Difference between revisions of "Very large-scale simulation"

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==Description:==
==Description:==
E-Science is a whole new concept just emerged.
Large-Scale Simulation is basically simulation of various scientific applications on a very large scale. Coupled with theory and experiment, it will help advance the frontiers of technology and lead to major discoveries in areas such as physics, bioinformatics, astronomy, biology, archeology, oceanography, and support for architecture, virtual reality and most of the large image processing applications.
 
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:==
*Technogical adavnces in GRID<br>
*Technogical adavnces in GRID<br>


*Technogical advances in parallel programming<br>
*Visualization - efficient post-processing of large data sets; feature extraction and scientific discovery in simulation results <br>
 
*Increasing demand for large computational systems, data storage and specialized experimental facilities.<br>
 
*Collaborative engineering<br>
 
*Need for browsing of remote datasets <br>
 
*Need for Usage of remote software<br>
 
*Large-scale parameter studies<br>


*[[Very large-scale simulation]]<br>
*Field specific applications<br>


*[[Data-intensive Computing]]<br>
*[[Data-intensive Computing]]<br>


*[[Virtual Integration]]
*Computation-intensive Computing<br>
<br>


==Inhibitors:==
==Inhibitors:==
- Extending the retirement age to another 10 years so people will have to work more
* Limitted large computational systems, data storage and specialized experimental facilities. <br>


==Paradigms:==
==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:==
==Experts:==
United Nations
US Department of Health and Human Services


==Timing:==
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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:==
==Web Resources:==


[http://scenariothinking.org/wiki/index.php/Technological_Driving_Forces >>back>>]
[http://scenariothinking.org/wiki/index.php/Technological_Driving_Forces >>back>>]

Latest revision as of 16:48, 31 May 2010

Description:

Large-Scale Simulation is basically simulation of various scientific applications on a very large scale. Coupled with theory and experiment, it will help advance the frontiers of technology and lead to major discoveries in areas such as physics, bioinformatics, astronomy, biology, archeology, oceanography, and support for architecture, virtual reality and most of the large image processing applications.

Enablers:

  • Technogical adavnces in GRID
  • Visualization - efficient post-processing of large data sets; feature extraction and scientific discovery in simulation results
  • Field specific applications
  • Computation-intensive Computing

Inhibitors:

  • Limitted large computational systems, data storage and specialized experimental facilities.

Paradigms:

Experts:

jxiePU <a href="http://wqakxreyomtp.com/">wqakxreyomtp</a>, [url=http://ccrcfdielcmk.com/]ccrcfdielcmk[/url], [link=http://hhxyluijbyzv.com/]hhxyluijbyzv[/link], http://nhivyvetemip.com/

Web Resources:

>>back>>

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