SSD Cache Eviction Using Host Hotness Data Across SLC and QLC
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Solution Overview
Problem
Existing memory systems face inefficiencies in managing cache evictions and insertions, leading to inconsistent performance and increased power consumption due to host-managed data management and the use of DRAM for complex algorithms, which result in performance disparities between SLC and QLC media.
Innovation Solution
Implementing a memory controller that manages cache evictions and insertions based on host-managed hotness data, using low-overhead software to keep high-priority data in SLC regions, thereby maintaining consistent performance by separating frequently accessed data from less frequently accessed data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If host manages data eviction between SLC and QLC media, then data management flexibility is improved, but power consumption increases
Solution Approach 1:
The patent introduces an intermediary mechanism (the memory controller with integrated eviction policy) that mediates between the host and the memory media. Instead of the host directly managing data eviction, the memory controller autonomously handles the eviction decisions based on integrated hotness tracking, reducing the computational burden and power consumption on the host while maintaining adaptive data management capabilities.
Solution Approach 2:
The memory controller implements self-service by autonomously managing the eviction policy without requiring continuous host intervention. The integrated hotness tracking and eviction logic enable the system to self-regulate data placement between SLC and QLC media based on actual access patterns, eliminating the need for power-consuming host-based management while maintaining adaptability.
2Speed
If SLC first algorithm is used for QLC SSDs, then write performance is improved, but read performance becomes inconsistent
Solution Approach 1:
The patent implements a dynamic eviction policy that adapts to changing access patterns rather than using a static SLC-first approach. The integrated hotness tracking continuously monitors data access patterns and dynamically adjusts eviction decisions, allowing the system to maintain both fast write performance and consistent read performance by keeping frequently accessed data in SLC and evicting cold data to QLC based on actual usage rather than predetermined rules.
Solution Approach 2:
The system incorporates feedback through integrated hotness tracking that monitors read and write patterns in real-time. This feedback mechanism allows the eviction policy to adjust data placement decisions based on actual access patterns, ensuring that data that is frequently read remains in SLC while data that is rarely accessed is evicted to QLC, thereby maintaining performance consistency across both read and write operations.
3Adaptability or versatility
If DRAM is used to hold data structures for bloom filter algorithms, then cache management capability is improved, but device complexity increases
Solution Approach 1:
The patent merges the hotness tracking functionality directly into the memory controller, eliminating the need for separate DRAM buffers and complex bloom filter algorithms. By combining the eviction policy logic and hotness tracking data structures within the memory controller itself, the system achieves effective cache management capability while reducing device complexity and eliminating the need for additional DRAM resources.
Solution Approach 2:
The patent extracts the complex bloom filter algorithm and DRAM buffer requirements from the system by implementing a simplified hotness tracking mechanism directly in the memory controller. This extraction eliminates the need for complex data structures and additional memory resources while maintaining the essential cache management capability through a more straightforward implementation.
Data Source
AI summary
Systems, apparatuses, and methods provide for a memory controller to manage cache evictions and/or insertions in a data server environment based at least in part on host managed hotness data. For example, a memory controller includes logic to receive a plurality of read and write requests from a host, where the plurality of read and write requests include an associated hotness data. A valid unit count of operational memory cells is maintained on a block-by-block basis for a plurality of memory blocks. A hotness index count is also maintained based at least in part on the hotness data on a block-by-block basis for the plurality of memory blocks. One or more memory blocks of the plurality of memory blocks are selected for eviction from a single level cell region to an x-level cell region based at least in part on the valid unit count and the hotness index count.