Comment A Way Forward for Grid Computing (Score 5, Interesting) 146
I've been working in the Grid Computing area for the last two and a half years, and would like to make a stand for all of us who aren't just worried about bigger supercomputers.
Supercomputers are great, but the number of big computing problems that can handle being run on distributed groups of supercomputers is small. That's why things such as the Earth Simulator and the ASCI programme still exist - sometimes it's just better to build a bigger box!
Where Grid Computing might take off in the science and business mainstream is collaboration and sharing of resources. In particular, I work on producing middleware to try and share and unify data resources. In the astronomy community for instance, they have spent many years standardising the naming schemes for their databases and as a result, projects such as Skyserver and SkyQuery are becoming possible. Now consider the bioinformatics field: hundreds of competing standards for naming things as simple as gene expression ids. Grid computing should provide some of the tools to make knowledge extraction from the many disparate scientific databases possible.
This has applications in business, and it's something we're already seeing in the uptake of Web Services. One recent Grid Computing initiative - Grid Services - is pushing the boundaries of Web Services, and extending them to standardise functionality such as state and lifetime management which should make them more useful for the kinds of collaborative problems which are cropping up in both business and science.
For instance: a car manufacturer has an agreement with different suppliers of airbags - obviously information exchange must take place to ensure safety of the passengers, but both the car manufacturer and airbag supplier will not necessarily want the other to be able to see all data for their parts, just use it. As suppliers change, the manufacturer must ensure that data is properly traced and expired. This is not much different from scientific collaborations, financial collaborations or even network gaming where we have a huge number of swiftly changing, transient resources.
It is these problems of dynamic collaboration and maintenance of resources that Grid Computing may eventually solve.
Supercomputers are great, but the number of big computing problems that can handle being run on distributed groups of supercomputers is small. That's why things such as the Earth Simulator and the ASCI programme still exist - sometimes it's just better to build a bigger box!
Where Grid Computing might take off in the science and business mainstream is collaboration and sharing of resources. In particular, I work on producing middleware to try and share and unify data resources. In the astronomy community for instance, they have spent many years standardising the naming schemes for their databases and as a result, projects such as Skyserver and SkyQuery are becoming possible. Now consider the bioinformatics field: hundreds of competing standards for naming things as simple as gene expression ids. Grid computing should provide some of the tools to make knowledge extraction from the many disparate scientific databases possible.
This has applications in business, and it's something we're already seeing in the uptake of Web Services. One recent Grid Computing initiative - Grid Services - is pushing the boundaries of Web Services, and extending them to standardise functionality such as state and lifetime management which should make them more useful for the kinds of collaborative problems which are cropping up in both business and science.
For instance: a car manufacturer has an agreement with different suppliers of airbags - obviously information exchange must take place to ensure safety of the passengers, but both the car manufacturer and airbag supplier will not necessarily want the other to be able to see all data for their parts, just use it. As suppliers change, the manufacturer must ensure that data is properly traced and expired. This is not much different from scientific collaborations, financial collaborations or even network gaming where we have a huge number of swiftly changing, transient resources.
It is these problems of dynamic collaboration and maintenance of resources that Grid Computing may eventually solve.
