Memory Controller Performance Manager for Dynamic Resource Allocation
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Solution Overview
Problem
Memory systems, such as solid-state drives, face challenges in optimizing performance based on varying user preferences and usage patterns, as existing technologies lack efficient methods to dynamically allocate resources for different operation profiles like read intensity, write intensity, and durability.
Innovation Solution
A performance manager is implemented within the memory system to track usage statistics and adjust resource allocation based on predicted workloads and user preferences, utilizing configuration profiles to optimize performance by selecting and generating settings that balance resource usage for specific performance goals, such as read intensity, write intensity, or durability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If resource allocation is fixed in the memory system, then device complexity is reduced, but adaptability to different performance goals (read intensity, write intensity, durability) deteriorates
Solution Approach 1:
The patent implements dynamic resource allocation by allowing the memory system to switch between different configuration profiles (performance profiles) based on predicted workloads. The system can dynamically adjust resource distribution for read operations, write operations, and durability based on user preferences and usage patterns, transforming a static system into an adaptive one without requiring complete system redesign.
Solution Approach 2:
The system changes operational parameters by selecting different configuration profiles that define resource allocation settings. Each profile specifies parameters such as read intensity, write intensity, and durability weights, allowing the memory system to modify its behavior by changing these parameters rather than redesigning the entire architecture.
2Adaptability or versatility
If the memory system tracks usage statistics and adjusts resource allocation dynamically, then adaptability to user preferences improves, but device complexity increases
Solution Approach 1:
The system implements feedback mechanisms by tracking usage statistics (read operations, write operations, durability metrics) and using this information to predict future workloads. The performance manager uses this feedback to adjust resource allocation by selecting appropriate configuration profiles, creating a closed-loop system that adapts to user preferences based on actual usage patterns.
Solution Approach 2:
The system performs preliminary actions by predicting future workloads based on historical usage statistics before actual operations occur. The performance manager proactively selects and applies appropriate configuration profiles in advance, allowing the system to be optimized for anticipated performance goals rather than reacting to usage patterns after they occur.
3Adaptability or versatility
If multiple configuration profiles are implemented for different performance goals, then adaptability improves, but device complexity increases
Solution Approach 1:
The patent implements multi-functionality by creating a unified performance manager that handles multiple performance goals (read intensity optimization, write intensity optimization, durability optimization) through a single framework. The system uses a common set of configuration profiles that can be selected based on different performance goals, allowing one management mechanism to serve multiple purposes without requiring separate specialized systems for each optimization type.
Data Source
AI summary
A memory system having a set of media, a set of resources, and a controller configured via firmware to use the set of resources in processing requests from a host system to store data in the media or retrieve data from the media. The memory system has a performance manager that identifies settings for allocations of the resources in the processing of the requests based on a user identified preference and optionally further based on operation statistics of the memory system.