Posit Neuromorphic Computing With Analog Format Conversion
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Solution Overview
Problem
Performing neuromorphic operations on data stored in the Type III unum format is cumbersome and less efficient compared to performing such operations on data stored in an analog format, as it can decrease the efficiency of neural network operations and reduce accuracy.
Innovation Solution
The implementation of hardware circuitry that converts bit strings between formats, such as from a unum or posit format to an analog format, allowing for neuromorphic operations to be performed efficiently while maintaining high accuracy and precision, and subsequently converting the results back to the original format for further processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If neuromorphic operations are performed on data stored in unum/posit format, then data precision is maintained, but operational efficiency deteriorates
Solution Approach 1:
The patent introduces an analog format as an intermediary representation for performing neuromorphic operations. Data is converted from unum/posit format to analog format for processing, and then converted back to unum/posit format. This intermediary analog representation enables efficient neuromorphic operations while maintaining the precision benefits of unum/posit formats through the conversion process.
Solution Approach 2:
The patent changes the representation parameter of data from digital unum/posit format to analog format during neuromorphic operations. This parameter change allows the system to leverage the computational efficiency of analog processing while maintaining the ability to preserve precision through the unum/posit format during storage and result representation.
2Measurement precision
If neuromorphic operations are performed on data in unum/posit format, then accuracy is maintained, but processing time increases
Solution Approach 1:
The analog format serves as a mediator that enables fast neuromorphic operations. By converting data to analog format for processing, the system achieves rapid computation while the unum/posit format ensures accuracy is maintained through precise conversion processes before and after the analog processing stage.
Solution Approach 2:
The patent performs preliminary conversion of data from unum/posit format to analog format before neuromorphic operations. This preliminary action prepares the data in a format optimized for fast processing, reducing the time required for neuromorphic operations while maintaining accuracy through the reversible nature of the conversion.
3Measurement precision
If data is stored in unum/posit format for neuromorphic operations, then precision is preserved, but power consumption increases
Solution Approach 1:
The analog format acts as an energy-efficient intermediary for neuromorphic operations. Data is converted to analog format where neuromorphic processing can be performed with lower power consumption compared to digital processing, while the unum/posit format ensures precision is preserved through accurate conversion processes.
Solution Approach 2:
The patent substitutes digital mechanical processing with analog processing for neuromorphic operations. This substitution reduces power consumption by leveraging the inherent parallel processing capabilities of analog circuits, while the unum/posit format ensures precision is maintained through the conversion architecture.
Data Source
AI summary
Systems, apparatuses, and methods related to a neuron built with posits are described. An example system may include a memory device and the memory device may include a plurality of memory cells. The plurality of memory cells can store data including a bit string in an analog format. A neuromorphic operation can be performed on the data in the analog format. The example system may include an analog to digital converter coupled to the memory device. The analog to digital converter may convert the bit string in the analog format stored in at least one of the plurality of memory cells to a format that supports arithmetic operations to a particular level of precision.