State Machine Engine Overflow Control in Parallel Pattern Recognition
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Solution Overview
Problem
Conventional computing systems face inefficiencies in pattern recognition due to the need to search large data streams for multiple patterns sequentially, leading to bottlenecks and slowed data processing, especially as the number of patterns increases.
Innovation Solution
A state machine engine with hierarchical, parallel finite state machine lattices that analyze data streams in parallel, allowing multiple patterns to be recognized simultaneously across high-speed data streams without slowing down the data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If sequential pattern searching is used in conventional computing systems, then implementation simplicity is maintained, but processing speed deteriorates as the number of patterns increases
Solution Approach 1:
The patent divides the pattern recognition task into multiple parallel finite state machine circuits, each capable of independently searching for specific patterns simultaneously. This segmentation allows the system to process multiple patterns in parallel rather than sequentially, dramatically improving data processing speed while maintaining manageable complexity through modular circuit design
Solution Approach 2:
The patent transitions from sequential (one-dimensional) pattern processing to parallel (multi-dimensional) processing by implementing multiple finite state machine circuits that operate simultaneously on different patterns. This dimensional shift from time-sequential to space-parallel processing resolves the contradiction between speed and complexity
2Productivity
If multiple patterns are searched simultaneously in parallel circuits, then processing speed improves, but overflow errors increase due to race conditions
Solution Approach 1:
The patent implements feedback mechanisms where each finite state machine circuit monitors its own state and provides feedback signals to a central control unit. This feedback system detects overflow conditions and race states, allowing the system to identify and correct errors that occur during parallel pattern recognition, thereby maintaining data integrity while preserving high productivity
Solution Approach 2:
The patent performs preliminary detection of potential overflow and race conditions by continuously monitoring circuit states before they can cause data corruption. By detecting these conditions in advance and implementing correction mechanisms proactively, the system maintains both high throughput and data reliability
3Adaptability or versatility
If more circuits are added to handle additional patterns, then pattern recognition capability improves, but hardware resource consumption increases
Solution Approach 1:
The patent designs finite state machine circuits with universal, reconfigurable structures that can be programmed to recognize different patterns. Each circuit can be dynamically configured to handle various pattern types, allowing the system to achieve high adaptability without proportionally increasing hardware resources. The same physical circuits serve multiple pattern recognition functions through reconfiguration
Data Source
AI summary
State machine engines are disclosed, including those having an inter-rank bus control system, which may include a register. The state machine engine may include a plurality of configurable elements, such that each of the plurality of configurable elements comprises a plurality of memory cells. These cells may analyze data and output a result of the analysis. The IR bus control system may halt a write operation of data to be analyzed by the cells based, at least in part, on one or more conditions.