Reconfigurable Optical Coprocessor Solving PDEs
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Solution Overview
Problem
Existing solutions for solving Partial Differential Equations (PDEs) using electrical circuits are inefficient in terms of speed, size, and energy consumption, necessitating the development of faster, smaller, and more energy-efficient methods.
Innovation Solution
A Reconfigurable Optical Coprocessor (ROC) utilizing a programmable array of photonic R (and LC) components based on nanoplasmonics technology, which includes tunable Indium Tin Oxide (ITO) for efficient permittivity tuning and deployment of photonics resistors, capacitors, and inductors to solve PDEs directly in the analog domain, leveraging 3D integration for enhanced performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If electrical circuits and arrays of electrical components are used for solving PDEs, then PDE solutions can be achieved, but the computation speed is slow, device size is large, and energy consumption is high
Solution Approach 1:
The patent replaces electrical circuits with optical circuits to solve PDEs. Specifically, it uses photonic R, L, and C components (resistors, inductors, and capacitors) made from materials like ITO (indium tin oxide) and graphene to create an optical computing system that solves partial differential equations directly in the optical domain, eliminating the need for electrical signal conversion and processing
Solution Approach 2:
The patent changes the fundamental operating parameter from electrical signals to optical signals. By using optical frequencies instead of electrical frequencies, the system achieves faster computation speeds (operating at optical frequencies vs. electrical frequencies) and lower energy consumption (photons vs. electrons), directly addressing the speed and energy efficiency contradictions
2Measurement precision
If resistor networks with hundreds of thousands of resistors are used, then PDE solutions can be obtained, but the device size becomes very large
Solution Approach 1:
The patent applies local quality by using nanoscale photonic components with precisely controlled local optical properties. Each photonic R, L, and C element is engineered with specific dimensions and material compositions to achieve desired optical impedance values, allowing accurate PDE solution representation in a compact nanoscale footprint rather than requiring large-scale resistor networks
Solution Approach 2:
The patent transitions from planar electrical resistor networks to three-dimensional stacked photonic circuits. By utilizing vertical stacking of photonic layers with through-silicon vias (TSVs) and interlayer coupling, the system achieves complex PDE solution capabilities in a compact 3D architecture, dramatically reducing the horizontal device area while maintaining solution accuracy
3Productivity
If traditional electrical computing methods are used, then computations can be performed, but energy consumption is high
Solution Approach 1:
The patent substitutes electrical current flow with optical field propagation. Photonic components guide and manipulate light waves to perform computations, eliminating the resistive heating and Joule losses inherent in electrical circuits. This substitution directly reduces energy consumption while maintaining high computation throughput through the inherent parallelism of optical wave propagation
Solution Approach 2:
The patent utilizes periodic optical waves at high frequencies to perform computations. By encoding information in the amplitude, phase, or polarization of periodic optical signals and using interferometric detection, the system achieves high-speed computation with low energy consumption per operation, as the optical fields can be modulated and detected with minimal energy input compared to electrical switching
Data Source
AI summary
An optical-electronic device can be controlled by a bias voltage to simulate an electronic component such as a resistor, capacitor, inductor with resistor, or capacitor with resistor. The optical-electronic device can be connected in a network to perform computations, model problems, simulate properties such as physical properties (for instance heat transfer), and achieve circuit performances to carry out computations in the analog domain, all at faster speed with smaller size and at less energy.