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The Grid

The Grid. 2006.11.8. 분산시스템연구실 최형준. Table of Contents. Introduction to Grid Scientists ’ Dream What is Grid How does it work More about Grid OGSA, WSRF, GT4 VM and the Grid Implementing the Grid on Classical Virtual Machine Systems. Introduction.

keith-jensen
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The Grid

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  1. The Grid 2006.11.8. 분산시스템연구실 최형준

  2. Table of Contents • Introduction to Grid • Scientists’ Dream • What is Grid • How does it work • More about Grid • OGSA, WSRF, GT4 • VM and the Grid • Implementing the Grid on Classical Virtual Machine Systems DCSLab

  3. Introduction • Rapid increase in total amount of computation power • Qualitywise (Moore’s Law) • Quantitywise (Reduced cost, wide availability of easy-to-use programs) • Underutilization of compute power! • Waste of energy + resource DCSLab

  4. Scientists’ Need • Scientists, on the other hand, considerably lack in computation power… • Scientists face increasingly complicated problems, which require heavy computing power • Weather prediction • Development of new drugs • Earth science • High energy physics DCSLab

  5. Scientists’ Need Computers can not keep up with what scientists demand of them!!! Difficult, expensive… and sometimes impossible to achieve certain scientific goals • Example of compute intensive application: CEPAR - 3D protein structure comparison • Similar structure  Similar function • 30,000 proteins in Protein Data Bank • 30 sec to compare each pair on a typical desktop processor • 30,000*30,000/2*30 sec = 428 CPU years on one processor DCSLab

  6. LCG/EGEE • “Large Hadron Collider Computing Grid and Enabling Grid for e-Science in Europe Project” • 27km of circumference • Largest machine ever built by human! • Will generate 15 Petabytes of data per year • Requires 10,000 PCs • CERN only has 1,000 computers and 1 Petabyte of storage • Impossible to process and store this much in a single site • Grid computing is the only solution DCSLab

  7. Scientists’ Dream • I want infinite storage space… • I want infinite computing power… • I want to share data, results, resources with my colleagues… • But how?! • The dream… DCSLab

  8. Solution? • Computer Rentals? • Analogous to vehicle rental model… • Short-term rental of computers fell out of favor Increased complexity of configuring S/W DCSLab

  9. Emergence of New Computing Environment • Emergence of ubiquitous connectivity & Internet • Emerging model for the future • Seek resources over a communication network • Have the task performed remotely • “Computation world is in a state analogous to the electricity world in 1910” – Foster, Kesselman • Utility computing • A business model whereby computer resources are provided on an on-demand and pay-per-use basis DCSLab

  10. What is Grid? Desktop PCs Workstations Data Storage Super-computers World Wide Web Internet Electron-microscopes Satellites Meteorological Sensors DCSLab

  11. What is Grid? • Computers and instruments connected to the Grid share not only information… but also computing power and resources like disk storage and S/W applications • Grid is a service for sharing computer power and data storage capacity over the Internet GRID DCSLab

  12. What is Grid? • The Grid goes well beyond simple communication between computers, and aims ultimately to turn the global network of computers into one vast computational resource • The reality is that today, the Grid is a "work in progress", with the underlying technology still in a prototype phase DCSLab

  13. What is Grid? • Evolution of computing that led to the concept of Grid • Distributed computing • Metacomputing (popular in the 90’s) • Cluster Computing • P2P • The Grid was born at a workshop at Argonne National Laboratory in September 1997 DCSLab

  14. What is Grid? DCSLab

  15. What is Grid? • Using Grid computing, resources from several different organizations are pooled into virtual organizations (VO) to solve specific problems • Grid computing extends the virtual machine concept to “organizational-level virtual machines” VO (2) VO (1) A C B DCSLab

  16. Why scientists need Grid • Grid computing is all about achieving greater performance by pooling together resources from different organizations • Scientists need Grid because it provides the following… • Infinite storage space • Infinite computing power • Possibility to collaborate with distant colleagues, sharing resources, data, and results DCSLab

  17. How does Grid work? • The big picture Registration Submit Job Step 1 Join Virtual Organization Step 4 Create proxy credential Step 2 Get Certificate Step 5 Write job description file (JDL file) Step 3 Install Certificate Step 6 Submit JDL file to Resource Broker Step 7 Check status and get result DCSLab

  18. How does Grid work? • Sample of job description file • <?xml version="1.0" encoding="utf-8" ?> • <job xmlns="http://www.globus.org/namespaces/2004/10/gram/job/description"> • <executable>C:\\Bin\dotNetGridFTPClient.exe</executable> • <argument>-cert</argument> • <argument>CN=a, OU=snu.ac.kr, OU=simpleCA.snu.ac.kr, O=Grid</argument> • <argument>-batch</argument> • <argument>file:///C:\GridFTPRoot\GRenderProject\test.pre</argument> • <argument>gsiftp://147.46.xxx.xxx/GRenderProject/test.pre</argument> • <jobType>single</jobType> • <stdout>C:\GridFTPRoot\dotnetgridftp.exe.txt</stdout> • </job> DCSLab

