• P.I.: Ingo Fischer, Claudio Mirasso
  • Partners: University of Göttingen, CSIC (IFISC), UIB (IFISC), University of Graz, LEONI Fiber Optics
  • Web page:
  • Start date: Oct. 1, 2020
  • End date: Sept. 30, 2023

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.


  • Ingo Fischer

    Ingo Fischer

  • Claudio Mirasso

    Claudio Mirasso

  • Apostolos Argyris

    Apostolos Argyris

  • Miguel C. Soriano

    Miguel C. Soriano

  • Irene Estébanez

  • Jaime Sánchez

    Jaime Sánchez

  • André Röhm

    André Röhm

Recent Publications

Unveiling the role of plasticity rules in reservoir computing

Morales, Guillermo B.; Mirasso, Claudio R.; Soriano, Miguel C.
Neurocomputing 461, 705-715 (2021)

nMNSD—A Spiking Neuron-Based Classifier That Combines Weight-Adjustment and Delay-Shift

Susi, G.; Antón-Toro, L. F.; Maestú, F.; Pereda, E.; Mirasso, C.
Frontiers in Neuroscience 15, Article 582608 (2021)

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