1. Eddie.Aronovich@cs.tau.ac.il Grid Infrastructure

2. Acknowledgements Presentation is based on slides from: –Roberto Barbera, University of Catania and INFN (EGEE Tutorial Roma, 02.11.2005) –Mike Mineter, Concepts of grid computing –Fabrizio Gagliardi, EGEE Project Director, CERN, Geneva, Switzerland (Naregi Symposium 2005 – Tokyo) –Fabrizio Gagliardi, EGEE Project Director, CERN, Geneva, Switzerland (APAC, 27 September 2005) –Guy Warner, NeSC Training Team (An Induction to EGEE for GOSC and the NGS NeSC, 8th December 2004 ) Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 2

3. What is it ? Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 3 SERVERS Clients

4. IT all about IT Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 4

5. Hardware utilization Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 5

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8. THE WORLD NEEDS ONLY FIVE COMPUTERS (Thomas J. Watson) Google grid Microsoft's live.com Yahoo! Amazon.com eBay Salesforce.com Well, that's O(5) ;) Greg Matter (http://blogs.sun.com/Gregp/entry/the_world_needs_only_five) Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 8

9. Scaling Scale-up –Add more resources within the system –Does not requires changes in the applications –Limited extension –Singe point of failure Scape-out –Add more systems –Architecture dependent (needs change of code) –Economically Howto ? –Split the operation into groups –Perform each group on a different machine Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 9

10. How fast can parallelization be ? Let: – α be the proportion of the process that can not be parallelized. –P – number of processors –S – System speedup Amdhals law: S = 1 / (α + (1- α ) / P ) Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 10

11. Cluster types High availability –Active-Active –Active-Passive –Heart beat Load Balancing Cluster –Round robin (weighted/non-weighted) –System status aware (session, cpu load, etc) Compute cluster –Queuing system (condor, hadoop, open-pbs, LSF, etc.) –Single system image (ScaleMP, SSI, Mosix, nomad,etc.) Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 11

12. Batch to On-Line scale gLite & Globus Dedicated resources PBS Torque Utility computing (Condor) hadoop Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 12

13. Key Cloud Services Attributes Off-Site, Thirds-party provider Access via Internet Minimal/no IT skills required to “implement” Provisioning - self-service requesting; near real-time deployment; dynamic & fine-grained scaling Fine-grained usage-based pricing model UI - browser and successors Web services APIs as System Interface Shared resources/common versions Source: IDC, Sep 2008

14. What is “Grid” Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 14

15. What is Grid Computing ? Definition is not widely agreed Foster & Kesselman: Computing resources are not administered centrally. Open standards are used. Non-trivial quality of service is achieved. Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 15

16. Other definitions "the technology that enables resource virtualization, on-demand provisioning, and service (resource) sharing between organizations." (Plaszczak/Wellner) "a type of parallel and distributed system that enables the sharing, selection, and aggregation of geographically distributed autonomous resources dynamically at runtime depending on their availability, capability, performance, cost, and users' quality-of- service requirements“ (Buyya )autonomous "a service for sharing computer power and data storage capacity over the Internet." (CERN)Internet Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 16

17. SOA & Web services Decompose processing into services Each service works independently Main components: –Universal Description, Discovery and Integration –Simple Object Access Protocol –Web Services Description Language W3C standard Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 17

18. The Grid Metaphor Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 18

19. Virtual Organization What’s a VO? –People in different organisations seeking to cooperate and share resources across their organisational boundaries Why establish a Grid? –Share data –Pool computers –Collaborate The initial vision: “The Grid” The present reality: Many “grids” Each grid is an infrastructure enabling one or more “virtual organisations” to share computing resources Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 19 Institute A VO1 Institute CInstitute BInstitute DInstitute E VO2 Institute F

20. Stand alone computer Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 20 Application Operating system Hardware

21. Stand alone computer Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 21 Application Network stack Operating system Hardware

22. Stand alone computer Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 22 Application Grid Middleware Network stack Operating system Hardware

23. Grid middleware Middleware, is an interfaces between resources and the applications –User/Program Interface –Resource management –Connectivity –Information services –Collaboration Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 23

