This innovation is used to connect between synapse and neuron arrays using nanowire in quantum dot and metal in CMOS (complementary metal oxide semi-conductor) technology to enable the density of a brainlike connection in hardware. The hardware implementation combines three technologies:

  1. Quantum dot and nanowire-based compact synaptic cell (50×50 nm2) with inherently low parasitic capacitance (hence, low dynamic power ≈10–11 watts/synapse),
  2. Neuron and learning circuits implemented in 50-nm CMOS technology, to be integrated with quantum dot and nanowire synapse, and
  3. 3D stacking approach to achieve the overall numbers of high density O(1012) synapses and O(108) neurons in the overall system.

In a 1-cm2 of quantum dot layer sitting on a 50-nm CMOS layer, innovators were able to pack a 106-neuron and 1010-synapse array; however, the constraint for the connection scheme is that each neuron will receive a non-identical 104-synapse set, including itself, via its efficacy of the connection.

This is not a fully connected system where the 100×100 synapse array only has a 100-input data bus and 100-output data bus. Due to the data bus sharing, it poses a great challenge to have a complete connected system, and its constraint within the quantum dot and silicon wafer layer.

For an effective connection scheme, there are three conditions to be met:

  1. Local connection.
  2. The nanowire should be connected locally, not globally from which it helps to maximize the data flow by sharing the same wire space location.
  3. Each synapse can have an alternate summation line if needed (this option is doable based on the simple mask creation).

The 103×103-neuron array was partitioned into a 10-block,102×103-neuron array. This building block can be completely mapped within itself (10,000 synapses to a neuron).

This work was done by Tuan A. Duong, Christopher Assad, and Anilkumar P. Thakoor of Caltech for NASA’s Jet Propulsion Laboratory.

Topics:
Artificial intelligence (AI) Connectivity Education and training Electronics & Computers Hardware Metals Parts People and personalities Research and development Semiconductors
This Brief includes a Technical Support Package (TSP).
Document cover
Optimal and Local Connectivity Between Neuron and Synapse Array in The Quantum Dot/Silicon Brain

(reference NPO-46222) is currently available for download from the TSP library.

Don't have an account?

Magazine cover
NASA Tech Briefs Magazine

This article first appeared in the October, 2010 issue of NASA Tech Briefs Magazine (Vol. 34 No. 10).

Read more articles from this issue here.

Read more articles from the archives here.

Overview

The document titled "Optimal and Local Connectivity Between Neuron and Synapse Array in The Quantum Dot/Silicon Brain" presents a novel approach to creating a brain-like computational system by integrating advanced technologies. The research, conducted by the California Institute of Technology and supported by NASA, focuses on developing a highly efficient neural architecture that mimics biological processes.

The proposed system combines three key technologies:

  1. Quantum Dot and Nanowire Synaptic Cells: These compact synaptic cells, measuring 50x50 nm, are designed to have low parasitic capacitance, resulting in minimal dynamic power consumption (approximately 10^-11 watts per synapse). This efficiency is crucial for scaling up the number of synapses in the system.

  2. Neuron and Learning Circuits in CMOS Technology: The neurons and associated learning circuits are implemented using 50 nm CMOS technology. This integration allows for a high density of neurons and synapses, facilitating complex computations similar to those performed by biological brains.

  3. 3-D Stacking Architecture: The system employs a 3-D stacking approach to achieve a high density of connections, with the potential to support up to 10^12 synapses and 10^8 neurons. This architecture allows for a compact design while maintaining the necessary connectivity for effective neural processing.

The document outlines a conceptual layout for a building block that includes 10^10 synapses and 10^6 neurons within a 1 cm² area. The synaptic array, based on quantum dots, is overlaid on the neuron circuitry, creating a fully connected system that can efficiently process information.

Additionally, the document discusses the biological inspiration behind the design, noting that each neuron can receive thousands of inputs from other neurons, which is essential for learning and memory. The synaptic weights, which modulate the strength of connections between neurons, play a critical role in this process.

In summary, this research presents a groundbreaking approach to neural computation by leveraging quantum dot technology, advanced CMOS circuits, and innovative 3-D stacking methods. The resulting system aims to replicate the efficiency and complexity of biological brains, with potential applications in various fields, including artificial intelligence and neuromorphic computing. The work is part of a broader effort to explore aerospace-related developments with implications for technological and scientific advancements.