Optical Circuit Concurrent Matrix Operations
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Solution Overview
Problem
Current computing systems face limitations in performing matrix operations efficiently, as they often rely on electrical circuits that are slow compared to optical signals, and struggle to process multiple matrices concurrently without significant increases in computational density.
Innovation Solution
The use of optical circuits that leverage attribute-dependent phase shifts and adjustments, such as wavelength or polarization, to perform concurrent matrix operations on optical signals, allowing for faster processing and increased computational density by using the same optical paths for multiple signal sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If electrical circuits are used to perform matrix operations, then device complexity is reduced and ease of manufacture is improved, but processing speed deteriorates
Solution Approach 1:
The patent replaces electrical circuits with optical circuits to perform matrix operations. Optical signals propagate faster than electrical signals in traditional circuits, achieving nearly instantaneous processing of matrix operations while maintaining manufacturability through integrated optical circuit technology.
Solution Approach 2:
The patent changes the fundamental operating parameter from electrical domain to optical domain. By using optical signals with different wavelengths to represent different matrices, the system achieves parallel processing capability and significantly higher speeds while maintaining practical manufacturability through wavelength multiplexing.
2Productivity
If multiple matrices are processed concurrently using optical circuits, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent creates a universal optical circuit platform that can process multiple different matrices concurrently by using optical signals with different wavelengths. The same physical circuit performs multiple matrix operations simultaneously through wavelength division multiplexing, achieving high productivity without proportionally increasing device complexity.
Solution Approach 2:
The patent adds the wavelength dimension to the optical signals to encode multiple matrices. By utilizing different wavelengths (frequency dimension) in addition to spatial paths, the system achieves concurrent processing of multiple matrices through the same physical infrastructure, significantly improving productivity without linearly increasing device complexity.
3Speed
If optical circuits are used to perform matrix operations, then processing speed is improved, but computational density increases leading to higher device complexity
Solution Approach 1:
The patent merges multiple matrix operations into a single optical circuit by using wavelength multiplexing. Different matrices are encoded in optical signals with different wavelengths that travel through and are processed by the same physical circuit simultaneously, achieving high-speed parallel processing without proportionally increasing device complexity.
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
This approach significantly enhances the performance of matrix operations by enabling nearly instantaneous optical effects and concurrent processing of multiple matrices, leading to improved calculation rates and computational density compared to traditional electrical circuits.
Implementation Method 1
a first plurality of optical signals having a first wavelength are provided to an optical circuit including waveguides and attribute-dependent adjustment elements. The optical circuit performs a first attribute-dependent operation on the first plurality of optical signals. In this way, the optical circuit performs a first wavelength-dependent matrix operation on the values encoded in the first plurality of optical signals.
Implementation Method 2
the optical circuit performs a first attribute-dependent operation on the first plurality of optical signals. In this way, the optical circuit performs a first wavelength-dependent matrix operation on the values encoded in the first plurality of optical signals.
Implementation Method 3
A wide body of algebraic operations have been developed to manipulate and analyze matrices and their contents, and because they are utilized with such frequency, computing systems may include dedicated hardware for handling matrices and performing these operations.
Data Source
AI summary
Examples described herein relate to concurrently performing operations on optical signals. In an example, a method includes providing, to an optical circuit, a first plurality of signals having a first optical property and encoding a first vector. A second plurality of signals is provided to the circuit that encodes a second vector and has a second optical property that is different from the first optical property. A first attribute-dependent operation is performed on the first plurality of signals via the circuit to perform a first matrix multiplication operation on the first vector, and concurrently, a second attribute-dependent operation is performed on the second plurality of signals to perform a second matrix multiplication operation on the second vector. The first matrix multiplication operation and the second matrix multiplication operation are different based on the first optical property being different from the second optical property.