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David Abramson & Hoang Anh Nguyen Monash University
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Background ◦ Scientific Workflow ◦ Tiled Display Wall ◦ Why do we need a SWF-TDW link ? Design and Implementation Case Study Conclusions & Future works
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In-silico science (e-Science) ◦ Complex process ◦ Multiple steps in different computing environment Scientific workflows ◦ Help automate, manage and execute steps ◦ Provide a high level, robust, repeatable research environment.
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SWF technology ◦ Application of workflow technology to solve scientific problems [1] ◦ Different from Business Workflow SWF Management System (SWFMS) ◦ Specification, modification, run, re-run, and monitoring of workflows Number of SWFMSs: Kepler, Taverna, Triana, Vistrails, etc. Kepler was chosen to implement our prototype
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Built on top of Ptolemy II ◦ Actor-oriented modelling ◦ Vergil user-interface Actor-oriented ◦ Actors with input/output ports ◦ Director Powerful SWFMS ◦ Web and grid-services support ◦ Provenance information
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Figure 1: Sample Workflow in Kepler (source: [2])
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What is a TDW ? ◦ Visualization cluster ◦ Multiple displays controlled by a powerful computer/cluster ◦ Acts like one or many virtual displays TDW could be ◦ Projectors ◦ LCDs
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Figure 2: Scalable Display Wall view from the back (Source [3])
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Figure 3: An Optiportal at Monash Clayton ( Source [4] )
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Built on top of Rocks Using SAGE, CGLX, COVISE as rendering middleware SAGE: Scalable Adaptive Graphics Environment ◦ Open source ◦ Distributed architecture: decouple graphic rendering and graphic display
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Figure 4: SAGE architecture SAIL: Sage Application Interface Library Sage receive r Sage receive r Sage receive r Sage receive r Sage receive r Sage receive r Free Space Manage r Free Space Manage r UI Clie nt SAIL App 1 SAIL App 2 App 3 SAIL SAGE messages Pixel stream
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Natural marriage ◦ Computation and visualization To date, no easy method connecting SWF to TDW. ◦ Manual process ◦ Did not receive a lot of attention from workflow community
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Goals: ◦ Provide seamless link between SWFs and TDW ◦ Middleware independence ◦ Future user interactions Design Alternatives ◦ SSH actor ◦ SAGE actor ◦ Distributed architecture: dedicated server
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SSH protocol Simple Inflexible Simple Inflexible SSH Actor Figure 5: Solution using SSH actor
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messages Pixel stream Sage receiver Sage receiver Sage receiver Sage receiver Sage receiver Sage receiver Free Space Manag er Free Space Manag er UI Client App SAIL SAGE actor UI Client JNI Kepler code (Java) SAIL Figure 6: SAGE actor block diagram compact possible feeding user feedbacks to workflow intensive computation on machine running Kepler middleware dependent compact possible feeding user feedbacks to workflow intensive computation on machine running Kepler middleware dependent
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Figure 7: Distributed Architecture Server Interface OptIPortal Middleware OptIPortal Middleware Server Interface OptiServer OptIPortal Kepler OptIPortal Actor OptIPortal Middleware OptIPortal Middleware OptIPortal Middleware OptIPortal Middleware middleware- independent highly distributed small communication overhead middleware- independent highly distributed small communication overhead
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Figure 8: Implementation messages Pixel stream Sage receiver Sage receiver Sage receiver Sage receiver Sage receiver Sage receiver Free Space Manag er Free Space Manag er SAIL App 1 SAIL App 2 App 3 SAIL OptiUI Client OptiServer Kepler OptIPortal Actor
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OptiportalActor ◦ Stream files ◦ Communicate with OptiServer OptiServer ◦ Background process controlling the visualization OptiUI ◦ Custom SAGE UI
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Illustrate the ease of use with OptiportalActor Use OptiportalActor in a set of optical microscopy workflows ◦ To visualize images of antibody cancer therapies* Part of a larger project ◦ Virtual microscopy ◦ Demonstrating the utility of workflows for microscopy
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Developed in the Faculty of Medicine, Monash University Fluorescent labeled antibodies, together with various reagents, are used to mark three distinct tissue types: ◦ tumour nuclei ◦ “stroma” or connective tissue ◦ blood vessels that feed the tumour These therapies work by denaturing the blood vessels to the tumor
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Figure 9: Cancer Nuclei, Blood vessels, Stroma in confocal microscopy Nuclei Stroma Blood vessels Merged image
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Figure 10: Confocal scanning workflow
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Figure 11: Cancer image stack on Optiportal
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Figure 12: Therapy effectiveness measurement workflow
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Figure 13: Therapy effectiveness calculation on Optiportal
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SWF-TDW linkage Demonstration the system with a case study in optical microscopy To-dos ◦ Support more data-types (currently images and movies) ◦ Support other middleware ◦ Support more interactive modes of operation: computational steering environment.
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[1] Lin, C., Lu, S., Lai, Z., Chebotko, A., Fei, X., Hua, J. and Farsha, F. “Service-oriented architecture for view: A visual scientific workflow management system.”, In SCC ’08: Proceedings of the 2008 IEEE International Conference on Services Computing, pages 335–342, Washington, DC, USA, 2008. IEEE Computer Society. [2] https://kepler-project.org/users/copy_of_LotkaWorkflow.png/image_largehttps://kepler-project.org/users/copy_of_LotkaWorkflow.png/image_large [3] http://systems.cs.princeton.edu/omnimedia/images/back24.jpghttp://systems.cs.princeton.edu/omnimedia/images/back24.jpg [4] http://messagelab.monash.edu.au/Infrastructure/OptiPortalhttp://messagelab.monash.edu.au/Infrastructure/OptiPortal [5] http://www.sagecommons.org/images/stories/SAGEcomponents.jpghttp://www.sagecommons.org/images/stories/SAGEcomponents.jpg
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