2. Denis Caromel 1

3. 2 www.devoxx.com

4. Denis Caromel 3 Clouds

5. Denis Caromel 4 www.devoxx.com Franca Perrina (Italy) Florin Alexandru Bratu (Romania) Denis Caromel (France, Nice) 3 Speakers/Demos

6. Denis Caromel 5 3 Strong Faiths 1.Parallel Computing will make it mainstream with Java 1.A need for a unified Parallel Abstraction: Multi-Core + Distributed 3. Java will make it possible to connect Enterprise Grids and Clouds

7. Denis Caromel 6 Agenda Effective SOA + GRIDs with 1.Background: INRIA, OASIS, ActiveEon 2.Programming, Optimizing 3. Scheduling 4. SOA: WS, WSDL, BPEL (Franca Perrina) 5. Enterprise Grids, Clouds: Amazon EC2 6. Java EE EJB (Florin Alexandru Bratu)

8. Denis Caromel 7 1. Background

9. Denis Caromel 8 OASIS Team & INRIA Computer Science and Control 8 Centers all over France Workforce: 3 800 Strong in standardization committees: – IETF, W3C, ETSI, … Strong Industrial Partnerships Foster company foundation: 90 startups so far - Ilog (Nasdaq, Euronext) - … - ActiveEon A joint team between: INRIA, Nice Univ. CNRS Now about 40 persons 2004: First ProActive User Group 2008: 5 th one, Acad./Indus. User Presentations ProActive 4.0.1: Distributed and Parallel: From Multi-cores to Enterprise GRIDs

10. Denis Caromel 9 Startup Company Born of INRIA Co-developing, Providing support for Open Source ProActive Parallel SuiteProActive Parallel Suite Worldwide Customers (EU, Boston USA, etc.)

11. Denis Caromel 10 2. Programming Optimizing Parallel Acceleration Toolkit in Java: Parallelism: Multi-Core+Distributed Used in production by industry

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14. Denis Caromel 13 ProActive Parallel Suite

15. Denis Caromel 14 ProActive Parallel Suite

16. Denis Caromel 15 Distributed and Parallel Active Objects

17. Denis Caromel 16 A ProActive : Active objects Proxy Java Object A ag = newActive (“A”, […], VirtualNode) V v1 = ag.foo (param); V v2 = ag.bar (param);... v1.bar(); //Wait-By-Necessity V Wait-By-Necessity is a Dataflow Synchronization JVM A Active Object Future Object Request Req. Queue Thread v1 v2 ag WBN!

18. Denis Caromel 17 Standard system at Runtime: No Sharing NoC: Network On Chip Proofs of Determinism

19. Denis Caromel 18 TYPED ASYNCHRONOUS GROUPS

20. Denis Caromel 19 A Creating AO and Groups Typed Group Java or Active Object A ag = newActiveGroup (“A”, […], VirtualNode) V v = ag.foo(param);... v.bar(); //Wait-by-necessity V Group, Type, and Asynchrony are crucial for Composition JVM

21. Denis Caromel 20 Broadcast and Scatter JVM ag cg ag.bar(cg); // broadcast cg ProActive.setScatterGroup(cg) ; ag.bar(cg); // scatter cg c1 c2 c3 c1 c2 c3 c1 c2 c3 c1 c2 c3 c1 c2 c3 c1 c2 c3 s c1 c2 c3 s Broadcast is the default behavior Use a group as parameter, Scattered depends on rankings

22. Denis Caromel 21 Optimizing

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25. Denis Caromel 24 IC2D

26. Denis Caromel 25 ChartIt

27. Denis Caromel 26 Pies for Analysis and Optimization

28. Denis Caromel 27 Video 1: IC2D Optimizing Monitoring, Debugging, Optimizing

29. Denis Caromel 28 3. Scheduling

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31. Denis Caromel 30 Scheduler and Resource Manager: User Interface

32. Denis Caromel 31 Scheduler: User Interface

33. Denis Caromel 32 Video 2: Scheduler, Resource Manager

34. Denis Caromel 33 4. SOA Integration: Web Services, BPEL Workflow Franca Perrina OASIS Team - INRIA

35. Denis Caromel 34 Active Objects as Web Services Why ? Access Active Objects from any language How ? HTTP Server SOAP Engine (Axis) Usage: ProActive.exposeAsWebService(); ProActive.unExposeAsWebService(); JVM Web Service Client Web Services

36. Denis Caromel 35 ProActive + Services + Workflows Principles: 3 kinds of Parallel Services 3. Domain Specific Parallel Services (e.g. Monte Carlo Pricing) 2. Typical Parallel Computing Services (Parameter Sweeping, D&C, …) 1.Basic Job Scheduling Services (parallel execution on the Grid)

