There is a fast-growing interest in extending the capabilities of computing systems to perform human-like tasks in an intelligent way. These technologies are usually referred to as cognitive computing. We envision a next revolution in computing in the forthcoming years that will be driven by deploying many “intelligent” devices around us in all kind of environments (work, entertainment, transportation, health care, etc.) backed up by “intelligent” servers in the cloud. These cognitive computing systems will provide new user experiences by delivering new services or improving the operational efficiency of existing ones, and altogether will enrich our lives and our economy.
A key characteristic of cognitive computing systems will be their capability to process in real time large amounts of data coming from audio and vision devices, and other type of sensors. This will demand a very high computing power but at the same time an extremely low energy consumption. This very challenging energy-efficiency requirement is a sine qua non to success not only for mobile and wearable systems, where power dissipation and cost budgets are very low, but also for large data centers where energy consumption is a main component of the total cost of ownership.
Current processor architectures (including general-purpose cores and GPUs) are not a good fit for this type of systems since they keep the same basic organization as early computers, which were mainly optimized for “number crunching”. CoCoUnit will take a disruptive direction by investigating unconventional architectures that can offer orders of magnitude better efficiency in terms of performance per energy and cost for cognitive computing tasks. The ultimate goal of this project is to devise a novel processing unit that will be integrated with the existing units of a processor (general-purpose cores and GPUs) and altogether will be able to deliver cognitive computing user experiences with extremely high energy-efficiency.
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