Grid Scheduling

1. WW Grid Grid Scheduling “A Distributed Computational Economy and the Nimrod-G Grid Resource Broker” Grid Computing and Distributed Systems (GRIDS) Lab. The University of MelbourneMelbourne, Australiawww.gridbus.org Rajkumar Buyya

2. Grid Grid Economy Scheduling Economics Agenda • A quick glance at today’s Grid computing • Resource Management challenges for Service-Oriented Grid computing • A Glance at Approaches to Grid computing • Grid Architecture for Computational Economy • Nimrod/G -- Grid Resource Broker • Scheduling Experiments on World Wide Grid testbed • Drug Design Application Case Study • GridSim Toolkit and Simulations • Conclusions

4. Virtual Lab

5. The Gridbus Vision: To Enable Service Oriented Grid Computing & Bus iness! WW Grid Nimrod-G World Wide Grid!

6. Grid Grid Economy Scheduling Economics Agenda • A quick glance at today’s Grid computing • Resource Management challenges for Service-Oriented Grid computing • A Glance at Approaches to Grid computing • Grid Architecture for Computational Economy • Nimrod/G -- Grid Resource Broker • Scheduling Experiments on World Wide Grid testbed • GridSim Toolkit and Simulations • Conclusions

7. database A Typical Grid Computing Environment Grid Information Service Grid Resource Broker Application R2 R3 R4 R5 RN Grid Resource Broker R6 R1 Resource Broker Grid Information Service

8. Security Data locality Resource Allocation & Scheduling Computational Economy Uniform Access System Management Resource Discovery Network Management Need Grid tools for managing Application Development Tools

9. What users want ?Users in Grid Economy & Strategy • Grid Consumers • Execute jobs for solving varying problem size and complexity • Benefit by selecting and aggregating resources wisely • Tradeoff timeframe and cost • Strategy: minimise expenses • Grid Providers • Contribute (“idle”) resource for executing consumer jobs • Benefit by maximizing resource utilisation • Tradeoff local requirements & market opportunity • Strategy: maximise return on investment

10. Sources of Complexity in Grid for Resource Management and Scheduling • Size (large number of nodes, providers, consumers) • Heterogeneity of resources (PCs, Workstations, clusters, and supercomputers, instruments, databases, software) • Heterogeneity of fabric management systems (single system image OS, queuing systems, etc.) • Heterogeneity of fabric management polices • Heterogeneity of application requirements (CPU, I/O, memory, and/or network intensive) • Heterogeneity in resource demand patterns (peak, off-peak, ...) • Applications need different QoS at different times (time critical results). The utility of experimental results varies from time to time. • Geographical distribution of users & located different time zones • Differing goals (producers and consumers have different objectives and strategies) • Unsecure and Unreliable environment

11. Traditional approaches to resource management & scheduling are NOT useful for Grid ? • They use centralised policy that need • complete state-information and • common fabric management policy or decentralised consensus-based policy. • Due to too many heterogenous parameters in the Grid it is impossible to define/get: • system-wide performance matrix and • common fabric management policy that is acceptable to all. • “Economic” paradigm proved as an effective institution in managing decentralization and heterogeneity that is present in human economies! • Hence, we propose/advocate the use of “computational economy” principles in the management of resources and scheduling computations on the Grid.

12. Benefits of Computational Economies • It provides a nice paradigm for managing self interested and self-regulating entities (resource owners and consumers) • Helps in regulating supply-and-demand for resources. • Services can be priced in such a way that equilibrium is maintained. • User-centric / Utility driven: Value for money! • Scalable: • No need of central coordinator (during negotiation) • Resources(sellers) and also Users(buyers) can make their own decisions and try to maximize utility and profit. • Adaptable • It helps in offering different QoS (quality of services) to different applications depending the value users place on them. • It improves the utilisation of resources • It offers incentive for resource owners for being part of the grid! • It offers incentive for resource consumers for being good citizens • There is large body of proven Economic principles and techniques available, we can easily leverage it.

13. New challenges of Computational Economy • Resource Owners • How do I decide prices ? (economic models?) • How do I specify them ? • How do I enforce them ? • How do I advertise & attract consumers ? • How do I do accounting and handle payments? • ….. • Resource Consumers • How do I decide expenses ? • How do I express QoS requirements ? • How I trade between timeframe & cost ? • …. • Any tools, traders & brokers available to automate the process ?

