In stream computing, advanced software algorithms analyze the data as it streams in. Text, voice and image-recognition technology, for example, can be used to determine that some data is more relevant to a particular problem than others. The priority data is then shuttled off into a program tailored to work on complex, fast-changing problems like tracking an epidemic and predicting its spread, or culling data from electronic sensors in a computer chip plant to quickly correct flaws in manufacturing.
The initial system runs on about 800 microprocessors, though it can scale up to tens of thousands as needed, I.B.M. said. The most notable step, researchers say, lies in the System S software, which enables software applications to split up tasks like image recognition and text recognition, and then reassemble the pieces of the puzzle into an answer.