Real-time scalable cortical computing at 46 giga-synaptic OPS/watt with ~100× speedup in time-to-solution and ~100,000× reduction in energy-to-solution

SC(2014)

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摘要
ABSTRACTDrawing on neuroscience, we have developed a parallel, event-driven kernel for neurosynaptic computation, that is efficient with respect to computation, memory, and communication. Building on the previously demonstrated highly-optimized software expression of the kernel, here, we demonstrate TrueNorth, a co-designed silicon expression of the kernel. TrueNorth achieves five orders of magnitude reduction in energy-to-solution and two orders of magnitude speedup in time-to-solution, when running computer vision applications and complex recurrent neural network simulations. Breaking path with the von Neumann architecture, TrueNorth is a 4,096 core, 1 million neuron, and 256 million synapse brain-inspired neurosynaptic processor, that consumes 65mW of power running at real-time and delivers performance of 46 Giga-Synaptic OPS/Watt. We demonstrate seamless tiling of TrueNorth chips into arrays, forming a foundation for cortex-like scalability. TrueNorth's unprecedented time-to-solution, energy-to-solution, size, scalability, and performance combined with the underlying flexibility of the kernel enable a broad range of cognitive applications.
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computer vision,neural chips,neural net architecture,recurrent neural nets,True North chips,codesigned silicon expression,complex recurrent neural network simulation,computer vision application,cortex-like scalability,energy to-solution,energy-to-solution,giga-synaptic OPS/Watt,magnitude reduction,magnitude speedup,neuroscience,neurosynaptic computation,parallel event-driven kernel,real-time scalable cortical computing,software expression,synapse brain-inspired neurosynaptic processor,time-to-solution,von Neumann architecture,
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