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.
As many of the other posters have pointed out, this work isn't necessarily new, but it is news.
There are other tools out there which do this: Legion, Avaki, Sun Grid Engine, Globus, to name a few but the goal is to create a network of (mostly) supercomputers which doesn't require a lot of reconfiguration at each site. What differentiates this work from many other approaches is that it is transparent to the system administrator.
For those who ask "why can't you just do something let seti@home" the answer is that not all problems in science and business can be easily decomposed into small chunks. Bandwidth requirements and latency may also be a problem. A lot of scientific programmers have to worry about communications much more than about processing power (although this tradeoff has been seesawing backwards and forwards with new advances in both technologies).
There's a worldwide effort through both business and academia to create a number of good, interoperating frameworks for doing this sort of transient, virtualised supercomputer.
Have a look at the Global Grid Forum (which is becoming the focus for Grid computing standards) for more information.
DISCLAIMER: I work for one of the centres involved in the DataGrid project.
One of the things DataGrid is designed to do is to give researchers easy access to the data they need.
It's kind of like a distributed data store with a tree like structure. The collider feeds data to national centres, they feed data to regional centres, regional centres feed data to local research groups, the researchers analyse the data.
What's more interesting, is what happens when these researchers start to exchange their results... terabytes of data flying around in all directions, not just downstream.
As for Grid Computing, yes - most of the technology isn't new, but then again neither was the World Wide Web. The Web was successful because it took existing good ideas, added a killer application (Mosaic) and proved to be useful to other fields than the one it was developed for.
The problem is that "grid" computing is being used to describe a number of distinctly different things: distributed data stores, clustered supercomputers, run-anywhere computing resources, commodity computing...
See the GlobalGridForum pages at: http://www.gridforum.org for more details about Grid research and projects across the world.
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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.
As many of the other posters have pointed out, this work isn't necessarily new, but it is news.
There are other tools out there which do this: Legion, Avaki, Sun Grid Engine, Globus, to name a few but the goal is to create a network of (mostly) supercomputers which doesn't require a lot of reconfiguration at each site. What differentiates this work from many other approaches is that it is transparent to the system administrator.
For those who ask "why can't you just do something let seti@home" the answer is that not all problems in science and business can be easily decomposed into small chunks. Bandwidth requirements and latency may also be a problem. A lot of scientific programmers have to worry about communications much more than about processing power (although this tradeoff has been seesawing backwards and forwards with new advances in both technologies).
There's a worldwide effort through both business and academia to create a number of good, interoperating frameworks for doing this sort of transient, virtualised supercomputer.
Have a look at the Global Grid Forum (which is becoming the focus for Grid computing standards) for more information.
DISCLAIMER: I work for one of the centres involved in the DataGrid project.
One of the things DataGrid is designed to do is to give researchers easy access to the data they need.
It's kind of like a distributed data store with a tree like structure. The collider feeds data to national centres, they feed data to regional centres, regional centres feed data to local research groups, the researchers analyse the data.
What's more interesting, is what happens when these researchers start to exchange their results... terabytes of data flying around in all directions, not just downstream.
As for Grid Computing, yes - most of the technology isn't new, but then again neither was the World Wide Web. The Web was successful because it took existing good ideas, added a killer application (Mosaic) and proved to be useful to other fields than the one it was developed for.
The problem is that "grid" computing is being used to describe a number of distinctly different things: distributed data stores, clustered supercomputers, run-anywhere computing resources, commodity computing...
See the GlobalGridForum pages at: http://www.gridforum.org
for more details about Grid research and projects across the world.