  19. How does Grid work? • Resource Broker queries Information Service and Replica Catalog to decide which resources to use DCSLab

  20. How does Grid work? • Once the appropriate resources have been located, the job is executed on the remote site DCSLab

  21. How does Grid work? • When the job is finished, the computing element transfers output to the Resource Broker, which in turn passes it back to the user DCSLab

  22. Things to Consider… • How do we decide what resources are part of each virtual organization • How do we decide which resources will be allocated to a task • How do we get resources to communicate among themselves • How do we split up a task so that it can be performed in parallel • Grid computing enables us to access heterogeneous resources from different organizations by providing a set of protocols, technologies, and methodologies that provide an answer to these questions DCSLab

  23. Important Remarks • Grid systems involve heterogeneous resources from different organizations • Coordinating all the resources involves a lot of different services such as job schedulers, resource managers, information services, etc DCSLab

  24. OGSA, WSRF, and GT4 • Common services in a grid system • VO Management Service • Resource Discovery and Management Service • Job Management Service • Security & Data Management etc… • Solution to successful coordination of these services: “Standardization” • The Open Grid Services Architecture (OGSA) • Developed by Global Grid Forum to define a common, standard, and open architecture for grid-based applications DCSLab

  25. OGSA, WSRF, and GT4 • We need a middleware on which to base the OGSA  Web Services • Web Services is yet another distributed computing technology like CORBA and RMI that allows us to create client/server applications DCSLab

  26. OGSA, WSRF, and GT4 • Why Web Service? • Advantages of Web Services • Platform independent • Language independent • Loosely coupled DCSLab

  27. OGSA, WSRF, and GT4 • Web Services is usually stateless • But OGSA requires “stateful services” • Web Services Resource Framework (WSRF) • WSRF specifies how to make Web Services stateful Statefulness Ability to remember information, keep state, from one invocation to another DCSLab

  28. OGSA, WSRF, and GT4 • A stateful Web Service invocation • Keep a state in a separate entity called a “resource” DCSLab

  29. OGSA, WSRF, and GT4 • How do we address a resource? • Use WS-Resource-qualified endpoint reference Endpoint Reference Uri: http://www.example.com/myservice ResourceID: 0x09EB23FA DCSLab

  30. OGSA, WSRF, and GT4 DCSLab

  31. OGSA, WSRF, and GT4 • Globus Toolkit 4 (GT4) • A open source toolkit, developed by The Alliance, which we can use to create Grid systems • Realization of the OGSA requirements • De facto standard for the Grid community • Includes high-level services, programming libraries and tools that we can use to build Grid applications • Security • Data Management • Execution Management • Information Services • Common Runtime DCSLab

  32. OGSA, WSRF, and GT4 • GT4 services Data Replication CredentialMgmt Replica Location Grid Telecontrol Protocol Delegation Data Access & Integration Community Scheduling Framework WebMDS Python Runtime Reliable File Transfer CommunityAuthorization Workspace Management Trigger C Runtime Authentication Authorization GridFTP Grid Resource Allocation & Management Index Java Runtime Security Data Mgmt Execution Mgmt Info Services CommonRuntime DCSLab

  33. OGSA, WSRF, and GT4 DCSLab

  34. OGSA, WSRF, and GT4 • Layered diagram of OGSA, GT4, WSRF, and Web Services Applications OGSA Web Services WSRF DCSLab

  35. Implementing the Grid on Classical Virtual Machine systems • Change the level of abstractionof jobs from the user process level to the full machine • The unit of work with which the grid middleware deals becomes a system virtual machine rather than a process DCSLab

  36. Implementing the Grid on Classical Virtual Machine systems • User isolation • Ensures greater system integrity • Platform independence • Not necessary for there to be a physical system that matches the exact configuration specified by the user • Task management and accounting • Resource control at a higher level of granularity; simplifies job allocation process • Portability • Allows an application to run on any platform that has a VMM specified by the application DCSLab

  37. Implementing the Grid on Classical Virtual Machine systems • Three important aspects of a task in an system VM-based grid • Ability to capture the state of a VM • Ability to instantiate a VM • Ability to save user data DCSLab

  38. User request 2: query (data, image, compute server) 7: Login session window, 5: copy/access user data isolation 1: user request 3: setup VM image 6: return handler to user (URL) Y V2 X V1 4: start VM Implementing the Grid on Classical Virtual Machine systems • Scenario from Figueiredo, Dinda, and Fortes (2003) Information service User ‘Y’ User ‘X’ Front end ‘F’ Physical server pool P Image Server I Data Server D2 Data Server D1 DCSLab

  39. Conclusion • Skeptical Views on Grid • Just an elaborate marketing strategy • Media hype • Too much expectations and promises that can never be fulfilled • Trust/security issues that are inherently difficult to solve (VO involves human interaction) DCSLab

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