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. Acknowledgement This research is supported by Science Foundation Ireland under Grant No. 07/SRC/I1169

2. Spiking Neural Networks (SNN) Emulate biological neurons Communicate through a series of spikes between neurons Information encoded as frequency and magnitude of spikes Provide rich non-linear dynamics for Control applications, e.g. robotics control

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. Acknowledgement This research is supported by Science Foundation Ireland under Grant No. 07/SRC/I1169

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  1. 2. Spiking Neural Networks (SNN) • Emulate biological neurons • Communicate through a series of spikes between neurons • Information encoded as frequency and magnitude of spikes • Provide rich non-linear dynamics for • Control applications, e.g. robotics control • Classifier applications (provide good solution given imprecise data) • Computationally more powerful than traditional ANNs • Connections scale exponentially with number of neurons 1. EMBRACE: Inspiration and Goals • Modelled on biological neurons • Human brain: ~1013 neurons • ~1,000 synapses per neuron • Fault Tolerant / Adaptive • Addresses brain repair by relocating neural synaptic connections Biological neural network SNN spike train sequence illustrating Neuron B potential and output spike firing event Hardware neural network SNN neurons, synapses & interconnect • 3. EMBRACE System Architecture • Goals • Mixed signal device • Low power • Analogue CMOS compatible neuron/synapse cell • Network on Chip (NoC) used for inter-neuron communication • NoC supports neuron packet firing rates (of the order of 10ms) • Scalable, configurable Network on Chip (NoC)-based SNN architecture, implemented on Xilinx Virtex-II Pro FPGA • 32 Neurons • 32 Synapses per Neuron • 8 Spike Generators • 2 Spike Monitors • Table Driven Routing • Genetic Algorithm used to configure • Network parameters • Synaptic Weights/Neuron Thresholds • Benchmark Applications • XOR classification problem • Inverted Pendulum control problem • Robust • Scalable • Reconfigurable Average fitness Best fitness Evolved EMBRACE-FPGA hardware pole balance SNN controller fitness EMBRACE NoC-based Neural tile array EMBRACE NoC-router and neural cell architecture Spike activity in the EMBRACE neural cell EMBRACE neural cell array Hardware evolution platform for evolution of an SNN-based pole balancing function • . • Acknowledgement • This research is supported by • Science Foundation Ireland under Grant No. 07/SRC/I1169 • Irish Research Council for Science, Engineering and Technology (IRCSET), International Centre for Graduate Education in Micro and Nano Engineering (ICGEE) • Xilinx University Programme • 5. Future Work • SystemCNoC-level traffic analysis • Hierarchical NoC • Small footprint fully, locally connected SNN Tile • NoC based inter SNN Tile communication • Reduced topology configuration memory • Fault detection/repair • Further application benchmarking • Contribute to the EMBRACE architecture Seamus Cawley Electrical & Electronic Engineering, National University of Ireland, Galway. Email: seamuscawley@gmail.com Tel: 353 91 493301 Web: http://birc.nuigalway.ie

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