Howdy readers! Today I’m here with another piece of information. This time I’m writing on grid computing and a few applications of grid computing. But first, let me shed some light on what grid computing is.
Grid computing is a distributed architecture of a large number of computers connected to a network that share each other and many more resources.
To name a few, memory storage and processing power are a few resources that users can leverage for completing certain tasks.
All the nodes on this network have authorized access and no other can access the network.
In the ideal grid computing scenario, every resource present is shared among the authorized computers turning them into supercomputers. Every node (individual computer) has access to massive storage and processing power.
Distributed supercomputing may seem like a fancy term but it’s very easy to understand. Let me put it this way, a grid computing network spread across different geographical areas, even different countries is distributed supercomputing. Easy right!
High throughput tasks give a little bit away by its name only, doesn’t it? Well, it can be characterized by the tasks wherein you need a large amount of processing power for an extended amount of time.
Time can vary from few months to years. So to accomplish these tasks, there is a need for high throughput supercomputing.
One of the applications of grid computing is on-demand supercomputing. Came into existence to overcome the problems that enterprises faced during fluctuating demand.
This happens when computing services are provided by the third party.
This model can be characterized by three attributes namely pay-per-use, self-service, and scalability. On-demand supercomputing increases a business’ agility.
This is a kind of parallel computing wherein a massive volume of data is divided into chunks of data which are then processed simultaneously.
The data can be as big as the big data! This type of computing is very resourceful when there’s a time constraint associated with the task/project as the operations work simultaneously.
So, the data is divided and worked upon at the same time.
As the name suggests, this kind of computing happens when one organization wants to collaborate with another to make use of its supercomputing abilities.
Doesn’t matter if you’re a mid-size or a large size enterprise, if you don’t have the required skill and resources this is the only way out.
Also, Rolls-Royce, a British aerospace and aviation firm, is one of the first companies to join this collaborative supercomputing initiative.
So these were a few applications of grid computing. Now let me take you to a tour of how some industries are applying grid computing.
Nowadays, being in an IT position in the media industry is also a glamorous position to be in. Large studios are trying hard to recruit the best IT specialists and programmers out there.
One of the major reasons for recruiting the best talent is the increased need for realism in the movies or what we call special effects.
Many films can’t be made without the use of grid computing not only because of special effects but also because of the fact that grid computing enables faster production of a film.
Grid computing is an enhancement tool for the studios.
Traditionally, the gaming industry was an in-house scenario. By in-house, I mean publishers hesitated in outsourcing any element of the project.
But with the growing popularity of online gaming, networking is becoming pivotal, thus comes the grid computing.
Despite all this hesitation, The 451 Group has pinpointed a few areas where grid computing is gaining popularity,
• In-game art internal creation
• In-game cut scenes rendering
• Packaging game assets for multiple platforms
• Distribution of online program
• Hosting of a massively multiplayer online game
The advances in the life sciences sector have led to some accelerated changes in the ways of conducting drug discovery and drug treatment.
With these rapid changes, new challenges are also being surfaced like massive amounts of data analysis, data caching, data mining, and data movement.
With great power comes great responsibility, likewise with these complexities came a few surrounding requirements such as secured storage, privacy, secured data access, and more.
This requires a grid computing architecture that can manage all these complexities and all the while accurately analyze the data.
It gives the ability to afford top-notch information while providing faster responses and accurate results.
The pressure on the engineering firms and industry as a whole is increasing day by day resulting in lesser turnaround time.
The industry is in grave need of capturing data and speeding up the analysis part. And who is going to take care of these complexities? Yes, you guessed it right.
Grid computing can answer these complexities:
• Analysis of real-time data to find a particular pattern.
• Experiment modeling to create new designs.
• Verifying existing models for accuracy using simulation activities.
We all can imagine the amount of data that the government has to process. Grid computing can help in coordinating all the data, which is held across government agencies.
This will make way for clear coordination, not only in case of emergencies but in normal situations as well.
Grid computing will enable virtual organizations which may include many government agencies as participants.
This is an essential step to provide the required data in real-time and simultaneously analyze the data to detect any problem and its solution.
In the end, we can safely say that grid computing answers many complexities across industries. It wasn’t the scenario a few years back but now not only more and more companies but industries are following the grid computing way.
It won’t be wrong to say that if mastered or perfected in the future, grid computing is the way to go.
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