Cache Memory Bucket Reclamation by Weight Class
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing cache management systems face inefficiencies in reclaiming memory resources, as the process of identifying and freeing up memory resources to accommodate new data is time-consuming, especially when a large quantity of resources needs to be reclaimed.
Innovation Solution
The system partitions cache memory resources into subsets based on weight classes and age, allowing for asynchronous reclamation of buckets of memory resources, prioritizing the least recently accessed data to free up space efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If memory resources are reclaimed sequentially one by one, then the reclamation process is simple to implement, but the time required to reclaim memory resources increases significantly
Solution Approach 1:
The patent divides memory resources into multiple buckets based on access patterns and data characteristics. Instead of reclaiming memory sequentially, the system identifies and reclaims entire buckets of memory resources simultaneously, significantly reducing the time required for reclamation while maintaining organized management through the bucket segmentation structure
Solution Approach 2:
The system performs preliminary classification of memory resources into buckets based on access patterns before reclamation is needed. This pre-organization allows the system to quickly identify which buckets contain least recently accessed data and reclaim them efficiently without having to analyze individual memory resources at reclamation time
2Quantity of substance
If all memory resources are reclaimed to accommodate new data, then space for new data is ensured, but important data may be lost
Solution Approach 1:
The patent applies different reclamation priorities to different buckets of memory resources based on their characteristics and access patterns. Buckets containing frequently accessed or important data are marked with higher retention priorities and are reclaimed less aggressively, while buckets with less important data are reclaimed more readily, ensuring space for new data while preserving important information
Data Source
AI summary
A method may include dividing, into a first portion of memory resources and a second portion of memory resources, a plurality of memory resources included in a cache coupled with a database. The plurality of memory resources included in the cache may store data from the database. The first portion of memory resources may be occupied by data assigned to a first weight class. The second portion of memory resources may be occupied by data assigned to a second weight class. The first portion of memory resources may be selected based at least on the first weight class and an age of at least some of the data occupying the first portion of memory resources. In response to the selection of the first portion of memory resources, the first portion of memory resources may be reclaimed. Related systems and articles of manufacture, including computer program products, are also provided.