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BY: RUTHVIK REDDY GADDAM (2600661) SANDEEP KOYADA (2598727) VAMSHI KRISHNA MERUG PowerPoint Presentation
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BY: RUTHVIK REDDY GADDAM (2600661) SANDEEP KOYADA (2598727) VAMSHI KRISHNA MERUG - PowerPoint PPT Presentation


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GRID COMPUTING. BY: RUTHVIK REDDY GADDAM (2600661) SANDEEP KOYADA (2598727) VAMSHI KRISHNA MERUGU (2595078). Contents. Introduction History Need for Grid computing Advantages Related Technologies Grid Architecture Applications

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BY: RUTHVIK REDDY GADDAM (2600661) SANDEEP KOYADA (2598727) VAMSHI KRISHNA MERUG


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    1. GRID COMPUTING BY: RUTHVIK REDDY GADDAM (2600661) SANDEEP KOYADA (2598727) VAMSHI KRISHNA MERUGU (2595078)

    2. Contents • Introduction • History • Need for Grid computing • Advantages • Related Technologies • Grid Architecture • Applications • Methods of Grid Computing • Issues/Challenges • Future Enhancements • Conclusion

    3. Introduction • Grid computing is enabling, sharing, selection, and aggregation of distributed resources and presenting them as a single unified resource. • Each user should have a single login account to access all resources. • Users can use resources without needing to know source.

    4. Introduction….. • Allows users to use more resources than they independently own. • Resources may be owned by diverse organizations. • ‘The whole is bigger than the part’. • Related terms: Collaborative computing, cooperative computing, shared computing.

    5. History • Born at a workshop called “Building a Computational Grid” held at Argonne National Laboratory in September 1997. • Ian foster, Carl kesselman, and Steve Tuecker are regarded as fathers of grid computing. • Grid computing was orginated in the early 1990s as a metaphor which was used for easy accessing of computer power as an power grid.

    6. Need for Grid Computing • Millions of computer instruction cycles are wasted when not in use. • Users programs are constrained by limited amount of available resources. • Mutual resource sharing would mean users are no longer constrained to use only resources actually owned/operated by themselves.

    7. Advantages • Exploitation of under utilized resources In most organizations desktop machines are busy less than 5% of the time and even servers are idle so these resources can be shared over the grid. • Parallel CPU capacity In many fields like bio-medical, finance, Oil exploration require massive parallel cpu capacity these applications can easily tap into resources available over the grid.

    8. Advantages…. • Data Grids Files and databases can span many systems and thus have larger capacities than on any single system this can improve data transfer rates and data can be duplicated throughout the grid to serve as backup. • Resource balancing For applications that are grid enabled, scheduling can be done on machines with low utilization thereby achieving resource balancing effect.

    9. Advantages…. • Reliability High-end conventional computing systems use expensive hardware to increase reliability. Grid allows for machine redundancy and instant failover to other resources. • Communication When machines on a grid are connected to the internet and don’t share the same communication paths, they add to the total available bandwidth.

    10. Representation of Grid Computing

    11. Related technologies Cluster Computing • A set of connected computers that work together so that it can be viewed as a single system. • Cheaper to build than a mainframe supercomputer. • These have wide range of applicability and deployment.

    12. Related Technologies…. Peer to Peer Computing • Can access files from any computer on the network. • Allows data sharing without going through central server • Decentralized approach also useful for grid.

    13. Grid Computing

    14. Grid Architecture Internet GRID Application Application Collective Resource Transport Connectivity Internet Fabric Link

    15. Grid Architecture…. • Fabric layer: Provides the resources to which shared access is mediated by Grid protocols. • Connectivity layer: Defines the core communication and authentication protocols required for grid-specific network functions. • Resource layer: Defines protocols, APIs, and SDKs for secure negotiations, initiation, monitoring control, accounting and payment of sharing operations on individual resources. • Collective Layer:Contains protocols and services that capture interactions among a collection of resources. • Application Layer: These are user applications that operate within VO environment.

    16. Grid Computing:User’s perspective • Enrolling and installing grid software • While there may be tested grid setups with free and unrestricted access to all, production grids require users to first signup for virtual organization membership. • In order to obtain virtual membership, it is mandatory to obtain a digital certificate vouching for his/her identity. • Upon installing identity credentials, the users then has to install client software for accessing the grid.

    17. Grid Computing:User’s perspective • Logging onto the grid: • Many grid systems require the user to log on to a system using an id enrolled in the grid. • Often, the digital certificate itself forms the user’s id for logging onto the grid.

