Hardware Self-Organizing List Machine for Constant Access Time
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing self-organizing list technologies face unpredictable performance due to data-dependency and unknown probabilities at initialization, leading to variable and often high worst-case access times, which software-based approaches struggle to optimize effectively.
Innovation Solution
A hardware-based self-organizing list machine comprising an array of symbol index generators with customizable initialization and update mechanisms, utilizing multiplexers for efficient reordering of list items based on various heuristics like Move-To-Front and Move-One-From-Front, ensuring consistent average case access time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If software-based self-organizing list techniques are used, then the system can handle dynamic reordering, but the access time becomes unpredictable and data-dependent
Solution Approach 1:
The patent segments the self-organizing list into multiple parallel hardware paths, each capable of handling specific reordering operations simultaneously. This segmentation allows the system to maintain adaptability while reducing access time variability through parallel processing.
Solution Approach 2:
The patent replaces software-based reordering mechanisms with hardware-based parallel processing units. This substitution eliminates the unpredictable execution characteristics of software while maintaining the dynamic reordering capability through dedicated hardware circuits that can execute reordering operations in fixed, predictable time.
2Loss of time
If the list is initialized in order of diminishing probabilities, then the average access time may be reduced, but the probabilities are unknown at initialization making optimal sequencing impossible
Solution Approach 1:
The patent implements preliminary hardware-based probability estimation circuits that operate during the initialization phase to determine symbol frequencies before the list is fully constructed. This preliminary action allows the system to initialize the list in optimal order even when probability information is initially unavailable.
Solution Approach 2:
The patent incorporates feedback mechanisms where early access patterns are monitored and used to dynamically adjust the list initialization sequence. The hardware circuits collect feedback on symbol access frequencies during initial operations and use this information to optimize the ordering, reducing average access time without requiring prior probability knowledge.
3Ease of operation
If known reordering techniques are applied, then the list can be maintained, but all techniques share the same worst case access time of n
Solution Approach 1:
The patent implements dynamic hardware circuits that can adaptively select and execute different reordering strategies based on real-time access patterns. This dynamic approach allows the system to maintain ease of operation while avoiding worst-case scenarios by automatically switching to optimal reordering methods when detected.
Solution Approach 2:
The patent changes the operational parameters of the reordering system by implementing hardware circuits that can modify list structure parameters dynamically. These circuits monitor access patterns and adjust list organization parameters in real-time, preventing degradation to worst-case access times while maintaining simple operation interfaces.
Data Source
AI summary
A self-organizing list machine is provided for reordering items of a list in a manner that achieves both a constant and minimum time complexity. The self-organizing list machine comprises an array of symbol index generators, wherein (i) each symbol index generator has a unique location in the array between zero and N−1 inclusive, and (ii) N is the total number of unique symbols in a symbol alphabet.