Optoelectronic Computing for Sub-Nanosecond Optical Matrix Multiplication
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Solution Overview
Problem
Existing neuromorphic computing systems rely heavily on electronic integrated circuits for matrix multiplication, limiting the efficiency and scalability of artificial neural network computations.
Innovation Solution
Implement an optoelectronic computing system that utilizes optical signals for matrix multiplication through an optical processor with passive diffractive optical elements and integrated circuitry for digital-to-analog and analog-to-digital conversions, enabling efficient transformation of input vectors and application of non-linear transformations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If electronic integrated circuits are used for matrix multiplication in neuromorphic computing, then the system can perform neural network computations, but the computational efficiency and scalability are limited
Solution Approach 1:
The patent replaces electronic circuitry with optical computing components to perform matrix multiplication. Optical signals are used to encode input data and weights, and optical modulators and interferometers perform the multiplication operations in the optical domain, eliminating the need for complex electronic circuitry and achieving higher computational efficiency and scalability.
Solution Approach 2:
The patent changes the fundamental operating parameter from electrical signals to optical signals. By encoding data and weights as optical properties (intensity, phase) and performing computations using optical interactions, the system achieves faster computation speeds and higher throughput while reducing the complexity of the computing hardware.
2Speed
If optical signals are used for data transport, then long-distance and high-speed transmission is achieved, but optical computing operations are limited and require conversion to electrical signals
Solution Approach 1:
The patent makes optical signals serve multiple functions: they are used both for data transport and for performing computational operations. The optical computing system can directly process optical signals through optical modulators and interferometers, eliminating the need for separate conversion steps and achieving both high-speed transmission and computation using the same optical infrastructure.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system achieves rapid computation loops of less than 1 ns, facilitating high-speed artificial neural network operations with reduced electronic circuitry reliance, enhancing computational efficiency and scalability.
Implementation Method 1
a plurality of optical modulators coupled to the laser unit and the DAC unit, the plurality of optical modulators being configured to generate an optical input vector by modulating the plurality of light outputs generated by the laser unit based on the plurality of modulator control signals
Implementation Method 2
an optical matrix multiplication unit coupled to the plurality of optical modulators and the DAC unit, the optical matrix multiplication unit being configured to transform the optical input vector into an optical output vector based on the plurality of weight control signals
Implementation Method 3
optical processor with passive diffractive optical elements
Implementation Method 4
a photodetection unit coupled to the optical matrix multiplication unit and configured to generate a plurality of output voltages corresponding to the optical output vector
Data Source
AI summary
Systems and methods that include: providing input information in an electronic format; converting at least a part of the electronic input information into an optical input vector; optically transforming the optical input vector into an optical output vector based on an optical matrix multiplication; converting the optical output vector into an electronic format; and electronically applying a non-linear transformation to the electronically converted optical output vector to provide output information in an electronic format.In some examples, a set of multiple input values are encoded on respective optical signals carried by optical waveguides. For each of at least two subsets of one or more optical signals, a corresponding set of one or more copying modules splits the subset of one or more optical signals into two or more copies of the optical signals. For each of at least two copies of a first subset of one or more optical signals, a corresponding multiplication module multiplies the one or more optical signals of the first subset by one or more matrix element values using optical amplitude modulation. For results of two or more of the multiplication modules, a summation module produces an electrical signal that represents a sum of the results of the two or more of the multiplication modules.