1. Mythes et réalités du Grid Computing Presented by: Gilles Tourpe Directeur Technique EMEA

2. Mythes

3. © Platform Computing Inc. 2004 3 Grid is …

4. © Platform Computing Inc. 2004 4 Grid is … SLA Service wait time Run time per service

5. © Platform Computing Inc. 2004 5 Grid is … If you ask me to give you a very clear and simplistic definition of grid I would say grid computing is distributed computing involving multiple sites to integrate and support applications and support collaboration.

6. © Platform Computing Inc. 2004 6 Vision: A single (virtual) computer to run your business How? By delivering products that support all types of workloads, applications, standards, resources and computing environments with global enterprise-level scalability and with a common, virtualized infrastructure How to complete this vision ?

7. © Platform Computing Inc. 2004 7 Data Demand Compute Demand Retail Banking – Data Mining (Fast Interconnect, Data aware scheduling) Exotics – Risk Management (Load balancing) Front Office - Pricing & Hedging (Low latency task distribution) Grid Sweetspot Credit Risk (Fast Interconnect - InfiniBand, Scalable I/O storage Data-aware scheduling) Crossing the Finance Application Chasm

8. © Platform Computing Inc. 2004 8 Differences between Grid Computing and Distributed Computing Power without control is nothing. Grid power of 1000 machines needs to be managed and steered towards business objectives in a systematic, deterministic and predictable fashion Grid Computing = Distributed Computing + resource and workload management in terms of:  Resource virtualization  Resource ownership and sharing  Dynamic resource allocation  Resource monitoring, control, failover, and troubleshooting  Guaranteed SLA (Service Level Agreement) management  Workload scheduling and prioritization  Load balance  High reliability and availability, robustness, resilience, and failover  Performance and scalability in a large grid  Workload execution monitoring, control, and troubleshooting  Resource and workload usage collection, reporting, and accounting

9. © Platform Computing Inc. 2004 9 What are the supportive concepts & technologies A Virtualized IT environment Grid Virtualization Strengths Pool (Virtualize) heterogeneous resources Allocate and manage resources based on Policy Server Virtualization Strengths Partition server into virtual servers that provide a secure “container” for applications. Data virtualization Strenghts Data access transparency.NET Application Virtualization Strengths Rapid development Improved operation & maintanability Agile architecture

10. © Platform Computing Inc. 2004 10 Solaris Windows zLinux Linux AIX Windows Oracle DB2 SQL Application BApplication A Application C Legacy Stovepipes Avg. Utilization Rate 40% Avg. Utilization Rate 40% Avg. Utilizatio n Rate 2-5% Avg. Utilizatio n Rate 2-5% Avg. Utilization Rate 10% Avg. Utilization Rate 10% Avg. Utilization Rate 10% Avg. Utilization Rate 10% Avg. Utilization Rate 52% Avg. Utilization Rate 52% Avg. Utilization Rate 60% Avg. Utilization Rate 60% Avg. Utilization Rate 10% Avg. Utilization Rate 10% 15 Hours 8 Hours 2 Hours Grid Computing is about virtualizing and sharing resources Decoupling applications from infrastructure

11. © Platform Computing Inc. 2004 11 Grid Computing is about virtualizing and sharing resources Decoupling applications from infrastructure Solaris Windows zLinux Linux AIX Windows Results returned and integrated into application(s) Scheduler distributes application workload(s) to CPUs Oracle DB2 SQL Application BApplication A Application C

12. © Platform Computing Inc. 2004 12 Scheduler distributes application workload(s) to CPUs Grid Computing is about virtualizing and sharing resources Decoupling applications from infrastructure Solaris Windows zLinux Linux AIX Windows Results returned and integrated into application(s) Scheduler distributes application workload(s) to CPUs Oracle DB2 SQL Application BApplication A Application C Collaboration & Resiliency

13. © Platform Computing Inc. 2004 13 Enterprise Grid Context Workload Managers Applications Users Enterprise Resources BI.NETDB’sERPCRMVM’s Application Managers Batch Process Flow SOAParallel HPCMDAEDACAERisk “Acceleration” Applications Business Applications Grid Management Console Windows 2003 Server Resource Pool

