Storage Controller Read Prediction Cache Management
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Solution Overview
Problem
Existing storage systems face inefficiencies in random read performance, particularly in low-queue-depth environments, due to the immediate eviction of pre-fetched data when the next read command does not match the predicted command, leading to wasted resources and degraded performance.
Innovation Solution
Implementing a hit-rate based cache management system that maintains pre-fetched data in volatile memory even if the immediate next read command does not match the predicted command, using a prediction cache buffer to evacuate commands with minimal prediction scores and optimizing pattern lengths for read prediction, along with time-based enhancements to predict the expected arrival time of next random read commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If pre-fetched data is immediately evicted when the next read command does not match the predicted command, then memory space is freed for new data, but resource wastage increases and performance degrades
Solution Approach 1:
The patent applies dynamics by transitioning from static immediate eviction policy to dynamic cache management based on hit-rate thresholds. The system adaptively adjusts cache retention behavior according to predicted accuracy, maintaining pre-fetched data when prediction confidence is high and eviction when confidence is low, thereby optimizing the balance between resource utilization and performance
Solution Approach 2:
The patent changes the parameter of cache management from binary (evict immediately or keep indefinitely) to continuous by introducing hit-rate thresholds. The system monitors prediction accuracy metrics and adjusts cache retention policies based on these measured parameters, allowing fine-grained control over when to evict pre-fetched data
2Productivity
If pre-fetched data is maintained in volatile memory for later use, then random read performance improves, but memory resources are consumed and power usage increases
Solution Approach 1:
The patent applies partial action by selectively maintaining only those pre-fetched data entries that meet the hit-rate threshold criteria in volatile memory. Rather than maintaining all pre-fetched data or evicting all, the system performs partial retention based on prediction accuracy, optimizing the trade-off between performance gain and resource consumption
Solution Approach 2:
The patent extracts high-value pre-fetched data entries (those with high predicted hit-rates) and maintains them in volatile memory, while leaving low-value entries to be evicted. This selective extraction approach ensures that only the most beneficial data consumes additional memory resources, maximizing performance per unit of resource consumed
3Measurement precision
If prediction cache buffer is used to evacuate commands with minimal prediction scores, then prediction accuracy improves, but device complexity increases
Solution Approach 1:
The patent introduces a prediction cache buffer as an intermediary data structure between the read command stream and the cache eviction decision logic. This intermediary component simplifies the overall system by centralizing prediction score tracking and hit-rate calculation in one location, making the complex eviction policy more manageable and implementable
Data Source
AI summary
A storage system has a volatile memory, a non-volatile memory, and a controller. The controller of the storage system can implement various mechanisms for improving random read performance. These mechanisms include improved read prediction cache management, using a pattern length for read prediction, and a time-based enhancement for read prediction. Each of these mechanisms can be used alone on in combination with some or all of the other mechanisms.