Abstract:
Braindrop is the first neuromorphic system designed to be programmed at a high level of abstraction. Previous neuromorphic systems were programmed at the neurosynaptic le...Show MoreMetadata
Abstract:
Braindrop is the first neuromorphic system designed to be programmed at a high level of abstraction. Previous neuromorphic systems were programmed at the neurosynaptic level and required expert knowledge of the hardware to use. In stark contrast, Braindrop's computations are specified as coupled nonlinear dynamical systems and synthesized to the hardware by an automated procedure. This procedure not only leverages Braindrop's fabric of subthreshold analog circuits as dynamic computational primitives but also compensates for their mismatched and temperature-sensitive responses at the network level. Thus, a clean abstraction is presented to the user. Fabricated in a 28-nm FDSOI process, Braindrop integrates 4096 neurons in 0.65 mm2. Two innovations-sparse encoding through analog spatial convolution and weighted spike-rate summation though digital accumulative thinning-cut digital traffic drastically, reducing the energy Braindrop consumes per equivalent synaptic operation to 381 fJ for typical network configurations.
Published in: Proceedings of the IEEE ( Volume: 107, Issue: 1, January 2019)
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- IEEE Keywords
- Index Terms
- System Dynamics ,
- Level Of Abstraction ,
- Operator Equation ,
- Analog Circuits ,
- Neuromorphic Systems ,
- Energy Efficiency ,
- Nonlinear Function ,
- Digital Communication ,
- Digital Signal ,
- Analog Signal ,
- Spiking Neural Networks ,
- Communication Time ,
- Spike Trains ,
- Synaptic Weights ,
- Input Current ,
- Spike Rate ,
- Thermal Variation ,
- Transformation Kinetics ,
- Encoding Vector ,
- TrueNorth ,
- Biological Neural Networks ,
- Leaky Integrator ,
- CMOS Process ,
- Function Approximation ,
- Time Constant ,
- Prior Approaches ,
- Weight Matrix ,
- Neuron Counts
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- System Dynamics ,
- Level Of Abstraction ,
- Operator Equation ,
- Analog Circuits ,
- Neuromorphic Systems ,
- Energy Efficiency ,
- Nonlinear Function ,
- Digital Communication ,
- Digital Signal ,
- Analog Signal ,
- Spiking Neural Networks ,
- Communication Time ,
- Spike Trains ,
- Synaptic Weights ,
- Input Current ,
- Spike Rate ,
- Thermal Variation ,
- Transformation Kinetics ,
- Encoding Vector ,
- TrueNorth ,
- Biological Neural Networks ,
- Leaky Integrator ,
- CMOS Process ,
- Function Approximation ,
- Time Constant ,
- Prior Approaches ,
- Weight Matrix ,
- Neuron Counts
- Author Keywords