With the advent of networking and high-powered workstations, and the rise of end-user computing alongside the traditional centralised computing model, the heterogeneous network is emerging as the most significant platform for many computing activities. A heterogeneous network consists of a number of resources (e.g. workstations, fileservers, database engines and computation nodes) interconnected by a fast data network; open systems standards facilitate interoperability in this (possibly multivendor) environment.
This platform offers significant benefits for statistical computing applications. Not only can programs access repositories of online data as required, they can also access other processors in order to exploit specialised features or just to harness idle resources. Hence computationally intensive tasks can be accelerated by farming out subtasks to multiple processors. Further, this platform supports groups of users and hence there is scope for the development of applications which facilitate collaborative working, such as a team of researchers working on a common dataset.