Benefits of grid computing

The potential for massive parallel CPU capacity is one of the most common visions and attractive features of a grid. In addition to pure scientific needs, such computing power is driving a new evolution in industries such as the bio-medical field, financial modeling, oil exploration, motion picture animation, and many others.

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 CPU-intensive grid application can be thought of as many smaller subjobs, each executing on a different machine in the grid. To the extent that these subjobs do not need to communicate with each other, the more scalable the application becomes. A perfectly scalable application will, for example, finish in one tenth of the time if it uses ten times the number of processors.

Barriers often exist to perfect scalability. The first barrier depends on the algorithms used for splitting the application among many CPUs. If the algorithm can only be split into a limited number of independently running parts, then that forms a scalability barrier. The second barrier appears if the parts are not completely independent; this can cause contention, which can limit scalability.

For example, if all of the subjobs need to read and write from one common file or database, the access limits of that file or database will become the limiting factor in the application’s scalability. Other sources of inter-job contention in a parallel grid application include message communications latencies among the jobs, network communication capacities, synchronization protocols, input-output bandwidth to storage or other devices, and other delays interfering with real-time requirements.

There are many factors to consider in grid-enabling an application. One must understand that not all applications can be transformed to run in parallel on a grid and achieve scalability. Furthermore, there are no practical tools for transforming arbitrary applications to exploit the parallel capabilities of a grid. There are some practical tools that skilled application designers can use to write a parallel grid application. However, automatic transformation of applications is a science in its infancy. This can be a difficult job and often requires mathematics and programming talents, if it is even possible in a given situation. New computation-intensive applications written today are being designed for parallel execution, and these will be easily grid-enabled, if they do not already follow emerging grid protocols and standards.