Parallel FSM Pattern Recognition for Data Stream Synchronization
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Solution Overview
Problem
Pattern recognition in computing is bottlenecked by the need to search large data streams for multiple patterns sequentially, leading to delays and synchronization issues, especially as the number of patterns increases.
Innovation Solution
A pattern-recognition processor system that uses parallel finite state machines to evaluate multiple search criteria simultaneously, allowing for concurrent processing of a data stream without a significant increase in search-cycle duration, even with a large number of search criteria, by formatting search criteria into different finite state machines that operate in parallel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If sequential pattern searching is used, then system complexity is low, but processing speed decreases and time delay increases
Solution Approach 1:
The patent divides the processing system into multiple finite state machines (FSMs), each responsible for searching a specific pattern in the data stream. This segmentation allows parallel processing of multiple patterns simultaneously, increasing processing speed while maintaining manageable system complexity through modular design.
Solution Approach 2:
The patent transitions from sequential (one-dimensional) pattern searching to parallel processing by introducing multiple FSMs operating simultaneously. This dimensional change from serial to parallel architecture enables multiple patterns to be searched at the same time, dramatically improving processing speed without proportionally increasing complexity.
2Loss of time
If multiple patterns are searched sequentially, then synchronization is simple, but processing time increases significantly
Solution Approach 1:
The patent segments the pattern recognition task into multiple independent FSMs, each handling a specific pattern. This allows simultaneous execution of multiple pattern searches, reducing the total search cycle duration from sequential sum to parallel maximum, thereby improving both time efficiency and productivity.
Solution Approach 2:
The patent ensures continuous processing by having multiple FSMs operate simultaneously without idle waiting time. While sequential processing would require waiting for each pattern search to complete before starting the next, parallel FSMs maintain continuous useful action by processing multiple patterns concurrently, eliminating waiting time and improving throughput.
3Productivity
If parallel processing is implemented, then processing speed increases, but synchronization problems and timing issues arise
Solution Approach 1:
The patent merges the outputs of multiple parallel FSMs into a unified result set, ensuring that all parallel operations contribute to a consistent final output. This merging process maintains synchronization accuracy by consolidating results from multiple concurrent searches, preserving reliability while benefiting from parallel processing speedups.
Solution Approach 2:
The patent implements feedback mechanisms that monitor and coordinate the operation of multiple FSMs, ensuring proper synchronization. By providing feedback on the state and progress of each parallel search, the system can maintain timing accuracy and synchronization, preventing reliability issues while preserving the productivity benefits of concurrent processing.
Data Source
AI summary
A system includes a device that includes one or more pattern-recognition processors in a pattern-recognition cluster. One of the one or more pattern-recognition processors may be initialized to perform as a direct memory access master device able to control the remaining pattern-recognition processors for synchronized processing of a data stream.