Superconducting Optoelectronic Neurons V: Networks and Scaling

Abstract

Networks of superconducting optoelectronic neurons are investigated for their near-term technological potential and long-term physical limitations. Networks with short average path length, high clustering coefficient, and power-law degree distribution are designed using a growth model that assigns connections between new and existing nodes based on spatial distance as well as degree of existing nodes. The network construction algorithm is scalable to arbitrary levels of network hierarchy and achieves systems with fractal spatial properties and efficient wiring. By modeling the physical size of superconducting optoelectronic neurons, we calculate the area of these networks. A system with 8100 neurons and 330,430 total synapses will fit on a 1\,cm $\times$ 1\,cm die. Systems of millions of neurons with hundreds of millions of synapses will fit on a 300\,mm wafer. For multi-wafer assemblies, communication at light speed enables a neuronal pool the size of a large data center comprising 100 trillion neurons with coherent oscillations at 1\,MHz. Assuming a power law frequency distribution, as is necessary for self-organized criticality, we calculate the power consumption of the networks. We find the use of single photons for communication and superconducting circuits for computation leads to power density low enough to be cooled by liquid ${}^4$He for networks of any scale.

arXiv comment21 pages, 16 figures

References in corpus (12)

• Emergence of scaling in random networks
• Scale-free brain functional networks
• Emergent complex neural dynamics
• Detecting Single Infrared Photons with 93% System Efficiency
• Clustering in Complex Directed Networks
• Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex
• Superconducting optoelectronic circuits for neuromorphic computing
• A general mechanism for the `$1/f$' noise
• Superconducting Optoelectronic Neurons I: General Principles
• Superconducting Optoelectronic Neurons III: Synaptic Plasticity
• Superconducting Optoelectronic Neurons II: Receiver Circuits
• Superconducting Optoelectronic Neurons IV: Transmitter Circuits

Cited by in corpus (4)

• Superconducting Optoelectronic Neurons I: General Principles
• Superconducting Optoelectronic Neurons II: Receiver Circuits
• Superconducting Optoelectronic Neurons IV: Transmitter Circuits
• The largest cognitive systems will be optoelectronic