clustering clustering      

By  dinesh bhalothia, university of rajasthan, On October 23, 2011

1.3)Clustering of computers for bioinformatics. A flood of data means that many of the challenges in biology are now challengesin computing. Bioinformatics, the application of computational techniques to analyse theinformation associated with biomolecules on a largescale, has now firmly established itself as a discipline in molecular biology, and encompasses a wide range of subject areas from structural biology, genomics to gene expression studies. 1.3.1)CLUSTERING OF COMPUTER’S AT A GLANCE Clustering is the use of multiple computers, typically PCs or UNIX workstations, multiple storage devices, and redundant interconnections, to form what appears to users as a single highly available system. Cluster computing can be used for load balancing as well as for high availability. It is used as a relatively lowcost form of parallel processing machine for scientific and other applications that lend themselves to parallel operations. Computer cluster technology puts clusters of systems together to provide better system reliability and performance. Cluster server systems connect a group of servers together in order to jointly provide processing service for the clients in the network. Cluster operating systems divide the tasks amongst the available servers. Clusters of systems or workstations, on the other hand, connect a group of systems together to jointly share a critically demanding computational task. Theoretically, a cluster operating system should provide seamless optimization in every case. At the present time, cluster server and workstation systems are mostly used in High Availability applications and in scientific applications such as numerical computations. Very often applications need more computing power than a sequential computer can provide.By clustering of computers we can improve the operating speed of processors and other components so that they can offer the power required by computationally intensive applications. Even though this is currently possible to certain extent, future improvements are constrained by the speed of light, thermodynamic laws, and the high financial costs for processor fabrication. A viable and costeffective alternative solution is to connect multiple processors together and coordinate their computational efforts. The resulting systems are popularly known as parallel computers, and they allow the sharing of a computational task among multiple processors and randon access memory(ram). In terms of computing technologies, the analogy to this mantra is that working harder is like using faster hardware (high performance processors or peripheral devices). Working smarter concerns doing things more e_ciently and this revolves around the algorithms and techniques used to solve computational tasks. Finally, getting help refers to using multiple computers to solve a particular task. 1.3.2)Advantages of clustering • High performance • Large capacity • High availability