clustering by akashmshah

CLUSTER COMPUTING

PREPARED BY:- AKASH M SHAH &KEYUR AADESARA (5TH SEM CE)

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OVERVIEWHigh performance computing

High throughput computing

HPC, and HTC Parallel algorithms

Software technologies

CLUSTER COMPONENTS

1. Multiple High Performance Computers

2. Operating Systems.

A.Linux B. Microsoft NT

3. High Performance Networks.

4. Network Interface Card.

5. Parallel Programming Environments &tools.

parallelprocessingwasperformedbymultipleprocessorsinaspeciallydesignedparallelcomputer.Thesearesystemsinwhichmultipleprocessorsshareasinglememoryandbusinterfacewithinasinglecomputer.Thesetypesofclusterincreaseavailability,performance,andscalabilityforapplications,particularlycomputationallyordataintensivetasks.

Thebasicbuildingblocksofclustersarebrokendownintomultiplecategories:1.ClusterNodes2.ClusterNetwork3.NetworkCharacterizationTherearethreeprimarycategoriesofapplicationsthatuseparallelclusters:1.ComputeIntensiveApplication.2.DataorI/OIntensiveApplications.3.TransactionIntensiveApplications.Ausersubmitsajobtotheheadnode.Thejobidentifiestheapplicationtorunonthecluster.Thejobschedulerontheheadnodeassignseachtaskdefinedbythejobtoanodeandthenstartseachapplicationinstanceontheassignednode.Resultsfromeachoftheapplicationinstancesarereturnedtotheclientviafilesordatabases.

Themainbenefitsofclustersare:1.Availability2.Performance3.ScalabilityThesebenefitsmaptoneedsoftoday'senterprisebusiness,education,militaryandscientificcommunityinfrastructures.

CONTENTS

Introduction Architecture History Application Advantages Disadvantages

INTRODUCTIONWhat is cluster computing?

cluster computing is the technique of linking two or more computers into a network (usually through a local area network) inorder to take advantage of the Parallel processing power of those computers.

INTRODUCTION

The clustering model can provide both HA & HP, and also manageability, scalability, & affordability

Typically homogeneous, tightly coupled, nodes trust each other.

As number of h/w components rises, so does the probability of failure.

Increasing probability of fault occurrence for long-running applications.

WHY WE USE CLUSTER COMPUTING????

Improve the operating speed ofprocessors & other components.

Connect multiple processors together & coordinate their computational efforts.

allow the sharing of a computational task among multiple processors

How does it works?A user submits a job to the head node.

The job identifies the application to run on the cluster.

The job scheduler on the head node assigns each task defined by the job to a node and then starts each application instance on the assigned node.

Results from each of the application instances are returned to the client via files or databases.

CLUSTER COMPUTING ARCHITECTURE

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HISTORYCluster computing system contract by IBM in the 1950s based on the MIT Whirlwind  computer architecture.During the decade of the 1980s, increased interest in the potential of cluster computing was marked by important experiments in research and industry. 

TYPES OF CLUSTERSHigh Availability Clusters

Load-balancing Clusters

High-performance Clusters

HIGH AVAILABILITY CLUSTER

The clusters are designed to maintain redundant nodes that can act as backup systems in the event of failure. The minimum number of nodes in a HA cluster is two - one active and one redundant - though most HA clusters will use considerably more nodes.

High Availability Clusters

HIGH AVAILABILITY CLUSTER

LOAD-BALANCING CLUSTER

Load-balancing clusters are extremely useful for those working with limited IT budgets. Load-balancing clusters operate by routing all work through one or more load-balancing front-end nodes.

HIGH-PERFORMANCE CLUSTER

HPC clusters are designed to exploit parallel processing power of multiple nodes.

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NETWORKEthernet

10 Mbps obsolete100 Mbps almost obsolete1000 Mbps standard

Protocols

TCP/IP

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Example Clusters

July 19991000 nodes Used for genetic algorithm research by John Koza, Stanford Universitywww.genetic-programming.com/

Mateti-Everything-About-Linux

Mateti-Everything-About-Linux 21

Largest Cluster SystemIBM BlueGene, 2007Memory: 73728 GBInterconnect: ProprietaryPowerPC 440106,496 nodes478.2 Tera FLOPS

APPLICATION

There are three primary categories of applications that use parallel clusters.

1.Compute intensive application.

2.Data or i/o intensive applicaion.

3.Transaction intensive application.

ADVANTAGESHigh Performance

Expandability

Scalability: the resources are distributed in case of Cluster Computing.

Easy to upgrade and maintain.

High Availability

DISADVANTAGES

Software: difficult to develop software for distributed systems.

Network:- saturation, transmissions.

Security: easy access also applies to secrete data. Increased power: consumption compare to single server.

CONCLUSIONSolve parallel processing paradox .

Clusters based supercomputers can be seen everywhere!

New trends in hardware and software tech-nologies are likely to make clusters more promising and fill SSI (Single System Image)gap.

FUTURE TRENDS - GRID COMPUTING

The Grid is a large system of computing resources that performs tasks and provides to users a single point of access, commonly based on the World Wide Web interface, to these distributed resources.

Major Grid projects include NASA’s Information Power Grid, two NSF Grid projects (NCSA Alliance’s Virtual Machine Room ).

http://hello-engineers.blogspot.com/

More Information on Clusters

http://www.ieeetfcc.org/

http://lcic.org/

http://beowulf.org/

http://linuxclusters.com/

Sun Microsystems - http://www.sun.com/

REFRERENCES