results show that this framework is capable of exploiting the horsepower of a vast number of processors to accelerate data processing and visualization for explorative analysis of massive steady/unsteady volume flows.