Virtual Address Space Metadata Management for Unequal Granularity
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Solution Overview
Problem
Current software management layers for virtual address spaces require significant metadata storage and do not allow for direct access when dealing with unequal granularity and alignment, leading to inefficiencies in data management.
Innovation Solution
A method that identifies data writes within a virtual address space, determines corresponding entries in a metadata structure, and adds state information including size and alignment, allowing for efficient management and direct access by merging or adjusting entries as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current management layer implementations are used to track virtual address space usage, then comprehensive tracking capability is achieved, but metadata storage consumption increases significantly
Solution Approach 1:
The patent segments the address space into multiple regions, each with its own metadata structure. Instead of maintaining a single comprehensive metadata structure for the entire address space, the system divides it into region-specific metadata structures that can be managed independently, reducing overall metadata storage requirements while maintaining tracking capability.
Solution Approach 2:
The patent inverts the traditional approach by having the metadata structure adapt to the data rather than the data conforming to fixed metadata requirements. The system allows metadata entries to be dynamically created and merged based on actual data access patterns, reducing metadata overhead by only creating entries when necessary.
2Productivity
If direct access is enabled for virtual address spaces with unequal granularity and alignment, then access efficiency improves, but system complexity increases
Solution Approach 1:
The patent implements dynamic metadata structures that can adapt their granularity and alignment based on the specific data being accessed. Rather than using fixed-size metadata entries, the system dynamically adjusts metadata structure to match the actual data patterns, enabling direct access for unequal granularity while managing complexity through adaptive rather than static structures.
Solution Approach 2:
The system changes metadata parameters such as entry size, granularity, and alignment dynamically based on the data being accessed. This allows the metadata structure to optimize for direct access in specific scenarios while maintaining the ability to handle unequal granularity and alignment, rather than being constrained by fixed parameters.
3Quantity of substance
If metadata structure size is reduced to decrease storage consumption, then storage efficiency improves, but access speed may decrease
Solution Approach 1:
By segmenting the metadata structure into region-specific components, the system reduces the size of individual metadata structures that need to be accessed, improving access speed for specific regions while the overall system maintains comprehensive tracking. Each segment can be accessed independently, reducing the time to retrieve relevant metadata.
Solution Approach 2:
The system performs preliminary actions by pre-organizing metadata into merged entries based on anticipated access patterns. This preliminary organization allows for faster access during actual data operations, as the metadata is already structured optimally rather than requiring processing at access time.
Data Source
AI summary
A computer-implemented method according to one embodiment includes identifying a data write to a specific position within a virtual address space, determining an entry within a metadata structure that corresponds to the specific position within the virtual address space, and adding state information associated with the data write to the entry within the metadata structure, the state information including a size of the data write within the virtual address space and an alignment of the data write within the virtual address space.