State Machine Signal Multiplexing for Parallel Pattern Recognition
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Solution Overview
Problem
Conventional computing systems face inefficiencies in pattern recognition due to the increasing volume of data and number of patterns to be identified, leading to bottlenecks in processing and delays in data stream analysis, as existing hardware struggles to process large amounts of data in real-time.
Innovation Solution
The implementation of a state machine engine with hierarchical parallel configuration, utilizing finite state machine lattices that analyze data in parallel, allowing for rapid recognition of complex patterns by cascading clusters of FSM lattices in a series, enabling high-speed processing of data streams with high bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional computing systems process patterns sequentially, then system complexity is reduced, but processing speed and productivity deteriorate due to bottlenecks in data stream analysis
Solution Approach 1:
The patent segments the pattern recognition task into multiple parallel finite state machine circuits, each capable of independently analyzing different patterns simultaneously. This segmentation enables concurrent processing of multiple patterns without sequential bottlenecks, thereby improving processing speed while distributing system complexity across modular units
Solution Approach 2:
The patent transitions from sequential one-dimensional processing to parallel multi-dimensional processing by implementing multiple FSM circuits that operate simultaneously on different patterns. This dimensional change allows the system to process multiple patterns in parallel, dramatically increasing productivity without proportionally increasing overall system complexity
2Productivity
If hardware distributes data stream among multiple circuits, then processing capacity increases, but intermediate results become larger than original input data causing system issues
Solution Approach 1:
The patent extracts only the essential pattern matching results from each FSM circuit rather than transmitting all intermediate processing data. Each circuit outputs binary match/non-match indicators, significantly reducing intermediate data volume while maintaining full pattern recognition capability, thus resolving the issue of excessive intermediate data
3Adaptability or versatility
If the number of patterns to search increases, then pattern recognition capability improves, but processing delay increases causing bottlenecks in data stream analysis
Solution Approach 1:
The patent implements continuous parallel pattern matching where multiple FSM circuits simultaneously analyze incoming data streams without sequential delays. As new patterns are added, additional circuits are deployed to maintain continuous processing, ensuring that pattern recognition capability expands without increasing processing delay
Data Source
AI summary
A device includes a plurality of blocks. Each block of the plurality of blocks includes a plurality of rows. Each row of the plurality of rows includes a plurality of configurable elements and a routing line, whereby each configurable element of the plurality of configurable elements includes a data analysis element comprising a plurality of memory cells, wherein the data analysis element is configured to analyze at least a portion of a data stream and to output a result of the analysis. Each configurable element of the plurality of configurable elements also includes a multiplexer configured to transmit the result to the routing line.