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Grid Computing Presented by

Adithya DSeminar guide

Mr.RaghavendraDevadas


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Overview Definition Introduction

Benefits Grid Architecture Grid Applications

conclusion


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What is Grid computing? The GRID is a super fast Internet service. The term Grid is chosen as an analogy to a power Grid that

provides consistent, pervasive, dependable, transparentaccess to electricity irrespective of its source.

Experiments everywhere, producing billions of bytes of dataevery day.Its not possible for one single institution to store andanalyze all this data, so scientists have to share computerstorage and processing power around the world at

hundreds of different locations.

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What is Grid Computing ? Allows sharing and coordinated use of diverse

resources in dynamic, distributed virtualorganizations .

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Introduction The popularity of the Internet as well as the availability of

powerful computers and high-speed network technologiesas low-cost commodity components is changing the way weuse computers today.

These technology opportunities have led to the possibility of using distributed computers as a single, unified computingresource, leading to what is popularly known as Gridcomputing.

Grids enable the sharing, selection, and aggregation of awide variety of resources including supercomputers,storage systems, data sources, and specialized devices.

Many large-scale problems cannot be solved by a singlecomputer

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Towards Grid computing: a conceptual view.


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Contd.. The Grid would be the next big thing in the Internet. In

fact, itd be a new technology or a mass of computernetworks that would increase the Internet speeddramatically, which allows the download of entire featurefilms within a few seconds. Yes , a few seconds!.

Some background technologies

Cluster computingPeer to peer computingDistributed computing

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To build a Grid, the development and deploymentof a number of services is required. Such as

Computational , Data, knowledge, Information,Application services.

These services include security , information,

directory, resource allocation etc..

Grid is much better than the existing internet network .

10,000 times faster than the Broadband services.

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Why need Grid Computing?

Core networking technology now accelerates at amuch faster rate than advances in microprocessorspeeds .

Many large-scale problems cannot be solved by asingle computer.

Globally distributed data and resources.

Parallel CPU capacity


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Who needs Grid Computing?

Not just the computer scientists scientists when faced with situations:

The amount of data they need is huge and the data isstored in different institutions.

The amount of similar calculations the scientist has to dois huge.

Other areas: Government Business

Education Industrial design


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Benefits Better utilization of resources Grid computing uses

distributed resources more efficiently and delivers moreusable computing power.

Increased user productivity By providing transparent

access to resources, work can be completed more quickly. Scalability Grids can grow seamlessly over time,allowing many thousands of processors to be integratedinto one cluster. Components can be updatedindependently and additional resources can be added asneeded, reducing large one-time expenses.

Flexibility Grid computing provides computing powerwhere it is needed most, helping to better meetdynamically changing work loads.

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GRID ARCHITECTURE

Our goal in describing our Grid architecture is not toprovide a complete enumeration of all required protocols(and services, APIs, and SDKs) but rather to identifyrequirements for general classes of component.

we follow the principles of the hourglass model. In our architecture, the neck of the hourglass consists of

Resource and Connectivity protocols, which facilitate thesharing of individual resources.

Components within each layer share common

characteristics but can build on capabilities and behaviorsprovided by any lower layer as shown in figure below.

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The layered Grid architecture and its relationship to theInternet protocol architecture. Because the Internet protocol architecture extends from network to application, there is amapping from Grid layers into Internet layers.


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Fabric The Grid Fabric layer provides the resources to which

shared access is mediated by Grid protocols. Fabric components implement the local, resource-specific

operations that occur on specific resources (whetherphysical or logical) as a result of sharing operations athigher levels.

There is thus a tight and subtle interdependence betweenthe functions implemented at the Fabric level, on the onehand, and the sharing operations supported, on the other.

Richer Fabric functionality enables more sophisticatedsharing operations


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Connectivity The Connectivity layer defines core communication and

authentication protocols required for Grid-specific networktransactions. Communication protocols enable theexchange of data between Fabric layer resources.

Authentication protocols build on communication services to

provide cryptographically secure mechanisms for verifyingthe identity of users and resources.

Authentication servers have the following characteristics

Single sign o n: Users must be able to log on (authenticate) just once and then have access to multipleGrid resources defined in the Fabric layer.


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Delegation : A user must be able to endow a program withthe ability to run on that users behalf, so that theprogram is able to access the resources on which the user

is authorized.

