CSS490 Grid Computing Textbook No Corresponding Chapter Instructor: Munehiro Fukuda These slides were compiled from The Grid: Blueprint for a New Computer Infrastructure. Hello! Everyone, My name is Shinya Kobayashi. Today, I am going to present our paper titled “Inter-Cluster Job Coordination Using Mobile Agents” on behalf of the first author, Munehiro Fukuda. Munehiro was hoping to show up and present the paper at AMS2001, however he got to wait in Japan until he will get an H1B visa. Since I received the presentation materials from him quite recently, please allow me to present this paper using this script. I can respond to your questions as far as I know, however you can also ask Munehiro by email. His email address is on the title page of our paper. (time 1:05) Winter, 2004 CSS490 Grid Computing

Network Infrastructure Users login their organizational systems first locally or remotely. If they are affiliated with other organizations, They can login from the system of their main use to some other systems. (They are given an opportunity to use those resources in parallel). Problems: They must orchestrate job execution among the resources they use. Should those resources be limited to such a handful number of researchers? High-speed Information high way Winter, 2004 CSS490 Grid Computing

The Computational Grid Use computing resource connected to high-speed information highway as if we use electric power grid Only 30% utilization in academic/commercial environments. Many applications have only episodic requirements. So, why don’t we share computation resource? Computational results and data should be also made available to all users. Users: Computational scientists and engineers Experimental scientists Association and corporations Training and education Consumers (E-commerce) Winter, 2004 CSS490 Grid Computing

Grid Applications Category Examples Characteristics Distributed supercomputing DIS and Stellar dynamics Very large problems needing lots of computing resource at a time High throughput Chip design and parameter studies Harnessing many idle resources to increase aggregate throughput On demand Medical instrumentation Allocating special resource dynamically Data intensive Sky survey Using distributed data and needing high-volume data flows Collaborative Collaborative design Education Support communication or collaborative work Winter, 2004 CSS490 Grid Computing

Example: Distributed Interactive Simulation Fighter simulator Tank simulator Observer/Analyst Small unit (company, platoon) commander Software agents (automated enemy) Winter, 2004 CSS490 Grid Computing

Grid Services Architecture (from www.globus.org slide) High-energy physics data analysis Collaborative engineering On-line instrumentation Applications Regional climate studies Parameter studies Distributed computing Collab. design Remote control Application Toolkit Layer Data- intensive Remote viz Grid Services Layer Information Resource mgmt . . . Security Data access Fault detection Transport . . . Multicast Grid Fabric Layer Instrumentation Control interfaces QoS mechanisms Winter, 2004 CSS490 Grid Computing

Grid Systems/Tools NetSolve Legion Globus Toolkit http://icl.cs.utk.edu/netsolve/ RPC-based approach Legion http://legion.virginia.edu/ Object-based approach Globus Toolkit http://www.globus.org/ Tool-based approach Winter, 2004 CSS490 Grid Computing

NetSolve RPC-based approach Clients Agents Servers Network of servers Client RPC-based approach Clients Include a set of APIs called as (asynchronous) RPCs Agents Match client’s requests for services with servers Servers Encapsulates remotely accessed numerical libraries Agent Agent choice Scalar server Client request reply MPP servers Winter, 2004 CSS490 Grid Computing

Legion Legion classes Core objects Per-Program Scheduling Act as managers and make policy Core objects Provide mechanisms that classes use to implement policies: hosts (processors), vaults(memory), context, binding agents, etc. Per-Program Scheduling Participating sites can assure their local policies. User can choose a scheduling policy. Prog request Enactor Scheduler Converted Legion object ID By context objects reserve search Converted Logion object address By binding agents Resource database Class Host collection tty Host Host tty Resources Class tty Winter, 2004 CSS490 Grid Computing

Globus A collection of tools Resource brokers and resource co-allocators MPI, HPC++, CORBA Arch. Type, OS, memory, bandwidth GRAM (RSL-based management) Nexus (Remote execution by thread migration) MDS (Directory info. Tree) Condor NQE Load Sharing Facility IP, Message passing, ATM, shared mem. LDAP A collection of tools GRAM: Resource allocation and process management Nexus: Communication services MDS: Directory services GSI: Authentication/security services Winter, 2004 CSS490 Grid Computing

CoordAgents (The CSS490 Instructor’s New Research Project) Mobile-agent-based approach Resources: Server resources and client requests are all described in XML. Servlet: Launches a mobile agent on behalf of a client. Maintains a server resources. Mobile agents: Carries a client program, executes it remotely, and reports its results to the client. Each Server Client Outgoing Agent Web Launcher servlet Incoming Agent Rsc Mgmt servlet Jave DB Agent engine Resource XML OS Winter, 2004 CSS490 Grid Computing

CoordAgents Cont’d (The CSS490 Instructor’s New Research Project) job idle powered off!! checkpointing migration PCs Most PCs are idle PC Grid Why don’t PC users get together to use each other’s idle PCs? Challenges PCs may be powered on and off suddenly. Network bandwidth may change suddenly. Using CoordAgents Dispatches a user job. Performs check-pointing. Migrate a process dynamically. Winter, 2004 CSS490 Grid Computing