37. Denis Caromel 36 3 kinds of Parallel Services 3. Domain Specific Parallel Services: providing business functionalities executed in parallel 2. Parallelization services: typical parallel computing patterns (Parameter Sweeping, D&C, …) 1. Job Scheduling service: Schedule and Run jobs in parallel on the Grid. Parallel Services Operational Services … 1. Job Scheduling Service 2. Parameter Sweeping Service 2. Divide & Conquer Service Other Operational Service … Domain Specific Parallel Service … Other Basic Service High level Business ProcessGrid 3. Domain Specific Parallel Service

38. Denis Caromel 37 A sample pattern: Parameter Sweeping I1 I2 … In O1 O2 … On Exec Logic parameter sweeping I1 I2 … In O1 O2 … On Parameter Sweeping Service, customized with an Exec logic X Param Sweeping Service Process using parameter sweeping service … All the running instances of the Exec logic X are executed on the grid as a whole PA Scheduler & PA Resource Manager

39. Denis Caromel 38 Demo SOA Integration: Web Services, BPEL Workflow

40. Denis Caromel 39 5. Enterprise Grids, Clouds: Standards & Amazon EC2

41. Denis Caromel 40 Deploy on Various Kinds of Infrastructures Internet Clusters Parallel Machine Large Equipment Internet Job management for embarrassingly parallel application (e.g. SETI) Internet Servlets EJBsDatabases

42. Denis Caromel 41 GCM Fractal Standardization Fractal Based Grid Component Model Overall, the standardization is supported by industrials: BT, FT-Orange, Nokia-Siemens, Telefonica, NEC, Alcatel-Lucent, Huawei …

43. Denis Caromel 42 Protocols and Scheduler in GCM Deployment Standard Protocols: Rsh, ssh Oarsh, Gsissh Scheduler, and Grids: GroupSSH, GroupRSH, GroupOARSH ARC (NorduGrid), CGSP China Grid, EEGE gLITE, Fura/InnerGrid (GridSystem Inc.) GLOBUS, GridBus IBM Load Leveler, LSF, Microsoft CCS (Windows HPC Server 2008) Sun Grid Engine, OAR, PBS / Torque, PRUN Soon available in stable release: Java EE Amazon EC2

44. Denis Caromel 43 6. J2EE Integration Florin Alexandru Bratu OASIS Team - INRIA

45. Denis Caromel 44 J2EE Integration with Parallelism + Grids/Clouds Performing Grid & Cloud Computing From & In an Application Servers 1.Delegating heavy computations outsides J2EE Applications 2.Using Deployed J2EE Nodes as Computational Resources

46. Denis Caromel 45 ProActive – J2EE Integration (1) 1.Delegating heavy computations outsides J2EE Applications

47. Denis Caromel 46 ProActive – J2EE Integration (2) 2. Using Deployed J2EE Nodes as Computational Resources Objective Being able to deploy active objects inside the JVMs of application servers Implementation Based on a Sun standard – Java Connector Architecture JSR112 Deployment module: resource adapter (RAR)‏ Works with all J2EE-compliant Application Servers

48. Integration(2)‏

49. Denis Caromel 48 Grids & Clouds: Amazon EC2 Deployment

50. Denis Caromel 49 Big Picture + Clouds

51. Denis Caromel 50 Clouds: ProActive Amazon EC2 Deployment Principles & Achievements: ProActive Amazon Images (AMI) on EC2 So far up to 128 EC2 Instances (Indeed the maximum on the EC2 platform, … ready to try 4 000 AMI) Seamless Deployment: no application change, no scripting, no pain Open the road to : In house Enterprise Cluster and Grid + Scale out on EC2

52. Denis Caromel 51 ProActive Deployment on Amazon EC2 Video

53. Denis Caromel 52 On Going AGOS Grid Architecture for SOA

54. Denis Caromel 53 AGOS Grid Architecture for SOA AGOS Solutions Building a Platform for Agile SOA with Grid In Open Source with Professional Support

55. Denis Caromel 54 AGOS Generic Architecture for SOA with GRIDs OS, HW OS VirtualizationGrid Utility interface ESB Enterprise Service Bus SCA Service Component Architecture Resource Manager Task & Services Scheduling Parallel Programming SPMD, workflow Agent, Master/Worker Fork and Join In memory db cache (JSR / JPI / javaspaces) SOA BPEL Exec Repository, Registry, Orchestration SOA Monitoring Reporting, Notifications, alarms Business Intelligence BI Monitoring SLM Service Level Management

56. Denis Caromel 55 Summary

57. Denis Caromel 56 Conclusion: Effective SOA + GRIDs in Java with An Acceleration Toolkit : Concurrency+Parallelism Multi-Core+Distributed Grid & SOA: J2EE, WS, BEPL, EG + Amazon EC2

58. Q&A

59. Denis Caromel 58 www.devoxx.com