Data-intensive computing this approach is considered suitable for data-intensive computing and problems which are “embarrassingly parallel”, i.e. where it is relatively easy to separate the problem into a number of parallel tasks and there is no dependency or communication required between the tasks other than overall management of the tasks. These types of data processing problems are inherently adaptable to various forms of distributed computing including clusters, data grids, and cloud computing. Several common characteristics of data-intensive computing systems distinguish them from other forms of computing: A variety of system architectures have been implemented for data-intensive computing and large-scale data analysis applications
Server (computing) than a generic personal computer. The purpose of a server is to share data as well as to share resources and distribute work. A server computer can serve its own computer programs as well; depending on the scenario, this could be part of a "quid pro quo" transaction, or simply a technical possibility. The following table shows several scenarios in which a server is used. Almost the entire structure of the Internet is based upon a client–server model. High-level root nameservers, DNS, and routers direct the traffic on the internet. There are millions of servers connected to the Internet, running