Model Based Computing

As new forms of real-time data continue to come onto the scene, new forms of computing need to be developed to make sense of them. One method: Method Based Computing or RMS (Recognition - Mining, Synthesis) is being actively talked. Here is an introductory article.

" ... For the past year or so, Intel has been talking up RMS, an application software model for terascale computing. RMS, which stands for Recognition, Mining and Synthesis, is the class of software that Intel believes will represent the killer apps of the not-too-distant future -- 2010 and beyond. These applications will require the capabilities of terascale processors -- teraflop performance processing terabytes of data.

RMS applications are used to manipulate complex models, which can be either objects or events. The three components of RMS describe its function. Recognition involves defining the model; mining has to do with sifting through datasets for instances of that model; and synthesis performs "what-if" types of calculations on the model to yield predictions or solutions.

For example in financial markets, there is a deluge of real-time data being generated for all types of traded options (bonds, stocks, currency). This makes qualitative financial analysis somewhat of a guessing game. RMS might change that. A trader would be able to define a model of an attractive options investment (recognition). Once an investment of this type is found (mining), an algorithm could be applied to provide the trader with the different levels of risk and potential return (synthesis) in a given economic environment. The application doesn't provide the trader with an answer, per se, just guidance on which investments are more likely to yield good returns under different sets of economic conditions (interest rates, currency rates, stock P/E ratios, etc.). ... "