The challenges and major HiCONNECTS objectives are to transform the centralized cloud platform to decentralized platforms which include edge cloud computing in a sustainable, energy-efficient way. This will bring cloud services including Artificial Intelligence (AI) closer to the IOT end-users, which enables them to really use the COT and IOT efficiently. The technologies underpinning this revolutionary step include the development of high-performance computing, storage infrastructure, network interfaces and connecting media , and the analysis of IOT sensors and big data in real-time. This major step forward will enable, for example, the mobile clients (during the 5G deployment phase and 6G exploration) to move among different places with minimum cost, short response time and with stable connection between cloud nodes and mobile devices. The main underlying technology to be developed by the HiCONNECTS consortium, comprising large industrial players, universities and RTOs, and many SMEs, can be summarized under the title: heterogenous integration (HI) which is needed to meet the computing power, bandwidth, latency and sensing requirements for the next generation cloud and edge computing and applications. The HI revolution brings the electronic components and systems (ECS) into a new domain, which combines traditional silicon wafers integrated circuit (IC), InP based high speed electronics , and Si and InP photonics devices and interconnect. The HiCONNECTS ambition is to demonstrate, through HI development, a leap in computing and networking reliability and performances across the full vertical and horizontal ECS value chain (i.e. essential capabilities and key applications) in a sustainable way. In addition, HiCONNECTS will focus on the development of next generation design, algorithms, equipment (HW/SW), systems and Systems of Systems (SOS).

NEoteRIC’s primary objective is the generation of holistic photonic machine learning paradigms that will address demanding imaging applications in an unconventional approach providing paramount frame rate increase, classification performance enhancement and orders of magnitude lower power consumption compared to the state-of-the-art machine learning approaches. NEoteRIC’s implementation stratagem incorporates multiple innovations spanning from the photonic “transistor” level and extending up to the system architectural level, thus paving new, unconventional routes to neuromorphic performance enhancement. The technological cornerstone of NEoteRIC relies on the development and upscaling of a high-speed reconfigurable photonic FPGA-like circuit that will incorporate highly-dense and fully reconfigurable key silicon photonic components (ring resonators, MZIs, etc.). High-speed reconfigurability will unlock the ability to restructure the photonic components and rewire inter-component connections. Through NEoteRIC the integrated photonic FPGAs will be strengthened by the incorporation of novel marginal-power consuming non-volatile high-speed phase shifters that will push the boundaries of energy consumption. NEoteRIC’s “unconventional” chips will be utilized as a proliferating neuromorphic computational platform that will merge the merits of photonic and electronic technology and will allow the all-optical implementation of powerful non-von Neumann architectures such as Reservoir Computing, Recurrent Neural Networks, Deep Neural Networks and Convolutional Neural Networks simultaneously by the same photonic chip. The in-project excellence will be tested through demanding high impact application such as high frame-rate image analysis and in particular single-pixel time-stretch modalities thus pushing the boundaries of state-of-the-art; exhibiting simultaneous high spatial resolution and Gframe/sec processing rate.