Cloud computing often confused with grid computing, but there are key differences between them. When utilizing the resources of numerous computers in a network to work on a single problem at the same time, this is called a grid computing. Usually this implementation is used to address a scientific or technical problem that often needs more processing power. The famous example for this is the Search for Extraterrestrial Intelligence (SETI). Some People all over the world allow the SETI project to share the unused CPU cycles of their computers to search for signs of intelligence in thousands of hours of recorded radio data. Berkeley Open Infrastructure for Network Computing (BOINC) is another example of grid computing example.

In grid computing it’s necessary to use software that can divide and then send out pieces of the program to thousands of computers. This can be done throughout the computers of an organization, or it can be done as a form of public collaboration. Sun Microsystems offers grid engine software that allows engineers at companies to pool the computer CPU cycles on up to 80 workstations at a time. Grid computing could be appealing for several reasons:

  • Cost effective way to use a given amount of computer resources.
  • It is a way to solve problems that need a tremendous amount of computing power.
  • The resources of several computers can be shared cooperatively, without one computer managing the other.

To conclude, grid computing could be used in a large project when computing resources can divided among multiple computers to make use of their resources. Cloud computing is just the opposite to this approach in which it allows multiple smaller applications to run at the same time. This is why grid computing and cloud computing have to do with one another. Thus, grid computing and cloud computing are functioning in fundamentally different ways.

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