UbiManager: A Software Tool for Managing Ubichips

Thoma, Yann; Upegui, Andrés

doi:10.1109/ahs.2008.39

Cited by 6 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We implemented both types of synaptogenesis on the ubichip architecture using the UbiManager design tool [16]. In both cases we implemented an array of 62 neurons (8 × 8 leaving some place for generating the input stimuli) using an ubichip description of 32×32 ubicells, the equivalent of 16×16 macrocells.…”

Section: Experimental Setup and Resultsmentioning

confidence: 99%

“…This stochastic function is easily implemented in the ubichip thanks to the LFSR configuration mode of the ubicell. Figure 2 shows a screenshot of the dynamic routing layer in the UbiManager design tool [16]. In this screenshot we can identify four routing units: the two top units are configured as targets and act as the neuron's dendrites, the bottom left unit is configured as source and acts as the neuron's axon, and the bottom right unit is not used.…”

Section: Synaptogenetic Hardware Modelmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic Routing on the Ubichip: Toward Synaptogenetic Neural Networks

Upegui¹,

Thoma²,

Pérez-Uribe³

et al. 2008

2008 NASA/ESA Conference on Adaptive Hardware and Systems

Self Cite

View full text Add to dashboard Cite

The ubichip is a bio-inspired reconfigurable circuit developed in the framework of the european project Perplexus. The ubichip offers special reconfigurability capabilities, being the dynamic routing one of them. This paper describes how to exploit the dynamic routing capabilities of the ubichip in order to implement synaptogenetic neural networks. We present two techniques for dynamically generating the network topology, we describe their implementation in the ubichip, and we analyse the resulting topology. This work constitutes a first step toward neural circuits exhibiting more realistic neural plasticity features.

show abstract

Section: Experimental Setup and Resultsmentioning

confidence: 99%

Section: Synaptogenetic Hardware Modelmentioning

confidence: 99%