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Adaptive Grid Computing

Adaptive Grid Computing. Detecting and Adjusting for Dynamic Grid Conditions. Experiments with a Grid-Enabled Computational Framework. Dave Angulo, Ian Foster Chuang Liu, Matei Ripeanu, Michael Russell, Lingyun Yang Distributed Systems Laboratory

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Adaptive Grid Computing

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  1. Adaptive Grid Computing Detecting and Adjusting for Dynamic Grid Conditions

  2. Experiments with a Grid-Enabled Computational Framework Dave Angulo, Ian Foster Chuang Liu, Matei Ripeanu, Michael Russell, Lingyun Yang Distributed Systems Laboratory University of Chicago & Argonne National Laboratory Gabrielle Allen, Thomas Dramlitsch, Gerd Lanferman, Ed Seidel, Thomas Radke Max-Planck-Institut für Gravitationsphysik

  3. Acknowledgements • This work was supported in part by the NSF-funded Grid Application Development Software project under Grant No. 9975020. • We are grateful to our GrADS project colleagues for discussions on the topics discussed here.

  4. Research Goals • Investigate methods and structures for efficient Grid execution via in-depth study of a demanding application, including • Constructs for adapting to heterogeneity • Constructs for dynamic resource acquisition • Create testbed for GrADSoft components, as they emerge • Investigate utility of computational frameworks as facilitator of Grid computing

  5. Adaptation to Dynamic Grid Environments • Migrate to “faster/ cheaper” system • When better system discovered • When requirements change • When characteristics change (e.g., competition)

  6. Adaptation to Dynamic Grid Environments • Migrate to “faster/ cheaper” system • When better system discovered • When requirements change • When characteristics change (e.g., competition)

  7. Cactus WormMigrationThorn Resource Selector Client Thorn Performance Degradation Detection App & other thorns GlobusToolkit™ GRISs Migration Logic Manager (Under Development) GlobusToolkit™GRISs Resources Cactus Worm Architecture External Processes / Services CactusWormServer Globus Toolkit™GRAM Cactus “flesh” NWS Resource selector GlobusToolkit™GIIS

  8. Migration Demonstration GIIS Running on jupitor.isi.edu Resource Selector Service Running on hamachi.cs.uchicago.edu Cluster at UIUC Cluster at UCSD Cactus Worm Server Running on amajor.cs.uiuc.edu

  9. Migration Demonstration GIIS Resource Selector Service Cluster at UIUC Cluster at UCSD Cactus WormServer Computational application begins run NetLogger records performance and displays visual graph

  10. Migration Demonstration GIIS Resource Selector Service Cluster at UIUC Cluster at UCSD Cactus WormServer Competing application on one node steals CPU cycles NetLogger

  11. Migration Demonstration GIIS Resource Selector Service Cluster at UIUC Cluster at UCSD Cactus WormServer Resource Selector Service contacted NetLogger

  12. Migration Demonstration GIIS Resource Selector Service Cluster at UIUC Cluster at UCSD Cactus WormServer resource list sent to Worm Server NetLogger

  13. Migration Demonstration GIIS Resource Selector Service Cluster at UIUC Cluster at UCSD Cactus WormServer Worm Server shuts down app NetLogger

  14. Migration Demonstration GIIS Resource Selector Service Cluster at UIUC Cluster at UCSD Cactus WormServer Worm Server starts app on new resouces NetLogger

  15. Performance Results

  16. Gabrielle Allen; Dave Angulo; Ian Foster; Gerd Lanfermann; Chuang Liu; Thomas Radke; Ed Seidel; John Shalf. The Cactus Worm: Experiments with Dynamic Resource Discovery and Allocation in a Grid Environment. In International Journal of High-Performance Computing Applications Volume 15, Number 4, 2001 http://people.cs.uchicago.edu/~dangulo/papers/ This presentation: http://www.cs.uchicago.edu/~dangulo/scdemo.ppt

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