What Grid computing can DO?

When you deploy a grid, it will be to meet a set of customer requirements. To better match grid computing capabilities to those requirements, it is useful to keep in mind the reasons for using grid computing.

Exploiting underutilized resources

The easiest use of grid computing is to run an existing application on a different machine. The machine on which program usually run might have peak in activity, hence short of resources. But there are at least two prerequisites for this scenario.

First, the application must be executable remotely and without undue overhead.

Second, the remote machine must meet any special hardware, software, or resource requirements imposed by the application.

Parallel CPU capacity

The potential for massive parallel CPU capacity is one of the most attractive features of a grid. The common attribute among such uses is that the applications have been written to use algorithms that can be partitioned into independently running parts.  A perfectly scalable application will, for example, finish ‘n’ times faster if it uses ‘n’ times the number of processors.

Applications

There are many factors to consider in grid-enabling an application. Not all applications can be transformed to run in parallel on a grid and achieve scalability. And there are no transforming tool for transformation of an arbitrary application to GRID capable application.

Virtual resources and virtual organizations for collaboration

The users of the grid can be organized dynamically into a number of virtual organizations, each with different policy requirements. These virtual organizations can share their resources collectively as a larger grid. Sharing can be in form of files or Databases. A ‘Data GRID’ can enhance the capability of storing, indexing and searching in many way.

Resource balancing

For applications that are grid enabled, the grid can offer a resource balancing effect by scheduling grid jobs on machines with low utilization.