1 Denis Caromel 2 Denis Caromel www devoxx

1 Denis Caromel

2 Denis Caromel www. devoxx. com

s d u o l C 3 Denis Caromel

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

3 Strong Faiths 1. Parallel Computing will make it 2. mainstream with Java 3. A need for a unified Parallel Abstraction: 4. Multi-Core + Distributed 5. 3. Java will make it possible to connect 6. Enterprise Grids and Clouds 5 Denis Caromel

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

1. Background 7 Denis Caromel

OASIS Team & INRIA A joint team between: INRIA, Nice Univ. CNRS Computer Science and Control • Now about 40 persons • 8 Centers all over France • 2004: First Pro. Active User Group • Workforce: 3 800 • 2008: 5 th one, Acad. /Indus. User Presentations • Pro. Active 4. 0. 1: Distributed and Parallel: • Strong in standardization committees: – IETF, W 3 C, ETSI, … From Multi-cores to Enterprise GRIDs • Strong Industrial Partnerships • Foster company foundation: 90 startups so far - Ilog (Nasdaq, Euronext) -… - Active. Eon 8 Denis Caromel

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

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

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Pro. Active Parallel Suite 13 Denis Caromel

Pro. Active Parallel Suite 14 Denis Caromel

Distributed and Parallel Active Objects 15 Denis Caromel 15

Pro. Active : Active objects JVM A ag = new. Active (“A”, […], Virtual. Node) V v 1 = ag. foo (param); V v 2 = ag. bar (param); . . . v 1. bar(); //Wait-By-Necessity JVM A v 2 v 1 ag A WBN! V 16 Java Object Active Object Future Object Proxy Denis Caromel Req. Queue Request Thread Wait-By-Necessity is a Dataflow Synchronization 16

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

TYPED ASYNCHRONOUS GROUPS 18 Denis Caromel 18

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

Broadcast and Scatter Broadcast is the default behavior Use a group as parameter, Scattered depends on rankings cg ag JVM s c 1 c 2 c 3 c 3 JVM ag. bar(cg); // broadcast cg Pro. Active. set. Scatter. Group(cg); ag. bar(cg); // scatter cg JVM 20 Denis Caromel 20

Optimizing 21 Denis Caromel 21

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IC 2 D 24 Denis Caromel

Chart. It 25 Denis Caromel

Pies for Analysis and Optimization 26 Denis Caromel

Video 1: IC 2 D Optimizing Monitoring, Debugging, Optimizing 27 Denis Caromel

3. Scheduling 28 Denis Caromel 28

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Scheduler and Resource Manager: User Interface 30 Denis Caromel

Scheduler: User Interface 31 Denis Caromel

Video 2: Scheduler, Resource Manager 32 Denis Caromel

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

Active Objects as Web Services Why ? Access Active Objects from any language How ? HTTP Server SOAP Engine (Axis) Usage: JVM Web Services Pro. Active. expose. As. Web. Service(); Pro. Active. un. Expose. As. Web. Service(); 34 Denis Caromel Web Service Client

Pro. Active + 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 2. (parallel execution on the Grid) 35 Denis Caromel

3 kinds of Parallel Services High level Business Process Domain Specific Parallel Service 3. Domain Specific Parallel Service 1. Job Scheduling Service … 2. Parameter Sweeping Service 2. Divide & Conquer Service Parallel Services Grid 36 Denis Caromel … Other Operational Service Other Basic Service … Operational 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.

A sample pattern: Parameter Sweeping Process using parameter sweeping service I 1 I 2 … In parameter sweeping I 1 I 2 O 1 O 2 … In … On Param Sweeping Service O 1 O 2 … On All the running instances of the Exec logic X are executed on the grid as a whole Parameter Sweeping Service, customized with an Exec logic X Exec Logic PA Scheduler & PA Resource Manager … 37 Denis Caromel

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

5. Enterprise Grids, Clouds: Standards & Amazon EC 2 39 Denis Caromel 39

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

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 … 41 Denis Caromel

Protocols and Scheduler in GCM Deployment Standard Protocols: Rsh, ssh Oarsh, Gsissh Scheduler, and Grids: Group. SSH, Group. RSH, Group. OARSH ARC (Nordu. Grid), CGSP China Grid, EEGE g. LITE, Fura/Inner. Grid (Grid. System Inc. ) GLOBUS, Grid. Bus 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 EC 2 42 Denis Caromel

6. J 2 EE Integration Florin Alexandru Bratu OASIS Team - INRIA 43 Denis Caromel

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

Pro. Active – J 2 EE Integration (1) 1. Delegating heavy computations outsides J 2 EE Applications 45 Denis Caromel

Pro. Active – J 2 EE Integration (2) 2. Using Deployed J 2 EE 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 JSR 112 Deployment module: resource adapter (RAR) Works with all J 2 EE-compliant Application Servers 46 Denis Caromel

Integration(2)

Grids & Clouds: Amazon EC 2 Deployment 48 Denis Caromel

Big Picture + Clouds 49 Denis Caromel

Clouds: Pro. Active Amazon EC 2 Deployment Principles & Achievements: Pro. Active Amazon Images (AMI) on EC 2 So far up to 128 EC 2 Instances (Indeed the maximum on the EC 2 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 EC 2 50 Denis Caromel

Pro. Active Deployment on Amazon EC 2 Video 51 Denis Caromel

On Going AGOS Grid Architecture for SOA 52 Denis Caromel

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

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

Summary 55 Denis Caromel

Conclusion: Effective SOA + GRIDs in Java with An Acceleration Toolkit : Concurrency+Parallelism Multi-Core+Distributed 56 Denis Caromel Grid & SOA: J 2 EE, WS, BEPL, EG + Amazon EC 2

Q&A

58 Denis Caromel www. devoxx. com