Grid-Enabled Visualization with GVK

Kranzlmüller, Dieter; Heinzlreiter, Paul; Rosmanith, Herbert; Volkert, Jens

doi:10.1007/978-3-540-24689-3_18

Cited by 17 publications

(7 citation statements)

References 10 publications

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“…Kanzlmueller [KHRV04] present a Grid Visualization Kernel ( GVK ) based on Globus Toolkit [Fos05]. The authors propose a set of visualization services as an extension to the grid middleware services that can be used as building blocks for creating visualization applications.…”

Section: Technical Aspectsmentioning

confidence: 99%

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State‐of‐the‐Art Report in Web‐based Visualization

Mwalongo

Krone

Reina

et al. 2016

Computer Graphics Forum

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In this report, we review the current state of the art of web-based visualization applications. Recently, an increasing number of web-based visualization applications have emerged. This is due to the fact that new technologies offered by modern browsers greatly increased the capabilities for visualizations on the web. We first review these technical aspects that are enabling this development. This includes not only improvements for local rendering like WebGL and HTML5, but also infrastructures like grid or cloud computing platforms. Another important factor is the transfer of data between the server and the client. Therefore, we also discuss advances in this field, for example methods to reduce bandwidth requirements like compression and other optimizations such as progressive rendering and streaming. After establishing these technical foundations, we review existing web-based visualization applications and prototypes from various application domains. Furthermore, we propose a classification of these web-based applications based on the technologies and algorithms they employ. Finally, we also discuss promising application areas that would benefit from web-based visualization and assess their feasibility based on the existing approaches.

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Section: Technical Aspectsmentioning

confidence: 99%

“…Example for a visualization service using grid middleware: setup of a simulation process including in‐situ visualization using the Grid Visualization Kernel (image adapted from Kanzlmueller et al [KHRV04]).…”

Section: Technical Aspectsmentioning

confidence: 99%

State‐of‐the‐Art Report in Web‐based Visualization

Mwalongo

Krone

Reina

et al. 2016

Computer Graphics Forum

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“…The Grid Visualization Kernel (GVK) [10] is an extension to the Globus Toolkit for visualization in the grid and the Visapult software. The latter efficiently runs distributed VR tasks using the IBRAVR algorithm [1].…”

Section: Related Work and Conceptsmentioning

confidence: 99%

Optimizing the pre-processing of scientific visualization techniques using QEF

Oliveira

Porto

Giraldi

et al. 2010

Proceedings of the 8th International Workshop on Middleware for Grids, Clouds and E-Science

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Scientific Visualization is a computer-based field concerned with techniques that allow scientists to create graphical representations from datasets generated by computational simulations or acquisition instruments. To address the computational cost of visualization tasks, specially for large datasets, researchers have explored grid environments as a platform for their parallel evaluation. It is however not trivial to adapt each different visualization technique to run in grid environments. A desirable alternative would separate the specificities of data and process distribution in grids from visualization computation logic. In this work we claim that the QEF (query evaluation framework) leverages scientific visualization computation with the above mentioned characteristics. Visualization computation techniques are modeled as operators in an algebra and integrated with a set of control operators that manage data distribution leading to a parallel QEP (query execution plan). We show the benefits of parallelization for two of those techniques: particle tracing and volume rendering. For these techniques, our experiments demonstrate many positive aspects of the solution presented, as well as opportunities for future work.

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“…To achieve this behaviour two principle approaches are suitable, the first is via software rendering on the central processing unit (CPU) and the second way is hardware accelerated rendering on the graphics processing unit (GPU). The software rendering can be done on a single machine, in a cluster environment using all different paradigms of parallelization, like Open Multi-Processing (OpenMP) for shared memory architectures, Message Passing Interface (MPI) for a Beowulf [3] computing cluster or in a GRID environment [4]. Often such techniques enable the user to investigate very large datasets, which would otherwise not fit in the memory of a single visualization workstation, but the visualization process is often quite slow and Beowulf clusters or shared memory machines are restricted in access.…”

Section: The Power Of Real-time Visualizationmentioning

confidence: 99%

Visualization needs and techniques for astrophysical simulations

Kapferer

Riser

2008

New J. Phys.

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Abstract. Numerical simulations have evolved continuously towards being an important field in astrophysics, equivalent to theory and observation. Due to the enormous developments in computer sciences, both hardware-and software-architecture, state-of-the-art simulations produce huge amounts of raw data with increasing complexity. In this paper some aspects of problems in the field of visualization in numerical astrophysics in combination with possible solutions are given. Commonly used visualization packages along with a newly developed approach to real-time visualization, incorporating shader programming to uncover the computational power of modern graphics cards, are presented. With these techniques at hand, real-time visualizations help scientists to understand the coherences in the results of their numerical simulations. Furthermore a fundamental problem in data analysis, i.e. coverage of metadata on how a visualization was created, is highlighted.

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Grid-Enabled Visualization with GVK

Cited by 17 publications

References 10 publications

State‐of‐the‐Art Report in Web‐based Visualization

State‐of‐the‐Art Report in Web‐based Visualization

Optimizing the pre-processing of scientific visualization techniques using QEF

Visualization needs and techniques for astrophysical simulations

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