Automata Processor Network Parallel Pattern Recognition
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Solution Overview
Problem
Conventional computers face inefficiencies in pattern recognition due to the sequential search of increasing pattern volumes in data streams, leading to bottlenecks in processing large data volumes and delays in identifying complex patterns.
Innovation Solution
A processor-based system employing a state machine engine with hierarchical finite state machine lattices that analyze data in parallel, allowing multiple criteria to be searched simultaneously, mimicking the biological brain's hierarchical pattern recognition approach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sequential pattern search is performed on data streams, then pattern recognition can be conducted, but processing time increases and system performance degrades as pattern volume increases
Solution Approach 1:
The patent divides the pattern recognition system into multiple parallel circuits, each responsible for searching a specific portion of the pattern space. This segmentation allows simultaneous processing of multiple patterns without sequential delays, directly resolving the contradiction between pattern recognition capability and processing time.
Solution Approach 2:
The patent transitions from sequential one-dimensional pattern search to parallel multi-dimensional pattern search by distributing patterns across multiple circuits. This dimensional expansion enables concurrent processing of multiple patterns, eliminating the time loss associated with sequential search.
2Productivity
If multiple patterns are searched simultaneously in parallel circuits, then pattern recognition throughput improves, but intermediate results increase system complexity and data volume
Solution Approach 1:
The patent extracts and filters intermediate results from parallel circuit outputs, retaining only relevant pattern matches while discarding irrelevant data. This extraction process reduces the volume of intermediate data that requires further processing, thereby managing system complexity while maintaining high throughput.
Solution Approach 2:
The patent introduces an intermediary processing layer that coordinates between parallel circuits and final output. This intermediary manages the flow and integration of intermediate results, simplifying the overall system architecture by providing a structured approach to handling parallel data streams.
3Ease of manufacture
If conventional von Neumann architecture is used for pattern recognition, then system implementation is straightforward, but processing efficiency deteriorates for complex patterns
Solution Approach 1:
The patent segments the pattern recognition function across multiple dedicated circuits rather than using a single von Neumann processor. Each circuit handles specific pattern matching tasks in parallel, achieving high efficiency for complex patterns while maintaining implementation simplicity through modular circuit design.
Solution Approach 2:
The patent replaces the sequential mechanical processing of von Neumann architecture with parallel hardware circuit processing. This substitution enables simultaneous evaluation of multiple patterns, dramatically improving recognition efficiency for complex data while keeping the system manufacturable through standardized circuit designs.
Data Source
AI summary
The Automata Processor Workbench (AP Workbench) is an application for creating and editing designs of AP networks (e.g., one or more portions of the state machine engine, one or more portions of the FSM lattice, or the like) based on, for example, an Automata Network Markup Language (ANML). For instance, the application may include a tangible, non-transitory computer-readable medium configured to store instructions executable by a processor of an electronic device, wherein the instructions include instructions to represent an automata network as a graph.