Topic: Grid Computing


Grid computing is using the resources of many loosely networked computers at the same time in order to solve a problem that is too large for a single computer to solve. The majority of grid computing use is for scientific problems where there is too much information that needs to be processed to be able to use a single computer. Grid computing is made possible by software that separates different processes and sends them to other computers where those processes are completed and sent back to the original computer. Grid computing can be confined to a small, private network, or it can be applied in a public network comprising many thousand computers. The SETI (Search for Extraterrestrial Intelligence) @Home project is an example of grid computing in a public collaboration.

Early Grid Activities:
Over the past several years, there has been a number of derivatives of Grid Computing, including compute grids, data grids, science grids, access grids, knowledge grids, cluster grids, terra grids, and commodity grids. There are two core functions of grid computing, which are Data function and Computational function. Some of the core functions of data grid computing are:

  • The ability to integrate multiple distributed, heterogeneous, and independently managed data sources.
  • The ability to provide efficient data transfer mechanisms and to provide data where the computation will take place for better scalability and efficiency.
  • The ability to provide data caching and/or replication mechanisms to minimize network traffic.

Some of the core functions of computational grid computing are:

  • The ability to allow for independent management of computing resources.
  • The ability to provide mechanisms that can intelligently and transparently select computing resources capable of running user's job.
  • Understanding of the current and predicted loads on grid resources, resource availability, dynamic resource configuration, and provisioning.


Grid computing holds several advantages over the traditional supercomputer. One of the biggest advantages grid computing holds over a supercomputer is cost. It is much cheaper to to separate functions between multiple processors than to a custom built multiprocessor supercomputer. For this reason, grid computing is gaining popularity. A disadvantage to using grid computing over a supercomputer is speed. All of the processors in a supercomputer are connected using bus while grid computing requires the information to be sent to and from over a network.

Future: The Future of Grid Computing

Applications: Playstation 3
It can be used to solve problems that we have never before been able to solve, like protein folding, earthquake simulation, and weather/climate modeling.
It allows organizations to use technology resources efficiently.
NASA uses grid computing for things like genetic algorithms .
Used by CERN to hold enormous amounts of information fast and efficiently, they need to be able to store information at rates of several gigabytes per second.

Web Resources:

Joseph & Fellenstein, April 2004, "Introduction to Grid Computing"

Technology Review, February 2003, "10 Emerging Technologies That Will Change the World, Page 6