Sensor Data Bitwidth Splitting for Lower-Complexity Processing
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Solution Overview
Problem
Existing data processing systems face inefficiencies due to processors being designed to accommodate maximum bitwidths, leading to higher costs, complexity, and power usage, especially when processing sensor data with varying bitwidths.
Innovation Solution
Processors are configured to split high bitwidth sensor data into subsets that can be processed separately and then merged back into a single data point with the original bitwidth, optimizing operation for efficient bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If processors are designed to accommodate maximum bitwidths, then they can process high-precision sensor data, but this leads to higher costs, increased complexity, and higher power consumption
Solution Approach 1:
The patent divides high bitwidth sensor data into multiple lower bitwidth subsets that can be processed separately by the processor. This segmentation allows the processor to handle data in manageable chunks without requiring the full high bitwidth processing capability, thereby reducing processor complexity while maintaining the ability to process high-precision data.
Solution Approach 2:
The patent dynamically changes the bitwidth parameter of data during processing. High bitwidth sensor data is converted into multiple lower bitwidth subsets for processing, and the results are then recombined to restore the original high bitwidth precision. This parameter transformation enables the processor to operate at lower complexity levels while still achieving high-precision output.
2Measurement precision
If processors are designed to accommodate maximum bitwidths, then they can process high-precision sensor data, but this leads to higher power consumption
Solution Approach 1:
By segmenting high bitwidth data into multiple lower bitwidth subsets, the processor performs multiple simpler processing operations instead of one complex high bitwidth operation. This segmentation reduces the power consumption per operation, and even though multiple operations are performed, the total power consumption is lower than processing the full high bitwidth data in a single operation.
Solution Approach 2:
The patent transforms the bitwidth parameter from high to low during processing operations, enabling the processor to operate at lower power consumption levels. The original high bitwidth precision is restored after processing by recombining the processed subsets, thus achieving high-precision output with reduced power consumption during the critical processing phase.
3Measurement precision
If processors are designed to accommodate maximum bitwidths, then they can process high-precision sensor data, but this increases manufacturing costs
Solution Approach 1:
The segmentation approach allows manufacturers to produce processors with lower bitwidth capabilities at reduced cost, while still enabling support for high bitwidth sensor data through software-based segmentation and recombination. This eliminates the need for expensive high bitwidth processor hardware, significantly reducing manufacturing costs while maintaining compatibility with high-precision sensors.
Solution Approach 2:
By changing the bitwidth parameter dynamically during data processing, the system can use lower bitwidth (and thus lower cost) processor hardware to achieve high bitwidth processing results. This parameter transformation approach allows cost-effective manufacturing of processors that can still handle high-precision sensor data through intelligent data manipulation rather than expensive hardware.
4Area of stationary object
If processors split high bitwidth data into subsets, then processor area and power consumption are reduced, but additional processing steps are required
Solution Approach 1:
The patent segments high bitwidth data into multiple subsets that fit within the processor's native bitwidth capability. This segmentation reduces the required processor area by eliminating the need for high bitwidth processing hardware. The additional processing steps involved in splitting and recombining data are managed through efficient algorithms that minimize overhead, making the trade-off favorable for area-constrained applications.
Solution Approach 2:
After processing the segmented data subsets, the patent merges the results back together to reconstruct the high bitwidth output data. This merging step completes the segmentation- processing- recombination cycle, enabling the system to achieve high bitwidth processing results using lower bitwidth processor hardware, thus reducing the required processor area while maintaining output quality.
Data Source
AI summary
This disclosure provides systems, methods, and devices for efficiently processing data from sensors with varying bitwidths. In one aspect, a method is provided that includes receiving, at a processor, first data from a sensor where the data bitwidth exceeds the processor's predetermined maximum bitwidth. The method involves determining a first and a second subset of the data, processing the subsets to generate processed data, and then determining output data that blends the processed data to match the original bitwidth. Other techniques and implementations are also discussed.