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ref: -2019 tags: neuromorphic optical computing date: 06-19-2019 14:47 gmt revision:1 [0] [head]

Large-Scale Optical Neural Networks based on Photoelectric Multiplication

  • Critical idea: use coherent homodyne detection, and quantum photoelectric multiplication for the MACs.
    • That is, E-fields from coherent light multiplies rather than adds within a (logarithmic) photodiode detector.
    • Other lit suggests rather limited SNR for this effect -- 11db.
  • Hence need EO modulators and OE detectors followed by nonlinearity etc.
  • Pure theory, suggests that you can compute with as few as 10's of photons per MAC -- or less! Near Landauer's limit.

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ref: -2017 tags: neuromorphic optical computing nanophotonics date: 06-17-2019 14:46 gmt revision:5 [4] [3] [2] [1] [0] [head]

Progress in neuromorphic photonics

  • Similar idea as what I had -- use lasers as the optical nonlinearity.
    • They add to this the idea of WDM and 'MRR' (micro-ring resonator) weight bank -- they don't talk about the ability to change the weihts, just specify them with some precision.
  • Definitely makes the case that III-V semiconductor integrated photonic systems have the capability, in MMACs/mm^2/pj, to exceed silicon.

See also :

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ref: -2012 tags: phase change materials neuromorphic computing synapses STDP date: 06-13-2019 21:19 gmt revision:3 [2] [1] [0] [head]

Nanoelectronic Programmable Synapses Based on Phase Change Materials for Brain-Inspired Computing

  • Here, we report a new nanoscale electronic synapse based on technologically mature phase change materials employed in optical data storage and nonvolatile memory applications.
  • We utilize continuous resistance transitions in phase change materials to mimic the analog nature of biological synapses, enabling the implementation of a synaptic learning rule.
  • We demonstrate different forms of spike-timing-dependent plasticity using the same nanoscale synapse with picojoule level energy consumption.
  • Again uses GST germanium-antimony-tellurium alloy.
  • 50pJ to reset (depress) the synapse, 0.675pJ to potentiate.
    • Reducing the size will linearly decrease this current.
  • Synapse resistance changes from 200k to 2M approx.

See also: Experimental Demonstration and Tolerancing of a Large-Scale Neural Network (165 000 Synapses) Using Phase-Change Memory as the Synaptic Weight Element