Introduction to Grid Computing

Grid Computing can be defined as applying resources from many computers in a network to a single problem, usually one that requires a large number of processing cycles or access to large amounts of data.
- Grid computing is the act of sharing tasks over multiple computers.
- These computers join together to create a virtual supercomputer. Networked computers can work on the same problems, traditionally reserved for supercomputers, and yet this network of computers are more powerful.
- The idea of grid computing originated with Ian Foster, Carl Kesselman and Steve Tuecke.
- Grid computing techniques can be used to create very different types of grids, adding flexibility as well as power by using the resources of multiple machines.
- Grid computing is similar to cluster computing, but there are a number of distinct differences. In a grid, there is no centralized management; computers in the grid are independently controlled, and can perform tasks unrelated to the grid at the operator's discretion.
- The computers in a grid are not required to have the same operating system or hardware.
- At its core, Grid Computing enables devices-regardless of their operating characteristics-to be virtually shared, managed and accessed across an enterprise, industry or workgroup.

Benefits of Grid Computing

When you deploy a grid, it will be to meet a set of business requirements. To
better match grid computing capabilities to those requirements, it is useful to
keep in mind some common motivations for using grid computing.
- Exploiting under utilized resources
One of the basic uses of grid computing is to run an existing application on a
different machine. The machine on which the application is normally run might be
unusually busy due to a peak in activity. The job in question could be run on an
idle machine elsewhere on the grid.
- Parallel CPU capacity
The potential for massive parallel CPU capacity is one of the most common
visions and attractive features of a grid. A CPU-intensive grid application can be thought of as many smaller sub-jobs, each executing on a different machine in the grid.
- Virtual resources and virtual organizations for collaboration
Another capability enabled by grid computing is to provide an environment for
collaboration among a wider audience. Grid computing can take these capabilities to an even wider audience, while offering important standards that enable very heterogeneous systems to work together to form the image of a large virtual computing system offering a variety of resources.
- Access to additional resources
In addition to CPU and storage resources, a grid can provide
access to other resources as well. The additional resources can be provided in
additional numbers and/or capacity.
- Resource balancing
A grid federates a large number of resources contributed by individual machines
into a large single-system image. For applications that are grid-enabled, the grid
can offer a resource balancing effect by scheduling grid jobs on machines with
low utilization.
- Reliability
High-end conventional computing systems use expensive hardware to increase
reliability. They are built using chips with redundant circuits that vote on results,
and contain logic to achieve graceful recovery from an assortment of hardware
failures.
- Management
The goal to virtualize the resources on the grid and more uniformly handle
heterogeneous systems will create new opportunities to better manage a larger,
more distributed IT infrastructure. It will be easier to visualize capacity and
utilization, making it easier for IT departments to control expenditures for
computing resources over a larger organization.