Bit-Sliced Optical Computing for High-Precision Matrix Operations
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Optical computing faces challenges in improving final calculation accuracy due to factors such as nonlinear effects, optical loss, and error accumulation, limiting its practical application in complex tasks.
Innovation Solution
A high-precision analog optical computation method based on bit slicing, where input and weight signals are decomposed into low-precision bit slices, calculated independently, and combined to achieve high-precision matrix or convolution results through parallel photon computing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If analog optical computing is used for high-speed parallel processing, then computing speed and throughput are improved, but calculation accuracy deteriorates due to nonlinear effects, optical loss, and error accumulation
Solution Approach 1:
The patent applies segmentation by dividing high-precision input and weight signals into multiple low-precision bit slices. Each bit slice is processed independently through the analog optical computing system, and the results are subsequently combined through digital reconstruction to achieve high-precision output. This approach allows the system to benefit from fast analog processing while maintaining accuracy through digital error correction.
Solution Approach 2:
The patent changes the precision parameter of signals during processing. Input signals and weights are transformed from high-precision representations to low-precision bit slices for optical processing, then reconstructed to high-precision results through digital computation. This parameter transformation enables the system to overcome the inherent accuracy limitations of analog optical computing.
2Measurement precision
If weight accuracy is improved through feedforward and feedback control, then weight configuration precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces a digital intermediary layer that mediates between the analog optical processing system and the final high-precision output. Instead of making the analog optical components themselves highly complex to achieve precision, the system uses simple analog processing combined with digital reconstruction algorithms to achieve high accuracy, thereby reducing optical device complexity.
3Measurement precision
If multiple low-precision calculations are performed and combined, then final calculation accuracy is improved, but computational steps increase
Solution Approach 1:
The patent segments the computation into parallel bit slice processing channels. Multiple low-precision calculations are performed simultaneously in parallel rather than sequentially, and the results are combined through efficient digital reconstruction. This parallel processing approach minimizes the time penalty associated with multiple calculation steps.
Data Source
AI summary
A high-precision analog optical computing method and system based on bit slicing comprises decomposing high-precision signals into low-precision signal segments, decomposing high-precision weights into multiple low-precision weight segments, performing low-precision signal and weight multiplication operations in the optical domain respectively, and finally combining these low-precision calculation results to restore high-precision output. By splitting high-precision data into multiple low-precision bit slices for processing, it takes advantage of high-speed parallel characteristics of photonic computing to simultaneously handle multiple input bit slices and weight bit slices, improves computational efficiency of large-scale computing tasks and reduces the hardware requirements for optical computing. By adjusting values of M and N, it flexibly adapts to computing tasks of different scales and precisions, demonstrating strong adaptability and flexibility. It achieves balance between computational accuracy and hardware complexity, and fully exploits parallel processing advantages of photons, providing solutions for large-scale data processing and efficient optical domain computing.