    18. Grid Computing:User’s perspective • Querying and submitting jobs: • The user usually performs queries to check to the resources availabity on the grid. • The user may specify custom requirements in his submit script. • Scripts can also be used to submit pipeline jobs which each job depends on the output of it’s predecessor.

    19. Grid Computing:User’s perspective • The Job submit process: • Firstly , the job input data and possibly the executable program/script is staged in. Alternatively, the data executable may already be on the grid machine. • The job is the executed on the grid machine, either using a common user credential or the user’s own grid identity.

    20. Grid Computing:User’s perspective • Data configuration: • The data accessed by grid jobs may simply be staged in and out by the grid system. • However, in case of pipe-line jobs and other subjobs, repeated staging in can be avoided by using a networked file system instead.

    21. Grid Computing:User’s perspective • Resource reservation: • A user wanting to execute a job may apply for a slot in advance, in which case jobs submitted by him will await for unreserved resource availability or the commencement of reservation window, whichever comes first. • Many grid site offer the service of advance job reservations.

    22. Grid Computing:Administrator’s perspective • Planning: The admin should understand the organization’s requirements and accordingly deploy resources. • Security: Admin must take care to prevent unauthorized access of data in a multi-user grid environment.

    23. Grid Computing:Administrator’s perspective • User and Quota management: • Admin are required to ensure that virtual organization members possess valid accounts/credential mapping on all grid resources. • They must actively monitor machines to ensure that all necessary services are up and running.

    24. Grid Computing:Administrator’s perspective • Certificate Authority (CA) : • It is critical to maintain highest levels of security in a grid because it allows multiple users to not only access data but also to execute code. • The CA is responsible for positively identifying entities requesting for virtual organization membership/credential and ensure their bonafide.

    25. Methods of Grid Computing • Distributed Supercomputing • High-Throughput Computing • On-Demand Computing • Data-Intensive Computing • Collaborative Computing • Logistical Networking

    26. Distributed Supercomputing • Combining multiple high-capacity resources on a computational grid into a single, virtual distributed supercomputer. • Tackle problems that cannot be solved on a single system.

    27. High-Throughput Computing • Uses the grid to schedule large numbers of loosely coupled or independent tasks, with the goal of putting unused processor cycles to work.

    28. On-Demand Computing • Users grid capabilities to meet short-term requirements for resources that are not locally accessible.

    29. Data-Intensive Computing • The focus is on synthesizing new information from data that is maintained in geographically distributed repositories, digital libraries, and databases. • Particularly useful for distributed data mining.

    30. Collaborative Computing • Concerned primarily with enabling and enhancing human-to-human interactions. • Applications are often structured in ters of a virtual shared space.

    31. Logistical Networking • Global scheduling and optimization of data movement. • Contrasts with traditional networking which does not explicitly model storage resources in the network. • Called “logistical” because of the analogy it bears with the systems of warehouses, depots, and distribution channels.

    32. Applications • Scientists in the Earth System Grid (ESG) are producing, archiving, and providing access to climate data that advances our understanding of global climate change. ESG uses Globus software for security, data movement, and system monitoring. Grid Computing

    33. Applications(Contd..) • Computational scientists at Brown University are using the Globus Toolkit and MPICH-G2 to simulate the flow of blood through human arteries. Grid Computing

    34. Applications(Contd..) • Globus Toolkit-driven Grid computing is central to management of large datasets generated by colliders such as those at CERN. This simulation shows two colliding lead ions just after impact, with quarks in red, blue, and green and hadrons in white. Grid Computing

    35. Issues/Challenges • Security: • Access policy refers to who can share and when sharing can occur • Authentication: How to identify a user or resource • User Requirements: • Users often require installation of custom software to run their applications. This is problematic in shared access scenario. • A need was therefore felt for setting up ‘Virtual Organizations’ in which people working on similar technologies/domains could share resources amongst each other.

    36. Issues/Challenges…. • Networking performance: • Networking becomes a major problem when resources are spread across a WAN across cities or even countries. • Grid middleware needs to have high degrees of fault tolerance to allow for intermittent and transient network failures.

    37. Future Enhancements • Latency Limitations • Improved Protocol Schemes • Additional Grid-based Tools. • Cost Reducing.

    38. Prospect of Grid computing • The Grid aims ultimately to turn the global network of computers into one vast computational resource. • Related to many areas in computer science • Being developed by hundreds of researchers and software engineers around the world. • Still “work in process” • Potentially revolutionary. Grid Computing

    39. Conclusion • Grid computing involves cost savings, speed of computation, and ability. • The grid adjusts to accommodate the fluctuating data volumes that are typical in the seasonal business. • Grid computing takes advantage of the fact that most of the computers use their central processing units on average only 25% of the time for the work they have been assigned.

    40. THANK YOU