ViSlang: A System for Interpreted Domain-Specific Languages for Scientific Visualization

Rautek, Peter; Brückner, Stefan; Gröller, M. Eduard; Hadwiger, Markus

doi:10.1109/tvcg.2014.2346318

Cited by 26 publications

(11 citation statements)

References 29 publications

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“…Examples include D3 for JavaScript [43], the InfoVis Toolkit for Java [52], or Bokeh for Python [7]. Domain-specific languages such as Vivaldi [47], Diderot [59], and ViSlang [64] provide high-level programming APIs that are tailored for application domain experts.…”

Section: Authoring Non-immersive Visualizationsmentioning

confidence: 99%

DXR: A Toolkit for Building Immersive Data Visualizations

Sicat

Choi

et al. 2019

IEEE Trans. Visual. Comput. Graphics

140

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This paper presents DXR, a toolkit for building immersive data visualizations based on the Unity development platform. Over the past years, immersive data visualizations in augmented and virtual reality (AR, VR) have been emerging as a promising medium for data sense-making beyond the desktop. However, creating immersive visualizations remains challenging, and often require complex low-level programming and tedious manual encoding of data attributes to geometric and visual properties. These can hinder the iterative idea-to-prototype process, especially for developers without experience in 3D graphics, AR, and VR programming. With DXR, developers can efficiently specify visualization designs using a concise declarative visualization grammar inspired by Vega-Lite. DXR further provides a GUI for easy and quick edits and previews of visualization designs in-situ, i.e., while immersed in the virtual world. DXR also provides reusable templates and customizable graphical marks, enabling unique and engaging visualizations. We demonstrate the flexibility of DXR through several examples spanning a wide range of applications.

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Section: Authoring Non-immersive Visualizationsmentioning

confidence: 99%

DXR: A Toolkit for Building Immersive Data Visualizations

Sicat

Choi

et al. 2019

IEEE Trans. Visual. Comput. Graphics

140

View full text Add to dashboard Cite

show abstract

“…Being specific to some domain of algorithms, DSLs trade reduced flexibility of the language for (in principle) higher human productivity of writing new programs within that domain [24]. For our purposes we merely note FEM-related DSLs for formulating and solving PDEs [1,2,12,34] as well as DSLs for processing and visualizing image and volume data [8,10,17,22,23,26,33,35]. This list does not fairly describe the sophisticated approaches to high-performance computing [23] and computational scheduling [26,33].…”

Section: Related Workmentioning

confidence: 99%

“…Domain-specific languages (DSLs) for scientific visualization partially address this need by specializing for a class of algorithms and one form of data: regular grids [8,10,17,22,23,35]. In their own ways, these languages work to separate the legible expression of visualization algorithms from technical details of data access or parallel computing.…”

Section: Introductionmentioning

confidence: 99%

“…Visualization research may benefit from systems that can take a high-level specifications of a visualization method, and a separate description of how data and fields are formed, and then compile programs that both run efficiently on the given data and support exploration of the relevant parameter spaces. Domain-specific languages (DSLs) for scientific visualization partially address this need by specializing for a class of algorithms and one form of data: regular grids [8,10,17,22,23,35]. In their own ways, these languages work to separate the legible expression of visualization algorithms from technical details of data access or parallel computing.…”

Section: Introductionmentioning

confidence: 99%

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Point Movement in a DSL for Higher-Order FEM Visualization

Collin

Chiw

Scott

et al. 2019

2019 IEEE Visualization Conference (VIS)

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Scientific visualization tools tend to be flexible in some ways (e.g., for exploring isovalues) while restricted in other ways, such as working only on regular grids, or only on unstructured meshes (as used in the finite element method, FEM). Our work seeks to expose the common structure of visualization methods, apart from the specifics of how the fields being visualized are formed. Recognizing that previous approaches to FEM visualization depend on efficiently updating computed positions within a mesh, we took an existing visualization domain-specific language, and added a mesh position type and associated arithmetic operators. These are orthogonal to the visualization method itself, so existing programs for visualizing regular grid data work, with minimal changes, on higher-order FEM data. We reproduce the efficiency gains of an earlier guided search method of mesh position update for computing streamlines, and we demonstrate a novel ability to uniformly sample ridge surfaces of higher-order FEM solutions defined on curved meshes.

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“…Domain-Specific Languages (DSLs) are a recent trend in this area, with examples including ViSlang [32] for parallel volume rendering, and Liszt [8] for portable PDE solvers.…”

Section: Introductionmentioning

confidence: 99%

Skeletons for distributed topological computation

Duke

Hosseini

2015

Proceedings of the 4th ACM SIGPLAN Workshop on Functional High-Performance Computing

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Parallel implementation of topological algorithms is highly desirable, but the challenges, from reconstructing algorithms around independent threads through to runtime load balancing, have proven to be formidable. This problem, made all the more acute by the diversity of hardware platforms, has led to new kinds of implementation platform for computational science, with sophisticated runtime systems managing and coordinating large threadcounts to keep processing elements heavily utilized. While simpler and more portable than direct management of threads, these approaches still entangle program logic with resource management. Similar kinds of highly parallel runtime system have also been developed for functional languages. Here, however, language support for higher-order functions allows a cleaner separation between the algorithm and 'skeletons' that express generic patterns of parallel computation. We report results on using this technique to develop a distributed version of the Joint Contour Net, a generalization of the Contour Tree to multifields. We present performance comparisons against a recent Haskell implementation using shared-memory parallelism, and initial work on a skeleton for distributed memory implementation that utilizes an innovative strategy to reduce inter-process communication overheads.

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ViSlang: A System for Interpreted Domain-Specific Languages for Scientific Visualization

Cited by 26 publications

References 29 publications

DXR: A Toolkit for Building Immersive Data Visualizations

DXR: A Toolkit for Building Immersive Data Visualizations

Point Movement in a DSL for Higher-Order FEM Visualization

Skeletons for distributed topological computation

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