Read Look Ahead Data Size Determination for Memory Systems
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Solution Overview
Problem
Conventional memory systems face inefficiencies in data retrieval due to incorrect predictions of access patterns, leading to wastage of computing resources and reduced performance, especially in low queue depth environments where parallelism is limited.
Innovation Solution
The memory system determines an optimal size for read look ahead data to prefetch, based on the identified pattern of read requests and the architecture of the memory device, ensuring efficient data retrieval without excessive resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If read look ahead data is prefetched based on predicted access patterns, then data retrieval performance is improved, but computing resources are wasted when predictions are incorrect
Solution Approach 1:
The system dynamically adjusts the read look ahead data size based on detected access patterns and queue depth conditions. When sequential access patterns are detected and queue depth is low, a larger read look ahead size is used to maximize parallelism. When patterns are not detected or queue depth is high, the size is reduced to minimize resource waste, thereby adaptively resolving the contradiction between performance improvement and resource consumption.
Solution Approach 2:
The patent changes the parameter of read look ahead data size based on detected access patterns and operational conditions. By modifying this parameter dynamically rather than using a fixed size, the system optimizes the balance between prefetching benefits and resource consumption, achieving high performance only when beneficial while avoiding waste during normal operations.
2Productivity
If larger read look ahead data size is used to enable multi-plane parallelism, then throughput is improved, but latency increases due to retrieving excessive data
Solution Approach 1:
The system applies partial action by retrieving only the necessary amount of read look ahead data required to enable multi-plane parallelism rather than always retrieving maximum possible data. This ensures sufficient data is fetched to achieve parallelism benefits while avoiding the latency penalty of retrieving excessive data that won't be immediately used.
3Productivity
If read look ahead is enabled in low queue depth environments, then parallelism is improved, but resource overhead increases
Solution Approach 1:
The system dynamically enables or disables read look ahead operations based on detected queue depth conditions. In low queue depth environments where parallelism can be effectively utilized, read look ahead is enabled with appropriate data sizing. In high queue depth environments where the memory system is already busy handling multiple operations, read look ahead is disabled to avoid unnecessary resource overhead, thus adaptively resolving the contradiction between parallelism improvement and overhead introduction.
Data Source
AI summary
A method can include receiving a read request from a host system, determining, by a processing device, a size of data to retrieve that corresponds to an operation on a memory system, such that the size of the data is based on a die-level transfer size determined from a specification of a die of the memory system, and providing an indication for the memory system to retrieve the data at the determined size.