1. IBM Solutions for Grid Computing

2. I. IT view on “GRID” II. IBM and GRID III. IBM Storage and GRID Index …

3. IT view on GRID

4. Middleware Storage Directory and Security Servers Web Presentation Servers Web Application Servers Data Servers Transaction Servers Customers Business Partners Suppliers Employees Quality of Service Network Current IT Environment Distributed, Heterogeneous, Complex

5. Middleware Storage Directory and Security Servers Web Presentation Servers Web Application Servers Data Servers Transaction Servers Customers Business Partners Suppliers Employees Quality of Service Network Current IT Environment Distributed, Heterogeneous, Complex Complexity, TCO Tech. Cost, Efficiency

6. Pre-Internet “System” Storage Data Applications ProcessingI/OOperating System GRID Computing

7. Storage Applications ProcessingOperating System One virtual computing platform, 'limitless' global resources GRID Computing

8. Distributed Computing Over the Internet Using Open Standards  Virtual, collaborative organizations sharing applications and data in an open heterogeneous environment  A vast aggregation of geographically dispersed computing resources Virtual Servers, Storage and Instruments Grid Middleware Distributed Physical Servers and Storage GRID Computing

9. 4 Models, Unique Value Propositions Platform, Entropia, United Devices Increased Processing “Aggregate processing power from a distributed collection of heterogeneous systems” Partners: Customer Values:  Productivity  Flexibility  Resource use  Reliability/ Availability  Complexity  Total cost of ownership Decreased Uses of GRID Technology

10. 4 Models, Unique Value Propositions Increased Avaki, Platform Data “Secure access and sharing of distributed data & information in a collaborative fashion” Partners: Customer Values:  Productivity  Flexibility  Resource use  Reliability/ Availability  Complexity  Total cost of ownership Decreased Platform, Entropia, United Devices Processing “Aggregate processing power from a distributed collection of heterogeneous systems” Partners: Uses of GRID Technology

11. 4 Models, Unique Value Propositions Increased Platform Resiliency “Improve the quality of service of distributed systems, despite unplanned events” Partners: Customer Values:  Productivity  Flexibility  Resource use  Reliability/ Availability  Complexity  Total cost of ownership Decreased Platform, Entropia, United Devices Processing “Aggregate processing power from a distributed collection of heterogeneous systems” Partners: Avaki, Platform Data “Secure access and sharing of distributed data & information in a collaborative fashion” Partners: Uses of GRID Technology

12. 4 Models, Unique Value Propositions Increased Platform, Entropia, United Devices, Avaki On Demand “Access data & processing capabilities in a utility-like fashion…….. Make vs. Buy” Partners: Client Values:  Resource use  Flexibility  Productivity  Reliability/ Availability  Complexity  Total cost of ownership Decreased Platform Resiliency “Improve the quality of service of distributed systems, despite unplanned events” Partners: Platform, Entropia, United Devices Processing “Aggregate processing power from a distributed collection of heterogeneous systems” Partners: Avaki, Platform Data “Secure access and sharing of distributed data & information in a collaborative fashion” Partners: Uses of GRID Technology

13. ...Over the Internet Grid Infrastructure  UK National Grid  Netherlands National Grid  The TeraGrid  University of Pennsylvania  North Carolina BioGrid  Department of Energy Science Grid e-Science Grids Early Adopters

14. Heterogeneous Systems:  National Center for Supercomputing Applications  San Diego Supercomputing Center  Argonne National Laboratory  California Institute of Technology 13.6 trillion floating point operations per second 600 terabytes of data 40 gigabits per second Accessible to thousands of scientists working on advanced research The TeraGrid

15. IBM and GRID

16. Grid intersects several key IBM strategies/initiatives Deep Computing eLiza eSourcing / eUtilities Life Science Linux Cluster IBM and GRID

17. Grid Computing...over the Internet Simple Protocol Stack; Tools-assisted, people-managed Richer Protocol Stack; Self- managed, policy driven Scientific Computing eLiza Towards Commercial Computing Self-managing Components Self-managing Infrastructures Future Internet- Based Computing eLiza and GRID Relationship

18. Delivery of standardized processes, applications, and infrastructure over the network as a service on a pay- as-you-go basis Business Functions: CRM, eCommerce, Supply Chain,... IT Functions: Security, Web Hosting, Storage Services, Systems Management,... $4B to add 50 hosting centers worldwide to serve as e- Sourcing hubs First step in the utility model Recently announced IBM Initiative eSourcing

19. Information Power Grid Ubiquitous access Dependable Hides complexity Hosting Hubs connected over a Grid Longer Term … Utility Computing

20. IBM Storage And GRID

21. Storage Virtualisation definition: Separation of the logical view of storage from its physical implementation, enabling physical changes to be made without changing the logical view. GROWTH value : Ù Single Point of Mgmt Ù True File Sharing Flexible Infrastructure

22. n In the network n In the data path n Move intelligence of controller into network n Enterprise reliability Application File System DBMS Device Driver JBODs RAID Ctller Intelligent Storage Ctller SAN Installable File System JBODs RAID Ctller Application File System DBMS Device Driver Virtualization Engine Common File System - Storage Tank Hardware Element Management Tivoli SAN Management Storage Network Block Aggregation : IBM Plan

23. SAN Servers are mapped to specific physical disks i.e., "physical mapping" SANs Today Storage Network Servers are mapped to a virtual disk i.e., "logical mapping" Virtualization Layer Block Virtualization Block Level Virtualization

24. Storage Network Node Managed Disks Virtual LUNs Node Each node is an xSeries eServer with up to 4GB Read/Write Cache, mirrored across the pair Redundant, modular, scalable, complete solution IBM ’ s Virtualization Engine

25. Storage Network Node Managed Disks Virtual LUNs Node Virtual volumes are shared between a pair of nodes Redundant, modular, scalable, complete solution Engine IBM ’ s Virtualization Engine

26. Storage Network Node Managed Disks Virtual LUNs Node The pool of managed disks is controlled by a cluster of paired nodes (up to 4 pairs initially, scaling higher in future) Redundant, modular, scalable, complete solution IBM ’ s Virtualization Engine

27. n Single point for copy services l Synchronous remote copy l Point in time copy to a full target l Data migration n Use these to implement critical capabilities: l Disaster recovery l "LAN free backup" l "Server free backup" l Non-disruptive replacement Can you really do virtualization without virtual copy services? VISC Managed Disks Virtual LUNs VISC Storage Network VISC Managed Disks Virtual LUNs VISC Storage Network Common Platform for Advanced Functions

28. Increase Storage Administrator Productivity l Administrator can manage, add and migrate physical disks transparently from application Servers (i.e., servers are "insulated" from physical assets) l A single point of control, administration, planning, and security Provide a Common Platform for Advanced Functions l Disaster Recovery can be done at a single point in the SAN, in a common way l Same is true for Flashcopy, Peer to Peer copy, Data migration Improve Capacity Utilization l Spare capacity on managed disks can be reallocated transparently and dynamically -- irrespective of server operating system/platform type l Reuse retired database capacity and reutilize older storage enclosures Value Proposition of Block Level Virtualization

29. New open standards and software will enable resource sharing and collaboration over the Internet The Actual Layout Your View What the User Sees (one Large Virtual Computer) l Enterprise Workload Mgr l Dynamic Resource Mgt l Single Systems Mgt l Enterprise Backup/ Recovery Grid/eLiza Open Svcs Future Computing Envirionment

30. For the next Generation of Computing Environment, IBM Commits…