Image processing for the grid: a toolkit for building grid-enabled image processing applications

Hastings, Shannon; Kurç, Tahsin; Langella, Stephen; Çatalyürek, Ümit V.; Pan, Tony; Saltz, Joel

doi:10.1109/ccgrid.2003.1199350

Cited by 58 publications

(39 citation statements)

References 11 publications

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“…The first one is grid-enabling medical image analysis [11,45,23]. In a clinical context, medical image analysis (segmentation, registration) and exploitation (augmented reality for intervention planning or intra-operative support) require full interaction because computer programs are not yet competitive with the human visual system for mining these structured and noisy data.…”

Section: Motivationmentioning

confidence: 99%

Scheduling for Responsive Grids

Germain-Renaud

Loomis²,

Mościcki

et al. 2007

J Grid Computing

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Abstract. Grids are facing the challenge of seamless integration of the grid power into everyday use. One critical component for this integration is responsiveness, the capacity to support on-demand computing and interactivity. Grid scheduling is involved at two levels in order to provide responsiveness: the policy level and the implementation level. The main contributions of this paper are as follows. First, we present a detailed analysis of the performance of the EGEE grid with respect to responsiveness. Second, we examine two user-level schedulers located between the general scheduling layer and the application layer. These are the DIANE (DIstributed ANalysis Environment) framework, a general-purpose overlay system, and a specialized, embedded scheduler for gPTM3D, an interactive medical image analysis application. Finally, we define and demonstrate a virtualization scheme, which achieves guaranteed turnaround time, schedulability analysis, and provides the basis for differentiated services. Both methods target a brokering-based system organized as a federation of batch-scheduled clusters, and an EGEE implementation is described.

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Section: Motivationmentioning

confidence: 99%

Scheduling for Responsive Grids

Germain-Renaud

Loomis²,

Mościcki

et al. 2007

J Grid Computing

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“…A recent trend has seen grid-based systems emerging [12], implementing systems for different application domains such as medical imaging [14], computer vision, simulation, data visualization, graphical interactive sessions [15], etc. Grid systems allow data-and CPU-intensive processes to run on clusters of heterogeneous computers, potentially located at different sites.…”

Section: Related Workmentioning

confidence: 99%

<title>Multimedia content analysis and indexing: evaluation of a distributed and scalable architecture</title>

et al. 2003

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multimedia information systems, content-based searching, media indexing, media processing, distributed computing, grid computing, web services Multimedia search engines facilitate the retrieval of documents from large media content archives now available via intranets and the Internet. Over the past several years, many research projects have focused on algorithms for analyzing and indexing media content efficiently. However, special system architectures are required to process large amounts of content from real-time feeds or existing archives. Possible solutions include dedicated distributed architectures for analyzing content rapidly and for making it searchable. The system architecture we propose implements such an approach: a highly distributed and reconfigurable batch media content analyzer that can process media streams and static media repositories. Our distributed media analysis application handles media acquis ition, content processing, and document indexing. This collection of modules is orchestrated by a task flow management component, exploiting data and pipeline parallelism in the application. A scheduler manages load balancing and prioritizes the different tasks. Workers implement application-specific modules that can be deployed on an arbitrary number of nodes running different operating systems. Each application module is exposed as a web service, implemented with industry-standard interoperable middleware components such as Microsoft ASP.NET and Sun J2EE. Our system architecture is the next generation system for the multimedia indexing application demonstrated by www.speechbot.com. It can process large volumes of audio recordings with minimal support and maintenance, while running on low-cost commodity hardware. The system has been evaluated on a server farm running concurrent content analysis processes.

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“…The last few years have seen active development and deployment of many such workflows in various domains [4][5][6] and these workflows require considerable amounts of computing power. Therefore, it is natural to explore the possibility of executing them on large-scale computing platforms such as grids [7].…”

Section: Introductionmentioning

confidence: 99%