Integration with various local security solution s: Each siteor resource provider may employ any of a variety of localsecurity solutions, including Kerberos and Unix security.

User-based trust relationship s: In order for a user to useresources from multiple providers together, the securitysystem must not require each of the resource providers tocooperate or interact with each other in configuring thesecurity environment.

For example, if a user has the right to use sites A and B, theuser should be able to use sites A and B together without requiring that As and Bs security administrators interact


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Resource

The Resource layer builds on Connectivity layer

communication and authentication protocols to defineprotocols (and APIs and SDKs) for the secure negotiation,initiation, monitoring, control, accounting, and payment of sharing operations on individual resources.

Two primary classes of Resource layer protocols can bedistinguished they are,

o Information protocols are used to obtain information aboutthe structure and state of a resource, for example, itsconfiguration, current load, and usage policy (e.g., cost).

o Management protocols are used to negotiate access to ashared resource, specifying, for example, resourcerequirements (including advanced reservation and quality of service) and the operation(s) to be performed.


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Collective

While the Resource layer is focused on interactions with asingle resource, the next layer in the architecture containsprotocols and services (and APIs and SDKs) that are notassociated with any one specific resource but rather areglobal in nature and capture interactions across collectionsof resources.

For this reason, we refer to the next layer of thearchitecture as the Collective layer. Because Collectivecomponents build on the narrow Resource and Connectivitylayer neck in the protocol hourglass, they can implement a

wide variety of sharing behaviors without placing newrequirements on the resources being shared.


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Applications

The final layer in our Grid architecture comprises the userapplications that operate within a VO environment.

Applications are constructed in terms of, and by calling upon,services defined at any layer.

At each layer, we have well-defined protocols that provideaccess to some useful service: resource management, dataaccess, resource discovery, and so forth.

At each layer, APIs may also be defined whose

implementation (ideally provided by third-party SDKs)exchange protocol messages with the appropriate service(s)to perform desired actions.


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Grid Applications Distributed supercomputing High-throughput computing

On-demand computing Data-intensive computing Collaborative computing

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Distributed Supercomputing Idea: aggregate computational resources to

tackle problems that cannot be solved by a singlesystem

Examples: climate modeling, computationalchemistry

Challenges include: Scheduling scarce and expensive resources

Scalability of protocols and algorithms Maintaining high levels of performance acrossheterogeneous systems

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High-throughput computing Schedule large numbers of independent tasks.

Goal: exploit unused CPU cycles (e.g., from idle

workstations).

Unlike distributed computing, tasks looselycoupled.

Examples: parameter studies, cryptographicproblems

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On-demand computing Use Grid capabilities to meet short-term

requirements for resources that cannotconveniently be located locally.

Unlike distributed computing, driven by cost-performance concerns rather than absoluteperformance.

Dispatch expensive or specialized computationsto remote servers.

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Data-intensive computing Synthesize data in geographically distributed

repositories. Synthesis may be computationally and

communication intensive. Examples:

High energy physics generate terabytes of distributed data, need complex queries todetect interesting events.

Distributed analysis of Sloan Digital SkySurvey data.

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Collaborative computing Enable shared use of data archives and

simulations.

Examples: Collaborative exploration of large geophysical

data sets.

Challenges: Real-time demands of interactive applications Rich variety of interactions.

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Conclusion There are currently a large number of projects

and a diverse range of new and emerging Griddevelopmental approaches being pursued. Thesesystems range from Grid frameworks toapplication testbeds, and from collaborativeenvironments to batch submission mechanisms.

It is difficult to predict the future in a field suchas information technology where thetechnological advances are moving very rapidly.Hence, it is not an easy task to forecast what willbecome the dominant Grid approach.

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Reference Foster, C. Kesselman, editors. The Grid: Blueprint for a

New Computing Infrastructure , Morgan Kaufmann, SanFrancisco, Calif. (1999).

Foster. I, Kesselman, C. and Tuecke, S. The Anatomy of theGrid: Enabling Scalable Virtual Organizations. International

Journal of High Performance Computing Application s.

Rajkumar Buyya, Mark Baker. Grids and Gridtechnologies for wide-area distributed computing ,SP&E.

www.globus.org

Ian Foster. The Grid: A New Infrastructure for 21st CenturyScience, Physics today.


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Thank You! You may say I'm a dreamer

But I'm not the only oneI hope someday you'll join usAnd the world will be as one

---Beatles

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