Benchmarking Keyword Spotting Efficiency on Neuromorphic Hardware

@article{Blouw2019BenchmarkingKS,
  title={Benchmarking Keyword Spotting Efficiency on Neuromorphic Hardware},
  author={Peter Blouw and Xuan Choo and Eric Hunsberger and C. Eliasmith},
  journal={ArXiv},
  year={2019},
  volume={abs/1812.01739}
}
  • Peter Blouw, Xuan Choo, +1 author C. Eliasmith
  • Published 2019
  • Computer Science, Mathematics
  • ArXiv
  • Using Intel's Loihi neuromorphic research chip and ABR's Nengo Deep Learning toolkit, we analyze the inference speed, dynamic power consumption, and energy cost per inference of a two-layer neural network keyword spotter trained to recognize a single phrase. [...] Key Result Our results indicate that for this real-time inference application, Loihi outperforms all of these alternatives on an energy cost per inference basis while maintaining equivalent inference accuracy.Expand Abstract
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