ADC Grouping and Input Range Optimization for Neural Inference
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Solution Overview
Problem
Conventional analog-to-digital converters (ADCs) occupy a large area and consume significant power, which hampers the efficiency and accuracy of neural network models in electronic devices.
Innovation Solution
The proposed solution involves classifying ADCs into groups based on input signal distribution information and optimizing their input ranges, allowing each group to operate within a specific dynamic range, thereby reducing area and power consumption while enhancing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional analog-to-digital converters are used with fixed input ranges, then they can handle various signal distributions, but they occupy large area and consume significant power
Solution Approach 1:
The patent divides ADCs into multiple groups based on input signal distribution characteristics. Each group is assigned a specific optimized input range, allowing ADCs to be specialized for particular signal types rather than requiring a single large ADC to handle all distributions. This segmentation reduces the area required per ADC while maintaining overall system versatility.
Solution Approach 2:
The system dynamically assigns ADCs to different input ranges based on the actual signal distribution of incoming data. By adapting the input range assignment to match the current signal characteristics, the system optimizes ADC performance for the specific task at hand, reducing the need for oversized ADCs that must accommodate worst-case scenarios across all possible signal distributions.
2Adaptability or versatility
If conventional analog-to-digital converters are used with fixed input ranges, then they can handle various signal distributions, but they consume significant power
Solution Approach 1:
By segmenting ADCs into specialized groups with optimized input ranges, each ADC operates more efficiently within its designated range. This specialization reduces the power consumption of individual ADCs compared to using a single high-performance ADC with a wide input range, while the collective system maintains the ability to handle various signal distributions.
Solution Approach 2:
The system changes the input range parameter of ADC groups based on the characteristics of the input signal distribution. By adjusting which ADC group handles which input range according to signal properties, the system optimizes power consumption for the current operating conditions while maintaining adaptability to different signal types.
3Area of stationary object
If analog-to-digital converters are optimized for specific input ranges, then area and power consumption are reduced, but accuracy may be compromised without proper classification
Solution Approach 1:
The system performs preliminary classification of input signal distributions before routing signals to ADC groups. By analyzing the signal distribution characteristics in advance and assigning ADCs to appropriate input ranges based on this analysis, the system ensures that each ADC operates in its optimized range, maintaining high measurement precision while benefiting from the area and power savings of specialization.
Solution Approach 2:
The system uses feedback from signal distribution analysis to dynamically adjust which ADC groups handle which input ranges. This feedback mechanism ensures that ADCs are always operating in their optimal input ranges for the current signal characteristics, maintaining high accuracy while preserving the benefits of optimized ADC design.
Data Source
AI summary
An electronic device includes analog-to-digital converters each configured to receive an analog input signal and output a digital output signal corresponding to the analog input signal, an analog input signal generator configured to generate analog input signals provided to each analog-to-digital converter based on input voltages and weight data, an input signal distribution information generator configured to generate input signal distribution information indicating a distribution of the analog input signals for each of the analog-to-digital converters, an analog-to-digital converter group classifier configured to classify the analog-to-digital converters into a plurality of first analog-to-digital converter groups based on the input signal distribution information, and an analog-to-digital converter input range optimizer configured to determine an input range of each first analog-to-digital converter group based on the input signal distribution information, and each analog-to-digital converter is configured to operate according to an input range of a corresponding first analog-to-digital converter groups.