24. Middleware components – The batch approach Eddie Aronovich – Operating System course (TAU CS, Jan 2009) 24 InformationService SE & CE info Publish Input “sandbox” + Broker Info ReplicaCatalogue DataSets info Logging & Book-keeping Author. &Authen. StorageElement ComputingElement Output “sandbox” ResourceBroker Job Status Job Submit Event Job Query Job Status Input “sandbox” Output “sandbox” “User interface”

25. UI Network Server Job Contr. Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node Characts. & status

26. UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node CE characts & status SE characts & status submitted Job Status UI: allows users to access the functionalities of the WMS (via command line, GUI, C++ and Java APIs)

27. UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node CE characts & status SE characts & status edg-job-submit myjob.jdl Myjob.jdl JobType = “Normal”; Executable = "$(CMS)/exe/sum.exe"; InputSandbox = {"/home/user/WP1testC","/home/file*”, "/home/user/DATA/*"}; OutputSandbox = {“sim.err”, “test.out”, “sim.log"}; Requirements = other. GlueHostOperatingSystemName == “linux" && other. GlueHostOperatingSystemRelease == "Red Hat 7.3“ && other.GlueCEPolicyMaxCPUTime > 10000; Rank = other.GlueCEStateFreeCPUs; submitted Job Statu s Job Description Language (JDL) to specify job characteristics and requirements

28. UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node CE characts & status SE characts & status RB storage Input Sandbox files Job waiting submitted Job Status NS: network daemon responsible for accepting incoming requests

29. Job submission UI Network Server Job Contr. - CondorG Replica Location Server Inform. Service Computing Element Storage Element RB node CE characts & status SE characts & status RB storage waiting submitted Job Status WM: acts to satisfy the request Job Workload manager

30. Job submission UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node CE characts & status SE characts & status RB storage waiting submitted Job Status Match- Maker/ Broker Where must this job be executed ?

31. Job submission UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node CE characts & status SE characts & status RB storage waiting submitted Job Status Match- Maker/ Broker Matchmaker: responsible to find the “best” CE for a job

32. Job submission UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node CE characts & status SE characts & status RB storage waiting submitted Job Status Match- Maker/ Broker Where are (which SEs) the needed data ? What is the status of the Grid ?

33. Job submission UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node CE characts & status SE characts & status RB storage waiting submitted Job Status Match- Maker/ Broker CE choice

34. Job submission UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node CE characts & status SE characts & status RB storage waiting submitted Job Status Job Adapter Job Adapter: responsible for the final “touches” to the job before performing submission (e.g. creation of wrapper script, PFN, etc.)

35. Job submission UI Network Server Job Contr. Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node CE characts & status SE characts & status RB storage Job Status Job Controller: responsible for the actual job management operations (done via CondorG) Job submitted waiting ready

36. Job submission UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node CE characts & status SE characts & status RB storage Job Status Job submitted waiting ready scheduled

37. “Compute element” – reminder! Homogeneous set of worker nodes Grid gate node Local resource management system: Condor / PBS / LSF master Globus gatekeeper Job request Info system Logging gridmapfile I.S. Logging

38. Job submission UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node RB storage Job Status submitted waiting ready scheduled running “Grid enabled” data transfers/ accesses Job Input Sandbox files

39. Job submission UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node RB storage Job Status Output Sandbox files submitted waiting ready scheduled running done

40. Job submission UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node RB storage Job Status submitted waiting ready scheduled running done edg-job-get-output

41. Job submission UI Network Server Job Contr. - CondorG Workload Manager Replica Location Server Inform. Service Computing Element Storage Element RB node RB storage Job Status Output Sandbox files submitted waiting ready scheduled running done cleared

42. Job monitoring UI Log Monitor Logging & Bookkeeping Network Server Job Contr. - CondorG Workload Manager Computing Element RB node LM: parses CondorG log file (where CondorG logs info about jobs) and notifies LB LB: receives and stores job events; processes corresponding job status Log of job events edg-job-status edg-job-get-logging-info Job status

43. EGEE08 Istanbul, Turkey www.eu-egi.eu 43 Grids in Europe www.eu-egi.eu Prof. Dieter KRANZLMUELLER, EGEE 08