What is the use of grid computing?

What is the use of grid computing?

Grid computing is the term given to a system of computers from different administrative domains, working together to get a task done. Grid computing is used so that a complex task can be done with ease that might not be possible to be handled by a single computer system.

What are the two types of grid in grid computing?

TYPES OF GRID:- 1) COMPUTATIONAL GRID:- It acts as the resource of many computers in a network to a single problem at a time. 2) DATA GRID:- It deals with the controlled sharing and management of distributed data of large amount.

What are the features of grid computing?

According to Bote-Lorenzo (2008:5ff; 2004), main uses of grids are:

  • Distributed supercomputing support.
  • High-throughput computing support.
  • On-demand computing support.
  • Data-intensive computing support.
  • Collaborative computing support.
  • Multimedia computing support.

What are the advantages of grid computing?


  • Accelerate time to market. Grids help improve corporate productivity and collaboration.
  • Enable collaboration and promote operational flexibility.
  • Efficiently scale to meet variable business demands.
  • Increase productivity.
  • Leverage existing capital investments.

What are the limitations of grid computing?

Cons of Grid Computing

  • May Still Require Large SMP. Will be forced to run on a large SMP for memory hungry applications that can’t take advantage of MPI.
  • Requires Fast Interconnect.
  • Some Applications Require Customization.
  • Licensing.

How grid computing is connected?

Grid computing uses a distributed architecture to connect large numbers of computer nodes. Each node runs specialized grid computing software that enables participation in the grid. A grid environment also requires a control node — typically a server — to handle administrative operations and schedule tasks.

What is the advantages of grid computing?

Pros or Advantages of Grid Computing: It is easier to collaborate with other organizations. This model scales very well. This modular environment really scales well. No need to buy a six-figure SMP server for applications that can be split up and farmed out to the smaller commodity-type server.