The concept of grid computing is not new. In a way, it is
nothing but parallel or distributed computing; however, the difference lies in
the scale and complexity! So imagine parallel processing at a level where
instead of sharing one or more resources, each and every computing resource is
shared among all the computers within the network (as if they form an
interconnected grid). Now imagine that the grid can consist of several
different authorized heterogeneous systems, even owned by different organizations!
It would be like a huge supercomputer with unmatched processing power, memory
capacity and data storage capacity suitable for the most complex computations,
but really it is just a network of interconnected computers. As far as the user
of a grid computer is concerned, he/she is just using the local computer (now a
supercomputer owing to the grid links) unaware of the links contributing to the
power and enormous complexity of the network grid or cluster to which that
machine belongs.
Grid computing is a computer network in which each
computer's resources are shared with every other computer in the system.
Processing power, memory and data storage are all community resources that
authorized users can tap into and leverage for specific tasks. A grid computing
system can be as simple as a collection of similar computers running on the
same operating system or as complex as inter-networked systems comprised of
every computer platform you can think of.
Grid computing, offers increased agility and scalability,
requires more of an upfront cost. Therefore, grid computing is more geared
toward increasing computing efficiency and is often the choice of companies
with more money upfront, due to the infrastructure and development demands of
such a system. Grid computing seeks to assist skilled programmers. While it can
be used for tasks like customer relationship management, it is better suited to
more complex and involved business tasks.
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