14. Grid EconomyGrid Scheduling Economics Agenda • A quick glance at today’s Grid computing • Resource Management challenges for next generation Grid computing • A Glance at Approaches to Grid computing • Grid Architecture for Computational Economy • Nimrod-G -- Grid Resource Broker • Deadline and Budget Constrained (DBC) Scheduling Experiments on World Wide Grid testbed • Conclusions

15. NetSolve mix-and-match Object-oriented Internet/partial-P2P Grid Computing Approaches Network enabled Solvers Market/Computational Economy Nimrod-G

16. Australia Nimrod-G GridSim Virtual Lab Active Sheets DISCWorld ..new coming up Europe UNICORE MOL UK eScience Poland MC Broker EU Data Grid EuroGrid MetaMPI Dutch DAS XW, JaWS Japan Ninf DataFarm Korea... N*Grid USA Globus Legion OGSA Javelin AppLeS NASA IPG Condor-G Jxta NetSolve AccessGrid and many more... Cycle Stealing & .com Initiatives Distributed.net SETI@Home, …. Entropia, UD, Parabon,…. Public Forums Global Grid Forum P2P Working Group IEEE TFCC Grid & CCGrid conferences Many Grid Projects & Initiatives http://www.gridcomputing.com

17. WW Grid Many Testbeds ? & who pays ?, who regulates supply and demand ? GUSTO (decommissioned) World Wide Grid Legion Testbed NASA IPG

18. Testbeds so far -- observations • Who contributed resources & why ? • Volunteers: for fun, challenge, fame, charismatic apps, public good like distributed.net & SETI@Home projects. • Collaborators: sharing resources while developing new technologies of common interest – Globus, Legion, Ninf, Gridbus, Nimrod-G, etc. unless you know lab. leaders, it is impossible to get access! • How long ? • Short term: excitement is lost, too much of admin. Overhead (Globus inst+), no incentive, policy change,… • What we need ? Grid Marketplace! • Regulates supply-and-demand, offers incentive for being players, simple, scalable solution, quasi-deterministic – proven model in real-world.

19. Grid Grid Economy Scheduling Economics Agenda • A quick glance at today’s Grid computing • Resource Management challenges for Service-Oriented Grid computing • A Glance at Approaches to Grid computing • Grid Architecture for Computational Economy • Nimrod/G -- Grid Resource Broker • Scheduling Experiments on World Wide Grid testbed • GridSim Toolkit and Simulations • Conclusions

20. Building Grid Economy(Next Generation Grid Computing!) To enable the creation and promotion of: Grid Marketplace (competitive) ASP Service Oriented Computing . . . And let users focus on their own work (science, engineering, or commerce)!

21. GRACE: A ReferenceGrid Architecture for Computational Economy Grid Bank Information Service Grid Market Services Sign-on HealthMonitor Info ? Grid Node N … Grid Explorer … Secure ProgrammingEnvironments Job Control Agent Grid Node1 Applications Schedule Advisor QoS Pricing Algorithms Trade Server Trading Trade Manager Accounting Resource Reservation Misc. services … Deployment Agent JobExec Resource Allocation Storage Grid Resource Broker … R1 R2 Rm Grid Middleware Services Grid Consumer Grid Service Providers

22. Grid Components Applications and Portals Grid Apps. … Prob. Solving Env. Collaboration Engineering Web enabled Apps Scientific Grid Tools Development Environments and Tools … Web tools Libraries Languages Monitoring Resource Brokers Debuggers Grid Middleware Distributed Resources Coupling Services … QoS Security Information Process Resource Trading Market Info Local Resource Managers … TCP/IP & UDP Queuing Systems Operating Systems Libraries & App Kernels Grid Fabric Networked Resources across Organisations … Storage Systems Data Sources Clusters Scientific Instruments Computers

23. Economy Grid = Globus + GRACE Applications Grid Apps. … Science Engineering Commerce Portals ActiveSheet High-level Services and Tools … Grid Tools Cactus MPI-G CC++ Nimrod Parametric Language Nimrod-G Broker Higher Level Resource Aggregators Core Services Grid Middleware MDS GRAM GASS DUROC GARA GMD GBank GTS Globus Security Interface (GSI) Grid Fabric Local Services GRD QBank JVM Condor TCP UDP eCash LSF PBS Linux Irix Solaris

