Automata Processor Encoding for Smaller Pattern-Matching Arrays
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Solution Overview
Problem
Automata processors face inefficiencies due to complex arrays of state elements and transitions, leading to excessive resource usage in tasks like pattern matching, which hinders processing power and speed.
Innovation Solution
Encoding sequential position information with data pattern symbols to merge states and transitions, reducing the array size of state transition elements and enabling efficient pattern identification with error compensation for mismatches, substitutions, insertions, and deletions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional automata processors use separate state elements and transition elements to identify data patterns, then pattern matching capability is achieved, but array size and system complexity increase excessively
Solution Approach 1:
The patent combines separate state elements and transition elements into integrated state transition elements. Each state transition element simultaneously performs state storage and transition logic functions, eliminating the need for separate transition elements. This merging reduces the overall array size while maintaining the capability to identify data patterns, directly resolving the contradiction between adaptability and device complexity.
2Adaptability or versatility
If complex arrays of state elements and transitions are used for pattern identification, then pattern matching is achieved, but processing efficiency and speed decrease due to excessive resource usage
Solution Approach 1:
By merging state and transition elements into unified state transition elements, the patent reduces the total number of processing units required. This consolidation decreases resource usage and eliminates redundant operations between separate elements, thereby improving processing efficiency and speed while maintaining pattern identification capability.
3Reliability
If traditional automata processors use separate state and transition elements, then state transitions can be tracked, but resource usage becomes inefficient
Solution Approach 1:
The integration of state and transition elements into single unified elements eliminates the need for separate resource allocation for each function. This merging maintains reliable state transition tracking while significantly improving resource usage efficiency by removing redundant structures and operations associated with separate element implementations.
Data Source
AI summary
A method includes encoding an input data stream to generate an encoded input data pattern, transmitting the encoded input data pattern to a programmed automata processor, and searching the encoded input data pattern via the programmed automata processor to identify an identifiable data pattern within the encoded input data pattern as a data pattern search.


