Virtual Binning Memory Circuit Reduces Shift Operations
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Solution Overview
Problem
Current memory systems face inefficiencies in data organization and retrieval due to the need for frequent shift operations to maintain ordered data structures and the high resource consumption in writing, storing, and retrieving data from memory resources, especially when dealing with large quantities of data entries.
Innovation Solution
The implementation of virtual binning circuitry that organizes data entries using a center allocation data structure, where data is written to address locations based on relative values, reducing shift operations and consolidating data into virtual bins to optimize storage and retrieval processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If data entries are written to maintain ordered data structures using conventional methods, then data organization is achieved, but frequent shift operations are required which increase resource consumption and reduce productivity
Solution Approach 1:
The patent divides the memory resource into multiple bins, each capable of storing data entries with specific value ranges. This segmentation allows data to be distributed across multiple containers rather than maintaining a single ordered structure, eliminating the need for frequent shift operations while preserving data organization capabilities.
Solution Approach 2:
The patent introduces a new dimension of organization by mapping data values to specific bins based on their magnitude rather than maintaining sequential order in a single linear structure. This dimensional transformation from linear ordering to distributed binning reduces the need for shift operations.
2Quantity of substance
If conventional data storage methods are used, then data can be stored in memory resources, but the number of searches required to locate specific data entries increases
Solution Approach 1:
Each bin is assigned a specific value range or characteristic, creating local quality differentiation across the memory structure. When searching for data, the system can first determine which bin contains the target data based on its value, then search only within that localized bin rather than the entire memory resource, significantly improving search efficiency.
3Quantity of substance
If data is written to memory resources using traditional approaches, then data storage is achieved, but the complexity of writing, storing, and retrieving data increases
Solution Approach 1:
The binning structure enables self-service operations where data entries automatically determine their destination bin based on their values, and retrieval operations can directly target specific bins without complex search algorithms. This reduces the operational complexity of writing, storing, and retrieving data while maintaining the ability to handle large quantities of data entries.
Data Source
AI summary
A first memory resource is configured to store a data structure. The first memory resource is coupled to a second memory resource that is configured to store a plurality of data structures. A processing device is coupled to the first memory resource, the second memory resource, and a third memory resource. The processing device writes data entries to the data structure within the first memory resource, determine that the data structure within the first memory resource includes a threshold quantity of data entries, and write the contents of the data structure within the first memory resource to a data structure within the second memory resource. The processing resource is further configured to move the contents of the contents of the data structure in the second memory resource to the third memory resource by readdressing the entries written within the second memory resource to virtual addresses associated with the third memory resource.