CLUSTER COMPUTING Presented By, Navaneeth.C.Mouly 1AY05IS037 Under the guidance of, Prof.Umapathi G.R
AGENDA • Abstract. • Introduction. • Why Clusters? • Real Time Example. • Architecture. • Cluster Classification. • Benefits. • Dark side of cluster computing. • Applications. • Challenges. • Conclusion.
Abstract Cluster computing is the technique of linking two or more computers into a network (usually through a local area network) in order to take advantage of the parallel processing power of those computers.
INTRODUCTION • Very often applications need more computing power than a sequential computer can provide. • One way of overcoming this limitation is to improve the operating speed of processors and other components so that they can offer the power required by computationally intensive applications. • The viable and cost-effective solution is to connect multiple processors together and co-ordinate their computational efforts.
Shared Pool ofComputing Resources:Processors, Memory, Disks Interconnect Introduction contd.. Pfisterpoints out, there are 3 ways to improve performance.. Work harder. Work smarter Get help
Why Clusters? • The question may arise why clusters are designed and built when perfectly good commercial supercomputers are available on the market. • Clusters are surprisingly powerful . • They are cheap and easy way to take off-the-shelf components and combine them into a single supercomputer. • In some areas of research clusters are actually faster than commercial supercomputer. • Clusters also have the distinct advantage that they are simple to build using components available from hundreds of sources.
Real Time Example 270 GB RAM 8,700 GB Hard Disk Pentium 4 Xeon Cluster
Largest Cluster System IBM BlueGene, 2007 Memory: 73728 GB OS: CNK/SLES 9 Interconnect: Proprietary 106,496 nodes 478.2 Tera FLOPS on LINPACK
Types Of Clusters High availability or Failover Clusters. Load Balancing Clusters. Parallel/Distributed processing clusters.
Benefits Of Clusters • 1. Reduced Cost • 2. Processing Power • 3. Improved Network Technology • 4. Scalability • 5. Availability
Dark Side Of Computing • An eternal struggle in any IT department is in finding a method to squeeze the maximum processing power out of a limited budget. • Today more than ever, enterprises require enormous processing power in order to manage their desktop applications, databases and knowledge management . • Many business processes are extremely heavy users of IT resources, and yet IT budgets struggle to keep pace with the ever growing demand for yet more power.
Challenges • The cluster computing concept also poses three pressing research challenges: • A cluster should be a single computing resource and provide a single system image. This is in contrast to a distributed system where the nodes serve only as individual resources. • The supporting operating system and communication Mechanism must be efficient enough to remove the performance Bottlenecks.
Challenges Cont’d… • The system’s total computing power should increase proportionally to the increase in resources.
Applications • Few important cluster application are: • 1. Google Search Engine. • 2. Earthquake Simulation. • 3.Image Rendering.
Google contd… • Google uses cluster computing to meet the huge quantity of worldwide search requests that comprise of a peak of thousands of queries per second. • A single Google query needs to use at least tens of billions of processing cycles and access a few hundred megabytes of data in order to return satisfactory search result.
Google Cont’d… • The first phase of query execution involves index servers consulting an inverted index that match each query keyword to a matching list of documents. • In the second phase, document servers fetch each document from disk to extract the title and the keyword-in-context portion of the document. • In addition to the 2 phases, the GWS also activates the spell checker and the ad server. The spell checker verifies that the spelling of the query keywords is correct, while the ad server generate advertisements that relate to the query and may therefore interest the user.
Conclusion • Solve parallel processing paradox • Offer incremental growth and matches with funding pattern • New trends in hardware and software technologies are likely to make clusters more promising. • Clusters based supercomputers can be seen everywhere!
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