24. Economic Models • Price-based: Supply,demand,value, wealth of economic system • Commodity Market Model • Posted Price Model • Bargaining Model • Tendering (Contract Net) Model • Auction Model • English, first-price sealed-bid, second-price sealed-bid (Vickrey), and Dutch (consumer:low,high,rate; producer:high, low, rate) • Proportional Resource Sharing Model • Monopoly (one provider) and Oligopoly (few players) • consumers may not have any influence on prices. • Bartering • Shareholder Model • Partnership Model See SPIE ITCom 2001 paper!: with Heinz Stockinger, CERN!

25. Call for Bid(DT) Grid Open Trading Protocols Trade Manager Get Connected Reply to Bid (DT) API Trade Server Pricing Rules Negotiate Deal(DT) …. Confirm Deal(DT, Y/N) DT - Deal Template: - resource requirements (TM) - resource profile (TS) - price (any one can set) - status - change the above values - negotiation can continue - accept/decline - validity period Cancel Deal(DT) Change Deal(DT) Get Disconnected

26. Cost Model • Without cost model any shared system becomes un-managable • Charge users more for remote facilities than their own • Choose cheaper resources before more expensive ones • Cost units (G$) may be • Dollars • Shares in global facility • Stored in bank

27. Machine 1 Machine 5 User 1 1 3 User 5 2 1 Cost Matrix @ Grid site X • Non-uniform costing • Encourages use of local resources first • Real accounting system can control machine usage Resource Cost = Function (cpu, memory, disk, network, software, QoS, current demand, etc.) Simple: price based on peaktime, offpeak, discount when less demand, ..

28. Grid Grid Economy Scheduling Economics Agenda • A quick glance at today’s Grid computing • Resource Management challenges for Service-Oriented Grid computing • A Glance at Approaches to Grid computing • Grid Architecture for Computational Economy • Nimrod/G -- Grid Resource Broker • Scheduling Experiments on World Wide Grid testbed • GridSim Toolkit and Simulations • Conclusions

29. Nimrod/G : A Grid Resource Broker • A resource broker for managing, steering, and executing task farming (parameter sweep/SPMD model) applications on Grid based on deadline and computational economy. • Based on users’ QoS requirements, our Broker dynamically leases services at runtime depending on their quality, cost, and availability. • Key Features • A single window to manage & control experiment • Persistent and Programmable Task Farming Engine • Resource Discovery • Resource Trading • Scheduling & Predications • Generic Dispatcher & Grid Agents • Transportation of data & results • Steering & data management • Accounting

30. Parametric Computing(What Users think of Nimrod Power) Parameters Magic Engine Multiple Runs Same Program Multiple Data Killer Application for the Grid! Courtesy: Anand Natrajan, University of Virginia

31. Sample P-Sweep/Task Farming Applications Bioinformatics: Drug Design / Protein Modelling Combinatorial Optimization: Meta-heuristic parameter estimation Ecological Modelling: Control Strategies for Cattle Tick Sensitivityexperiments on smog formation Data Mining Electronic CAD: Field Programmable Gate Arrays High Energy Physics: Searching for Rare Events Computer Graphics: Ray Tracing Finance: Investment Risk Analysis VLSI Design: SPICE Simulations Civil Engineering: Building Design Network Simulation Automobile: Crash Simulation Aerospace: Wing Design astrophysics

32. Molecules Protein Drug Design: Data Intensive Computing on Grid • It involves screening millions of chemical compounds (molecules) in the Chemical DataBase (CDB) to identify those having potential to serve as drug candidates. Chemical Databases (legacy, in .MOL2 format)

33. Data Generation Results • [deadline, budget, optimization preference] MEG(MagnetoEncephaloGraphy) Data Analysis on the Grid: Brain Activity Analysis Analysis All pairs (64x64) of MEG data by shifting the temporal region of MEG data over time: 0 to 29750: 64x64x29750 jobs 64 sensors MEG 2 3 1 Data Analysis 5 Nimrod-G 4 Life-electronics laboratory, AIST World-Wide Grid • Provision of expertise in • the analysis of brain function • Provision of MEG analysis [Collaboration with Osaka University, Japan]

