Hierarchical Bitmap Resource Manager for Cache-Aligned Memory Optimization
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Solution Overview
Problem
As the number of managed computing resources increases, bitmap-based resource management systems require more memory space and longer search times to allocate and deallocate resources, impairing the performance of computing devices.
Innovation Solution
The implementation of flexible bitmap configurations with tree structures, including varying node sizes and tailored search directions, reduces memory usage and search times by matching node lengths to processor cache lengths, thereby optimizing resource management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the number of managed computing resources increases, then the resource management capacity increases, but the memory space required and search time increase, impairing device performance
Solution Approach 1:
The patent divides the bitmap into multiple segments or partitions, each managed independently. This segmentation allows the system to handle large numbers of computing resources by breaking down the monolithic bitmap into smaller, more manageable units, thereby reducing the time required to search and allocate resources while maintaining the capacity to manage a large total number of resources
2Quantity of substance
If the number of managed computing resources increases, then the resource management capacity increases, but the memory space required increases, impairing device performance
Solution Approach 1:
The patent implements a hierarchical bitmap structure where bitmaps are nested within parent bitmaps. This nesting allows the system to manage large numbers of computing resources efficiently by organizing bitmaps in a tree-like hierarchy, where only relevant portions of the hierarchy need to be loaded into memory at any given time, thereby reducing overall memory space requirements while maintaining the capacity to manage extensive resource pools
3Device complexity
If traditional bitmap structures are used, then implementation simplicity is maintained, but resource allocation efficiency decreases as resource numbers increase
Solution Approach 1:
The patent transitions from a traditional one-dimensional bitmap to a multi-dimensional hierarchical bitmap structure. This dimensional change introduces parent-child relationships and multiple levels of organization, enabling more efficient resource allocation by allowing searches and allocations to occur at multiple levels simultaneously. The increased structural complexity is justified by the significant improvement in allocation efficiency, as the system can quickly navigate through hierarchical levels to locate and allocate resources without examining the entire bitmap
Data Source
AI summary
Bitmaps for managing computing resources are described. Example bitmaps described in this application use less memory space by varying the sizes of the nodes in the bitmap's tree structure, and/or by limiting the number of nodes in the bitmap's leaf layer. Other example bitmaps described in this application reduce the time needed to traverse the bitmap by tailoring the search direction according to the bitmap's configuration.