State Machine Engine Programming for Parallel Pattern Analysis
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Solution Overview
Problem
Current computing systems face challenges in efficiently performing complex data analysis, particularly in pattern recognition tasks, due to bottlenecks in processing large volumes of data and increasing numbers of patterns.
Innovation Solution
The implementation of a state machine engine with finite state machine (FSM) lattices arranged in a hierarchical parallel configuration, allowing for simultaneous analysis of data streams across multiple criteria, mimicking the hierarchical organization of the human brain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional von Neumann based computers are used for complex data analysis, then system simplicity is maintained, but processing efficiency deteriorates
Solution Approach 1:
The patent replaces conventional von Neumann sequential processing with a hardware-based state machine engine that processes data streams in parallel. The FSM lattice structure uses dedicated hardware circuits instead of software execution, enabling simultaneous pattern matching across multiple data streams and achieving brain-like data analysis efficiency.
Solution Approach 2:
The patent divides the data analysis system into hierarchical layers of state machines, where each layer processes specific aspects of the data stream. The FSM lattice is segmented into multiple independent state machines that can be configured to detect different patterns, allowing parallel processing of complex data while maintaining modular system architecture.
2Adaptability or versatility
If the number of patterns to detect is increased, then pattern recognition capability is improved, but processing delay increases
Solution Approach 1:
The patent merges multiple pattern detection functions into a single hardware-based state machine engine. By combining the detection capabilities of numerous patterns into parallel hardware circuits within the FSM lattice, the system can simultaneously search for multiple patterns in a data stream without sequential processing delays.
Solution Approach 2:
The patent pre-configures the state machine engine with multiple finite state machines that are ready to detect specific patterns as they emerge in the data stream. The hierarchical structure allows patterns to be detected at appropriate levels of the hierarchy, with higher layers analyzing outputs from lower layers, enabling rapid pattern recognition without waiting for complete data processing.
3Speed
If data stream processing speed is increased, then throughput is improved, but analysis accuracy may deteriorate
Solution Approach 1:
The patent replaces software-based data analysis with hardware-based state machine processing that operates at the speed of data arrival. The FSM lattice structure enables the system to process data streams at line rate without the overhead of software interpretation, maintaining both high speed and accurate pattern recognition through dedicated hardware circuits.
Data Source
AI summary
A state machine engine having a program buffer. The program buffer is configured to receive configuration data via a bus interface for configuring a state machine lattice. The state machine engine also includes a repair map buffer configured to provide repair map data to an external device via the bus interface. The state machine lattice includes multiple programmable elements. Each programmable element includes multiple memory cells configured to analyze data and to output a result of the analysis.