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Load Balancing and Grid Computing. David Finkel Computer Science Department Worcester Polytechnic Institute. References. “The Anatomy of the Grid”, Ian Foster, Carl Kesselman, Steven Tuccke, International Journal of Supercomputer Applications, 2001
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Load Balancing and Grid Computing David Finkel Computer Science Department Worcester Polytechnic Institute
References • “The Anatomy of the Grid”, Ian Foster, Carl Kesselman, Steven Tuccke, International Journal of Supercomputer Applications, 2001 • “A Performance Oriented Migration Framework for the Grid”, Satish S. Vadhiyar and Jack J. Dongarra, Proceedings of CCGrid 2003, Third IEEE/ACM International Symposium on Cluster Computing and the Grid • Innumerable papers by PEDS members Finkel, Wills and Finkel, and Claypool and Finkel, with additional co-authors.
What is the Grid? (Foster et al paper) • Distributed computing infrastructure for advanced science and engineering • Runs over the Internet, potentially world-wide • Several approaches have emerged: Paper discusses Globus Toolkit
The Grid Concept • Coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organizations. • Highly controlled, with resource providers and consumers defining what is shared and the conditions of sharing. • Issues to address: Protocols, privacy, security, costs, …
Related approaches • Application Service Providers • Storage Service Providers • CORBA • DCE • Volunteer Computing (SETI @ home, Distriblets, SLINC)
Fabric Layer • Provides access and control to resources • Resources: Computational, storage, network • Enquiry functions: to determine characteristics and state of a resource • Management functions: Start, stop computations, reserve bandwidth
Collective Layer • Protocols and services not associated with a particular resource • Directory services for discovery of resources • Co-allocation, scheduling, brokering • Monitoring the Virtual Organization for failure, intrusion detection, etc.
Load Sharing - Overview • Transferring work from a heavily loaded node to a lightly loaded node • Purpose: To improve application performance • Transferring processes not suitable for fine-grain parallelism • Also known as: Load Balancing, Process Migration.
Load Sharing Issues • Criteria for heavily-loaded, lightly loaded • Measuring load (policy, implementation) • Exchanging information about load, state • Which jobs to transfer • When to transfer (new processes only, already-running processes)
Load Sharing in the Grid • “A Performance Oriented Migration Framework for the Grid”, Vadhiyar and Donngarra • Part of the GrADS project – Grid Application Development System – based at Univ. of Tennessee and other institutions • Designed for long-running computations
Load Sharing in the Grid - 2 • Basic idea – the load sharing system can run a performance model of a computation to estimate running time and resource requirements. • Application programmer is responsible for providing performance model for the application, and hooks to stop application, checkpoint state, and re-start application. • Based on MPI Programming Library, Globus Toolkit
Load Sharing in the Grid - 3 • Before application begins, Application Manager runs performance model to predict execution times, number of processors. • Determines whether an appropriate set of processors is available, schedules jobs • Monitors process of application as it runs
Load Sharing in the Grid - 4 • Load sharing can occur if • Application progress is delayed • Additional resources become available • App Manager sends message to application so it will • Checkpoint • Stop computation • Re-start on new collection of nodes
Research Directions • Load sharing on the Grid: • There’s a large body of pre-Grid research of load balancing in distributed systems • Can the results of this research be used to design load balancing systems for the Grid
Load Balancing and Grid Computing David Finkel Computer Science Department Worcester Polytechnic Institute