Predictive Center Allocation Data Structure for Memory Efficiency
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Solution Overview
Problem
Conventional memory sub-systems face performance overhead due to repeated shifts and writes required to maintain data entries in ordered sequences, leading to increased computing resource costs in terms of power, time, and bandwidth.
Innovation Solution
A predictive center allocation data structure that determines a predicted address location for data entries, allowing them to be written to off-center locations in memory resources, reducing the need for shifts and writes, and optimizing data organization by writing subsequent entries based on relative values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data entries are written to memory resources in conventional sequential order, then data organization is simple, but repeated shifts and writes are required to maintain ordered sequences, increasing power consumption and time
Solution Approach 1:
The system performs preliminary analysis of incoming data entries to predict their optimal address locations before writing. By determining predicted address locations in advance based on data characteristics and memory state, the system avoids subsequent shift operations that would be required if data were written sequentially and then reorganized. This preliminary positioning action eliminates the need for maintaining ordered sequences through repeated shifts.
Solution Approach 2:
The patent implements dynamic address allocation where the predicted address location is not fixed but adapts based on the specific data entry characteristics and current memory state. The system dynamically adjusts write positions to optimize for each write operation, preventing the need for subsequent data movement operations. This dynamic approach contrasts with static sequential allocation that requires reorganization.
2Speed
If data entries are written to maintain ordered sequences, then data retrieval is efficient, but repeated shifts and writes increase time consumption
Solution Approach 1:
The system performs preliminary determination of predicted address locations based on data entry characteristics and memory state before the actual write operation. This advance planning ensures that data is positioned optimally from the start, eliminating the need for subsequent shift operations that would be required to maintain ordered sequences. The preliminary action captures the optimization opportunity before the time-consuming write and shift operations would occur.
Solution Approach 2:
The patent creates a predicted address location model based on analyzing characteristics of data entries and memory state, rather than physically organizing data in strict sequential order. This model acts as a virtual copy or representation of the ideal data arrangement, allowing the system to achieve efficient retrieval without the physical reorganization costs of maintaining ordered sequences through shifts.
3Ease of manufacture
If conventional sequential write methods are used, then implementation is simple, but computing resource costs increase due to repeated shifts and writes
Solution Approach 1:
The system introduces a preliminary determination step that analyzes data entry characteristics and memory state to predict optimal address locations. While this adds a computational step, it eliminates the need for complex shift operations and multiple write cycles that would be required to maintain ordered sequences. The net effect is reduced computing resource requirements despite the added prediction step.
Solution Approach 2:
The patent replaces the mechanical approach of physically shifting data entries in memory with a computational approach of predicting optimal address locations beforehand. Instead of using shift operations (mechanical data movement) to maintain order, the system uses predictive algorithms to determine where data should be written initially, substituting computational prediction for mechanical reorganization.
Data Source
AI summary
An apparatus includes a memory resource configured to store data entries in data structures including a first data structure and a second data structure and a processing device coupled to the memory resources. The processing device is configured to determine a predicted address location in the first data structure for a data entry, determine an equivalent address location in the second data structure, and write the data entry to the equivalent address location in the second data structure.