<< Chapter < Page | Chapter >> Page > |
Over the past decades, as we have begun to explain, we have moved from processing the data that we can hold in a lab notebook to working with many thousands of terabytes of information. (For reference, a terabyte is a million megabytes, and a megabyte is a million letters. A plain textbook might be a few megabytes in size, as might a high-quality photograph — a terabyte is like a huge library.) And yet we keep striving to work with ever more: more genomic data; more high-energy physics data; ever more detailed astronomical photographs; ever richer seismographic measurements; ever more layers of interpretation of artistic details; ever greater volumes of financial data; ever more complex and realistic simulations. We drill down ever deeper into the details. How are we coping with this?
We are in the middle of a huge revolution in information processing, driven by the fact that our tool of choice for working with information — the computer — has been getting exponentially better ever since their invention during the Second World War. We live in the middle of an age of wonder. And yet, despite now being able to hold immense quantities of computation and storage in our hands, our desire to work with ever more has grown even faster.
Thankfully we have been living through another revolution at the same time; the telecommunications revolution. The telecommunications revolution started with the invention of the telegraph, but accelerated with the convergence of computers and telecoms to create the Internet. This not only allows people to share information, but also computers, and it has transformed the world. The first indication of just how amazing this would be came with the WorldWideWeb (WWW), the first internet system to really reflect everything that people do throughout society [link/reference here to history chapter]. But it will not be the last; the ripples from the second wave are now being felt, and it is the global research community that are in the lead. This second wave is Distributed Computing.
Simply put, distributed computing is allowing computers to work together in groups to solve a single problem too large for any one of them to perform on its own. However, to claim that this is all there is to it massively misses the point.
Distributed computing is not a simple matter of just sticking the computers together, throwing the data at them and then saying “Get on with it”! For a distributed computation to work effectively, those systems must cooperate, and must do so without lots of manual intervention by people. This is usually done by splitting problems into smaller pieces, each of which can be tackled more simply than the whole problem. The results of doing each piece are then reassembled into the full solution.
Notification Switch
Would you like to follow the 'Research in a connected world' conversation and receive update notifications?