14. © Platform Computing Inc. 2004 14 Is this a Myth ? Shared application interface, scheduling system, and virtual resource pool Enables sharing and reuse of knowledge, data, resources, and analytics engines Shared resource pool is dynamically partitioned into “virtual clusters” Application interface and scheduling system are now commercially supported, fully documented software Low-cost off-the-shelf hardware replaces expensive SMP boxes Multi-asset models can now be run by one user, able to access any analytics engines and resources needed, governed by priority-driven policies

15. © Platform Computing Inc. 2004 15 Policy Evolution – Supporting the spectrum of ownership vs.sharing Model 1: Limits  Put hard limits around each consumer  Virtualize the resources instead of dedicating fixed resources  Guaranteed capacity in event of failures AB C AB C A B Silo Model Enterprise Sharing Model Utility Computing Model C Model 2: Borrow/Lend  Each consumer has “owned” capacity  Each consumer can specify lend and borrowing limits around that owned capacity Model 3:Fairshare  Consumer has % of capacity at each level relative to others  “Owned” capacity is 0 for consumer  Capacity allocated based on need and constrained by shares Model 4: Economic  Consumers specify budget $  Resource usage has cost ($/cpu-hr, $KB/hr)  System optimizes budget allocations & resource usage driven by application SLA (determined in WLM) 100% ownership of resources by Consumers Capped SLA guarantees when peak reached - Some minimum ownership of resources - Ability to share from pool or others - 0% ownership of resources by consumer. - All owned by service provider (IB - Consumer Pay for usage only - SLAs guaranteed in exchange for resource ownership

16. Réalités

17. © Platform Computing Inc. 2004 17 Platform Symphony – Road to Grid and Beyond Today Start Small (1 or 2 apps) Grow the grid and measure ROI Tomorrow As you grow, throw more apps or complex jobs at the grid Platform Symphony is designed to grow with you Supporting all workload and enterprise-class Scalability Ultimately future proofing your IT investments via a heterogeneous, standards-based, single, common infrastructure solution - The Virtual Execution Machine (VEM)

18. © Platform Computing Inc. 2004 18 Today FSI Policy Evolution – Supporting the spectrum of ownership vs.sharing Model 1: Limits  Put hard limits around each consumer  Virtualize the resources instead of dedicating fixed resources  Guaranteed capacity in event of failures AB C AB C A B Silo Model Enterprise Sharing Model Utility Computing Model C Model 2: Borrow/Lend  Each consumer has “owned” capacity  Each consumer can specify lend and borrowing limits around that owned capacity Model 3:Fairshare  Consumer has % of capacity at each level relative to others  “Owned” capacity is 0 for consumer  Capacity allocated based on need and constrained by shares Model 4: Economic  Consumers specify budget $  Resource usage has cost ($/cpu-hr, $KB/hr)  System optimizes budget allocations & resource usage driven by application SLA (determined in WLM) 100% ownership of resources by Consumers Capped SLA guarantees when peak reached - Some minimum ownership of resources - Ability to share from pool or others - 0% ownership of resources by consumer. - All owned by service provider (IB - Consumer Pay for usage only - SLAs guaranteed in exchange for resource ownership Today EDA,IM

19. © Platform Computing Inc. 2004 19 Summit VaR Cluster 1 48 Blades Sym 2.1.3 Summit VaR Cluster 2 48 Blades Summit VaR Cluster 1 44 CPUs Lognes Sym 2.1.3 Summit VaR Symphony 2.1.3 Sophis Pricing Symphony 2.1.3 Sophis Portfolio Symphony 2.1.3 Compute nodes Windows 2000 Compute nodes Windows 2000 Site CSite BSite A Customer A Architecture

20. © Platform Computing Inc. 2004 20 Summit VaR Sym 2.1.3 Hybrids Symphony 2.1.3 Compute nodes Windows 2003 Site DSite CSite B Customer B Architecture Hybrids Symphony 2.1.3 Compute nodes Windows 2003 UAT Production Summit VaR Sym 2.1.3 Summit VaR Sym 2.1.3 Summit VaR Sym 2.1.3 Site A WLM

21. © Platform Computing Inc. 2004 21 Customer B – Application focus Market Data Work Web Sphere Job Server Job Arrives, contains list of deals Excel Job Server decomposes deals into tasks Excel gets market data After new task arrives Symphony Job Server is Symphony Client Tasks sent to Symphony Symphony starts ExcelService which starts Excel,. Each task contains the deal string used for the calculation. ExcelService calls the relevant Excel method to start the computation. Excel Results returned to client Tasks distributed to available compute hosts and results returned to Symphony