34. P-study Applications -- Characteristics • Code (Single Program: sequential or threaded) • Long-running Instances • Numerous Instances (Multiple Data) • High Resource Requirements • High Computation-to-Communication Ratio • Embarrassingly/Pleasantly Parallel

35. Thesis • Perform parameter sweep (bag of tasks) (utilising distributed resources) within “T” hours or early and cost not exceeding $M. • Three Options/Solutions: • Using pure Globus commands • Build your own Distributed App & Scheduler • Use Nimrod-G (Resource Broker)

36. Remote Execution Steps Choose Resource Transfer Input Files Set Environment Start Process Pass Arguments Monitor Progress Summary View Job View Event View Read/Write Intermediate Files Transfer Output Files +Resource Discovery, Trading, Scheduling, Predictions, Rescheduling, ...

37. Using Pure Globus/Legion commands Do all yourself! (manually) Total Cost:$???

38. Build Distributed Application & Scheduler Build App case by case basis Complicated Construction E.g., AppLeS/MPI based Total Cost:$???

39. Nimrod-G Broker Automating Distributed Processing Compose, Submit, & Play!

40. Nimrod & Associated Family of Tools Remote Execution Server (on demand Nimrod Agent) P-sweep App. Composition: Nimrod/ Enfusion Resource Management and Scheduling: Nimrod-G Broker Design Optimisations: Nimrod-O App. Composition and Online Visualization: Active Sheets Grid Simulation in Java: GridSim Drug Design on Grid: Virtual Lab File Transfer Server

41. A Glance at Nimrod-G Broker Nimrod/G Client Nimrod/G Client Nimrod/G Client Nimrod/G Engine Schedule Advisor Trading Manager Grid Store Grid Dispatcher Grid Explorer Grid Middleware Globus, Legion, Condor, etc. TM TS GE GIS Grid Information Server(s) RM & TS RM & TS RM & TS G C L G Legion enabled node. Globus enabled node. L G C L RM: Local Resource Manager, TS: Trade Server Condor enabled node. See HPCAsia 2000 paper!

42. Nimrod/G Grid Broker Architecture Legacy Applications Nimrod-G Clients Customised Apps (Active Sheet) Monitoring and Steering Portals P-Tools (GUI/Scripting) (parameter_modeling) Farming Engine Meta-Scheduler Algorithm1 Programmable Entities Management Schedule Advisor . . . Resources Jobs Tasks Channels AlgorithmN Nimrod-G Broker IP hourglass! AgentScheduler Agents JobServer Grid Explorer Trading Manager Database Dispatcher & Actuators . . . Globus-A Legion-A Condor-A P2P-A . . . Condor GMD Globus Legion P2P GTS G-Bank Middleware . . . Computers Local Schedulers Storage Networks Instruments Fabric . . . PC/WS/Clusters Condor/LL/NQS Database Radio Telescope

43. Cost A Nimrod/G Monitor Deadline Legion hosts Globus Hosts Bezek is in both Globus and Legion Domains

44. User Requirements: Deadline/Budget

45. Nimrod Proxy Nimrod-G World-Wide Grid Active Sheet:Microsoft Excel Spreadsheet Processing on Grid

47. Grid Info Server Nimrod-G Grid Broker Task Farming Engine Grid Scheduler Grid Trade Server Do this in 30 min. for $10? Grid Tools And Applications Nimrod Agent User Process Local Resource Manager ProcessServer Grid Dispatcher File Server File access Nimrod/G Interactions Grid Node Compute Node User Node

48. Adaptive Scheduling Steps Discover More Resources Discover Resources Establish Rates Compose & Schedule Evaluate & Reschedule Meet requirements ? Remaining Jobs, Deadline, & Budget ? Distribute Jobs

49. Deadline and Budget Constrained Scheduling Algorithms

50. Grid Grid Economy Scheduling Economics Agenda • A quick glance at today’s Grid computing • Resource Management challenges for Service-Oriented Grid computing • A Glance at Approaches to Grid computing • Grid Architecture for Computational Economy • Nimrod/G -- Grid Resource Broker • Scheduling Experiments on World Wide Grid testbed • GridSim Toolkit and Simulations • Conclusions