Project description
Optical computation based on neuronal signal processing enhances energy efficiency
The dendrites of neurons form a highly branched tree-like structure largely devoted to receiving incoming signals from other neurons and processing them. In fact, some estimates suggest that approximately 75 % of the dendritic surface participates in synaptic transmission, or the reception of a signal from other neurons. The processing itself has linear and non-linear, analog and threshold features, as well as being complex and efficient. Models have been exploring the capabilities of such dendritic computation. Scientists working on the EU-funded ADOPD project intend to harness these concepts for ultrafast fibre-optical computational units, a basis for next-generation neuromorphic computing with significantly reduced energy consumption compared to standard computers. As end-users demand the ever faster processing of exponentially increasing amounts of information for applications ranging from cell phones and gaming to self-driving cars, novel computational units based on dendrite-inspired fibre-optical systems could be a game changer.
Objective
The increased demand for computation with low energy consumption requires entirely novel hardware concepts. In ADOPD we develop ultra-fast computational units based on optical-fiber technologies exploiting information processing principles used by neurons in their dendritic trees. Dendritic processing is highly condensed, local, and parallel and it allows also for non-linear computations. These properties will first be modelled and in a second step transferred to optical systems consisting of fiber optics as well as other optical components. For the first prototype, ADOPD uses well-established single-mode fiber technology to build an optical-dendritic unit (ODU). From there, we move on to cutting-edge multi-mode fibers to obtain an all-optical second prototype of a dendritic tree with significantly higher computing power and compactness. Finally we will design computational models of networks of multiple ODUs to quantify the computational efficiency such multiple, parallel operating devices. Thus, the optical dendritic units created by ADOPD represent a novel, cutting-edge computing hardware for fast, low-power, parallel computing, with the potential to help addressing the rising demands for computation.
Fields of science
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
37073 Gottingen
Germany