22. © Platform Computing Inc. 2004 22 Summit VaR BATCH Partition Summit VaR SUMMIT_VaR_H Sophis Pricing SOPHIS_PRICING Sophis Portfolio SOPHIS_PORTFOLIO Compute nodes Application Client Platform Symphony 2.2.1 Brokerage of ressources 1 Dedicated Service Partition per Application SLA per application with Lending and Borrowing ENABLED Contingency Site Customer A target (End of June) Windows machines resource pool

23. © Platform Computing Inc. 2004 23 Customer C Architecture Project A Windows 2000/2003 Compute Nodes Exotic Derivatives Pricers C++ 100s CPUs actives today 1000s CPUs by Q1CY2005 Project B Windows 2000/2003 Compute Nodes.NET 100 CPUs actives Project C Windows 2000/2003 Compute Nodes.NET 600-800 CPUs by Q1CY2005 Compute farms

24. © Platform Computing Inc. 2004 24 Customer C – Desktop Support SSM Mapping FS FS WLM Mapping FS Compute Node Dedicated Workstation Running Symphony Mapping FS DR Site with dedicated positions

25. © Platform Computing Inc. 2004 25 Customer C Grid A Grid Management Console Platform Policy Engine and Scheduler Shared Storage... VMware Desktop Farm In Disaster Recovery Platform Grid Virtual Machines... Grid B Grid C Triggered actions Compute farms

26. © Platform Computing Inc. 2004 26 Customer C - Step4 SSM Mapping FS FS WLM Mapping FS Compute Node Dedicated Workstation Running Symphony NO FS Dependency CORE Building workstations

27. © Platform Computing Inc. 2004 27 Customer C – Final Step Pool Compute farm ABC Disaster Recovery Desktop Opportunistic CPU stealing

28. © Platform Computing Inc. 2004 28 JPMorgan Chase Silos of resources and applications supporting different risk management apps No sharing or collaboration of knowledge, data, resources, or analytics engines Over-provisioning of hardware for peak in each silo Unstable and poorly documented home-grown distribution software and application interfaces Expensive SMP servers needed to support spikes in workload Multi-asset (cross-silo) models had to be run and assembled manually

29. © Platform Computing Inc. 2004 29 Today’s situation !

30. Key steps to implement an enterprise grid ?

31. © Platform Computing Inc. 2004 31 Four Stages of Enterprise Grid LEVEL TWO Connected, Multi-Domains There is an agreement between domains to share compute resources according to owner controlled policies. Charge-back manager tracks usage and allocates costs LEVEL ONE Single or Isolated Domains Each ”Domain” – project, work group or LoB, etc. controls – its own processes, data and compute resources within an enterprise, behind the firewall. LEVEL THREE Cross-enterprise, Compute Backbone” Each project, work group or LoB controls its own processes, data and compute resources, behind the firewall Compute resources are share according to owner controlled policies For maximum speed and efficiency all domains are linked together Sophisticated charge-back manager tracks usage and allocates costs. Value TIME

32. © Platform Computing Inc. 2004 32 LEVEL FOUR Internal Utility/Enterprise Utility Domains own no or almost compute resources of their own but pay for the use of any that they require. IT is charged with buying sufficient compute resources to meet demand from all parties. Domains establish priority requirements and are charged only for actual use. Sophisticated charge-back manager tracks usage and allocates costs. Sophisticated modeling analysis predicts volume/time requirements Value Time Four Stages of Enterprise Grid

33. © Platform Computing Inc. 2004 33 Partner Grid - beyond the firewall Value Time LEVEL FIVE Inter-Enterprise Each project, work group or LoB controls its own processes, data and compute resources within an enterprise, behind the firewall and interacts with other base “domains” But, there is an agreement to share computer resources with partners in other enterprises beyond the firewall.

34. © Platform Computing Inc. 2004 34 LEVEL SIX Utility Grid Computing Business owners own little or no hardware. Buy from utility on an as needed basis. Utility serves many customers; efficiencies drive down costs and drive up scale Utility Grid

35. Merci !