The aim of WiPLASH is to develop miniaturized, wireless graphene antenna that operate in the terahertz band to provide plasticity and reconfigurability for future computing platforms.
To date, computer processors or chips have been of two types: general purpose that can undertake any function with certain velocity, and processors that are ultraspecialized in a specific task, which carry out just one function in a very efficient, fast way. One example is the real-time facial recognition technology that most new smart phones include. This is a sophisticated authentication method that enables a user to unlock their device or verify payments. In this case, a processor can carry out hundreds of thousands of millions of operations per second to process the images.
The prototype of the processor that will be developed in the WiPLASH project is designed for artificial intelligence and automatic learning, disciplines that have been growing exponentially in recent years. When an algorithm, which is a programming code, is run through a large server it consumes an enormous amount of energy. That is why miniaturized wireless graphene antennas are key. They are up to a hundred times smaller than a metal antenna and can operate at extremely rapid frequencies of terahertzs. WiPLASH will verify whether these graphene antennas enable communication networks within a chip for artificial intelligence processors.
These new computing chips could be used in implants in the body, the internet of things, mobile phones, large servers and will open the door to a disruption in which artificial intelligence reaches more places and where size and energy consumption are critical.
The WiPLASH project lasts three years and has received three million euros from the European Commission as part of the Horizon 2020 programme, within the FET OPEN call. Participants in the project include seven European research centres and computing companies.