Automatic Distribution of Rendering Workloads in a Grid Enabled Collaborative Visualization Environment

Grimstead, Ian J.; Avis, Nicholas John; Walker, David W.

doi:10.1109/sc.2004.13

Cited by 20 publications

(9 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Automatic balancing of rendering workloads in collaborative visualization environments is presented in [9]. Available resources are allocated automatically, which enables visualization clients to request services regardless of the particular system implementation.…”

Section: Distributed Visualizationmentioning

confidence: 99%

Service-Oriented Information Visualization for Smart Environments

Thiede

Tominski

Schumann

2009

2009 13th International Conference Information Visualisation

View full text Add to dashboard Cite

Smart environments consist of several interconnected devices. The device ensemble can change dynamically as mobile devices enter or leave the environment.To utilize such environments efficiently for information visualization, we propose a service-oriented architecture. Various services run on different machines and visualizations are generated dynamically depending on the environment's current situation. The necessary adaptation to available output devices is driven by instantiation of different service implementations, by parameterizing service invocations, and by adapting the visualization pipeline at run-time. We implemented a prototype that provides parallel coordinates, scatter plot matrices, and a map display.

show abstract

Section: Distributed Visualizationmentioning

confidence: 99%

Service-Oriented Information Visualization for Smart Environments

Thiede

Tominski

Schumann

2009

2009 13th International Conference Information Visualisation

View full text Add to dashboard Cite

show abstract

“…Grid resources must be dedicated to the system to avoid severe slowdowns, because resource monitoring and selection issues are not addressed in this system. Some Grid projects use the GPU as a graphics accelerator to visualize large-scale data in server Grid environments [15,18]. In these environments, resources are dedicated to Grid users.…”

Section: Related Workmentioning

confidence: 99%

A Resource Selection System for Cycle Stealing in GPU Grids

2008

View full text Add to dashboard Cite

This paper presents a resource selection system for exploiting graphics processing units (GPUs) as general-purpose computational resources in desktop Grid environments. Our system allows Grid users to share remote GPUs, which are traditionally dedicated to local users who directly see the display output. The key contribution of the paper is to develop this novel system for non-dedicated environments. We first show criteria for defining idle GPUs from the Grid users' point of view. Based on these criteria, our system uses a screensaver approach with some sensors that detect idle resources at a low overhead. The idea for this lower overhead is to avoid GPU intervention during resource monitoring. Detected idle GPUs are then selected according to a matchmaking service, making the system adaptive to the rapid advance of GPU architecture. Though the system itself is not yet interoperable with current desktop Grid systems, our idea can be applied to screensaver-based systems such as BOINC. We evaluate the system using Windows PCs with three generations of nVIDIA GPUs. The experimental results show that our system achieves a low overhead of at most 267 ms, minimizing interference to local users while maximizing the performance delivered to Grid users. Some case studies are also performed in an office environment to demonstrate the effectiveness of the system in terms of the amount of detected idle time.

show abstract

“…Grimstead et al [20] presented a distributed, collaborative grid enabled visualization environment that supports automated resource discovery across heterogeneous machines. Running the Resource-Aware…”

Section: Ieee Transactions On Computersmentioning

confidence: 99%

Self-Adaptive Configuration of Visualization Pipeline Over Wide-Area Networks

Gao

Zhu

et al. 2008

IEEE Trans. Comput.

View full text Add to dashboard Cite

Next-generation scientific applications require the capabilities to visualize large archival datasets or on-going computer simulations of physical and other phenomena over wide-area network connections. To minimize the latency in interactive visualizations across wide-area networks, we propose an approach that adaptively decomposes and maps the visualization pipeline onto a set of strategically selected network nodes. This scheme is realized by grouping the modules that implement visualization and networking subtasks, and mapping them onto computing nodes with possibly disparate computing capabilities and network connections. Using estimates for communication and processing times of subtasks, we present a polynomial-time algorithm to compute a decomposition and mapping to achieve minimum end-to-end delay of the visualization pipeline. We present experimental results using geographically distributed deployments to demonstrate the effectiveness of this method in visualizing datasets from three application domains.

show abstract

Automatic Distribution of Rendering Workloads in a Grid Enabled Collaborative Visualization Environment

Cited by 20 publications

References 4 publications

Service-Oriented Information Visualization for Smart Environments

Service-Oriented Information Visualization for Smart Environments

A Resource Selection System for Cycle Stealing in GPU Grids

Self-Adaptive Configuration of Visualization Pipeline Over Wide-Area Networks

Contact Info

Product

Resources

About