Super Block Capacity Tuning for Lower GC Load in Flash Memory
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing flash-based memory systems face high probabilities of critical requests being blocked due to the increased capacity of super blocks, leading to elevated GC loads and performance degradation as memory processes improve, especially with the integration of unified storage and zoned name spaces.
Innovation Solution
Dynamically configure the capacity of super blocks based on the type of target data and memory parameters, adjusting the size of logical address space sections to match the super block capacity, thereby reducing the probability of critical request blocking and optimizing GC efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the capacity of super block is increased to meet future memory process improvements, then the storage capacity is improved, but the GC load increases and performance deteriorates
Solution Approach 1:
The patent applies dynamics by making the super block capacity adjustable rather than fixed. The file system dynamically configures the capacity of sections (which correspond to super blocks) based on the type of target data and memory parameters. This allows the system to adapt super block size to different workloads, reducing GC load for certain data types while maintaining high capacity where needed, thus resolving the contradiction between large capacity and performance.
Solution Approach 2:
The patent changes the parameter of super block capacity from a fixed value to a configurable parameter. By allowing the file system to configure section capacity based on data characteristics (hot, warm, cold data) and memory parameters, the system can optimize performance for different scenarios. This parameter change enables the same memory to achieve both large capacity and acceptable GC load by using smaller super blocks for data types that benefit from frequent GC operations.
2Device complexity
If the capacity of section is kept constant in file system, then the management simplicity is maintained, but it cannot adapt to different data types and memory parameters
Solution Approach 1:
The patent changes the section capacity from a constant parameter to a configurable parameter. The file system now configures section capacity based on the type of target data (hot, warm, cold) and memory parameters. This allows the same file system to adapt to different data types and memory configurations without requiring fundamentally different management mechanisms, thus improving adaptability while maintaining reasonable complexity.
Solution Approach 2:
The patent applies local quality by allowing different sections to have different capacities based on their specific needs. Instead of using a uniform section capacity across all data, the system configures appropriate capacities for different data types and memory parameters. This localized optimization enables the file system to handle diverse workloads effectively while keeping the overall management framework relatively simple.
3Productivity
If unified storage and zoned name spaces are integrated to reduce write amplification, then the write efficiency is improved, but the probability of critical request blocking increases
Solution Approach 1:
The patent applies local quality by configuring different section capacities for different data types. Hot data (critical requests) can be assigned to sections with capacities optimized for fast access and low blocking probability, while cold data can use larger sections that maximize storage efficiency. This localized optimization allows the unified storage system to maintain high write efficiency overall while ensuring critical requests experience minimal blocking.
Solution Approach 2:
The patent changes the section capacity parameter based on data characteristics. By configuring appropriate capacity values for different data types, the system can optimize both write efficiency and critical request performance. The configurable parameter approach allows the same unified storage architecture to achieve both high productivity and reliability by adapting parameters to workload requirements.
Data Source
AI summary
This application discloses a super block management method and apparatus. An example method includes: obtaining a parameter of a memory and a type of target data, where the target data is data to be written into the memory; configuring a capacity of a section in a file system based on at least one of the type of the target data or the parameter of the memory, where the configured capacity of the section matches a capacity of a super block in the memory; and managing, based on the configured capacity of the section, a logical address space corresponding to the memory.