SpaceFibre is the next generation of high speed interconnects for spacecraft communication networks. However the high performance and advanced features mean that SpaceFibre interfaces have an inherently high level of complexity, rendering implementation in some FPGA systems difficult due to limited hardware resources. This paper presents an investigation into the hardware resource characteristics of SpaceFibre through an experimental evaluation using the StarDundee IP core, including discussion of functionality tradeoffs that can be made when designing an interface for a limited number of hardware resources. A simple SpaceFibre interface optimised for a high-throughput instrument is subsequently described, with a specific focus on resource savings achieved when implementing for the RTAX2000 FPGA.

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Large social insect colonies require a wide range of important tasks to be undertaken to build and maintain the colony. Fortunately, in most nests there are many thousands of workers available to offer their assistance to ensure the expansion and survival of the colony. However, there is a crucial equilibrium between the number of workers performing each task that must not only be maintained but must also continuously adapt to sudden changes in environment and colony need. What is most fascinating is that social insects can sustain this balance without any centralised control and with colony members that have relatively little intelligence when considered on their own. Due to this simplicity and evident scalability it would seem that social insects have evolved an interesting scalable approach to task allocation that could be applied to very large many-core systems. To investigate this we have explored biological models of task allocation in ant colonies and applied this to a 36-core Network on Chip. This paper not only shows that effective decentralised task allocation is achieved, but also that such a scheme can adapt to faults and alter its behaviour to meet soft real-time constraints. Therefore, it is established that social insect inspired intelligence models offer a suitable metaphor and development direction for tackling the challenges introduced by dark silicon and in-field faults in a decentralised and adaptive fashion.

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