Difference between revisions of "Data-intensive Computing"

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==Description:==
==Description:==
E-Science is a whole new concept just emerged.
In high energy physics, bioinformatics, and other disciplines, we encounter applications involving numerous, loosely coupled jobs that both access and generate large data sets, these are large-scale data-intensive problems that normally need to harness geographically distributed resources.
 
In the future, '''''e-Science''''' will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet. Typically, a feature of such collaborative scientific enterprises is that they will require access to very large data collections, very large scale computing resources and high performance visualisation back to the individual user scientists. <br>
 
The Grid is the architecture proposed to bring all these issues together and make a reality of such a vision for e-Science. Ian Foster and Carl Kesselman, inventors of the Globus approach to the Grid define the Grid as an enabler for Virtual Organisations: ‘An infrastructure that enables flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions and resources.’ As a result, e-Science can be deemed as the driving force for Grid's future development.


==Enablers:==
==Enablers:==

Revision as of 17:53, 16 March 2005

Description:

In high energy physics, bioinformatics, and other disciplines, we encounter applications involving numerous, loosely coupled jobs that both access and generate large data sets, these are large-scale data-intensive problems that normally need to harness geographically distributed resources.

Enablers:

  • Technogical adavnces in GRID
  • Technogical advances in parallel programming
  • Increasing demand for large computational systems, data storage and specialized experimental facilities.
  • Collaborative engineering
  • Need for browsing of remote datasets
  • Need for Usage of remote software
  • Large-scale parameter studies


Inhibitors:

- Extending the retirement age to another 10 years so people will have to work more

Paradigms:

There has been enormous concern about the consequences of human population growth for the environment and for social and economic development. But this growth is likely to come to an end in the foreseeable future.

Experts:

United Nations US Department of Health and Human Services

Timing:

Improving on earlier methods of probabilistic forecasting, here we show that there is around an 85 per cent chance that the world's population will stop growing before the end of the century. There is a 60 per cent probability that the world's population will not exceed 10 billion people before 2100, and around a 15 per cent probability that the world's population at the end of the century will be lower than it is today. For different regions, the date and size of the peak population will vary considerably.

Web Resources:

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