Hierarchical Parallel State Machines for Faster State Transfer
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Solution Overview
Problem
The existing technologies face challenges in efficiently processing data with hierarchical finite state machines due to the asymmetry between input and output data sizes, which leads to significant delays, particularly in real-time applications where rapid state vector transfer is crucial.
Innovation Solution
The implementation of a hierarchical parallel machine architecture that cascades finite state machine engines, where each engine processes and modifies the output of the previous one, allowing for feedback and compression of state information to reduce data transfer time, and utilizing a method to aggregate final states for efficient data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If hierarchical finite state machines transfer complete state vectors between levels, then state information is accurately transmitted, but data transfer time increases significantly
Solution Approach 1:
The patent extracts only the essential final states from the complete state vector for transmission between hierarchical levels. Instead of transferring the entire state vector, the system identifies and transmits only those states that are relevant for higher-level processing, thereby reducing transfer time while maintaining necessary information accuracy.
Solution Approach 2:
The state vector is segmented into different components, with only the critical final states being transmitted upward through the hierarchy. This segmentation allows the system to separate essential information from redundant data, enabling efficient data transfer while preserving state information accuracy where needed.
2Productivity
If hierarchical finite state machines process data at multiple levels, then processing capability is enhanced, but asymmetry between input and output data sizes causes delays
Solution Approach 1:
The patent changes the parameter of data representation by encoding state information in a compressed format that adapts to the hierarchical level. At higher levels, where processing capability is enhanced, the system uses more compact state representations, which reduces the asymmetry between input and output data sizes and eliminates processing delays.
3Loss of information
If complete state vectors are transmitted between hierarchical levels, then accurate state representation is maintained, but data transmission efficiency decreases
Solution Approach 1:
The system extracts only the necessary final states from complete state vectors for inter-level transmission. This extraction maintains accurate state representation for hierarchical processing while dramatically improving data transmission efficiency by eliminating redundant information.
Solution Approach 2:
Instead of transmitting complete state vectors and filtering at the receiving end, the system inverts the approach by pre-filtering and transmitting only essential states upward. This inversion optimizes transmission efficiency while maintaining the accuracy needed for hierarchical decision-making.
Data Source
AI summary
Programmable devices, hierarchical parallel machines and methods for providing state information are described. In one such programmable device, programmable elements are provided. The programmable elements are configured to implement one or more finite state machines. The programmable elements are configured to receive an N-digit input and provide a M-digit output as a function of the N-digit input. The M-digit output includes state information from less than all of the programmable elements. Other programmable devices, hierarchical parallel machines and methods are also disclosed.