cluster computing
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.
Computing Need Overview
Requirements for computing increasing fast. Main reasons:
More data to process.
More compute intensive algorithms available.
Approaches to supply demand:
Qualitative: Optimized algorithms, faster processors, more memory.
Quantitative: Cluster computing, grid computing, etc.
Components
The components critical to the development of low cost clusters are:
1. Processors
2. Memory
3. Networking Components
4. Motherboards, busses, and other sub-systems
IT Limitations 
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. 
Types of Computer Clusters 
There are several different varieties of computer clusters, each offering different advantages to the user. These varieties are: 
High Availability Clusters
Load-balancing Clusters 
High-performance Clusters 
Types of Computer Clusters 
. High Availability Clusters HA Clusters are designed to ensure constant access to service applications. 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. 
Types of Computer Clusters 
. Load-balancing Clusters Load-balancing clusters operate by routing all work through one or more load-balancing front-end nodes, which then distribute the workload efficiently between the remaining active nodes. Load-balancing clusters are extremely useful for those working with limited IT budgets. Devoting a few nodes to managing the workflow of a cluster ensures that limited processing power can be optimised.