Understanding how simple biological entities perform complex tasks (such as moving away from predators, reproduction and seeking for food) is one of the main goals of researchers across the world. The C. elegans nematode is one of the simplest and well characterised biological nervous systems (BNS) and the Si elegans EU FP7 project aims to develop a framework to mimic its functionality and better understand basic functions. This paper presents a small scale emulation environment composed of 8 neurons running on field programmable gate arrays (FPGAs), where each neuron FPGA is interconnected to all of the other neuron FPGAs via an innovative optical synaptic connectivity strategy. This paper evaluates the fidelity of synaptic communication for transmission of spikes using both wired and optical methods.

Using C. elegans as a model organism, we present on an optimization strategy for reducing the spatial needs and power consumption in an optical connectome implementation. By means of a cluster analysis algorithm1, the interconnectivity of 279 neurons can be subdivided into 3 groups. This clustering reveals 2 independent neural populations, whose members interconnect only within their cluster-community and through a relay group of inter-cluster connections. Using this strategy, the expected spatial needs could be cut down by one fourth, thereby reducing the required light intensities by the same amount. A follow-up sub-partitioning of the individual clusters led to an additional power saving of up to 7%.

In this paper, a review of the different approaches to stationary thermal analysis of stacked die packages is presented, focusing on the opportunity to develop compact models suitable to be included in the design flow. Actually, although three-dimensional integration of the heat equation by numerical methods may provide an accurate estimate of the temperature distribution in the package, its main drawbacks lie in the relatively high computational cost and time consumption, together with the need of very experienced users. Simplified models are thus developed by gradually lumping thermal parameters of the various layers in order to attain a description of the device as a network of thermal resistances.