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

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 Worm Server
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 Worm Server
Competing application on one node steals CPU cycles
NetLogger

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

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

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

14. Migration Demonstration
GIIS
Resource Selector
Service
Cluster at UIUC
Cluster at UCSD
Cactus Worm Server
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
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