Memory Workload Profiling for Remote Performance Tuning
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Solution Overview
Problem
Existing memory device management systems lack efficient remote monitoring and management capabilities based on logged event data, leading to suboptimal performance and operational inefficiencies.
Innovation Solution
A system that includes a memory device with a monitor to log commands, sensor data, and errors, which periodically uploads this data to a remote computing device for centralized analysis and management, allowing for fine-tuning of memory device operations based on performance metrics and user inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If memory devices operate autonomously without remote monitoring, then device simplicity is maintained, but performance optimization and error reduction capabilities are limited
Solution Approach 1:
The patent introduces a remote computing device as an intermediary that receives logged event data from memory devices via a network interface. This mediator performs the complex analysis and optimization tasks externally, allowing the memory device itself to remain relatively simple while still benefiting from advanced performance optimization and error reduction through centralized monitoring and feedback mechanisms.
2Productivity
If centralized remote monitoring is implemented, then performance optimization is improved, but data transmission and processing time increases
Solution Approach 1:
The system performs preliminary actions by continuously logging event data locally in the memory device before remote analysis is needed. This pre-capturing of operational data, commands, and sensor readings ensures that when remote computing devices request information, the data is already prepared and available for immediate transmission and analysis, reducing overall processing delays.
Solution Approach 2:
The monitoring system operates continuously in the background, maintaining uninterrupted logging of memory device operations. This continuous operation ensures that performance data is constantly being collected and made available for remote analysis without interrupting the primary memory functions, thereby maintaining productivity while enabling ongoing optimization.
3Measurement precision
If detailed event data is logged and transmitted, then measurement precision is improved, but data storage requirements and transmission bandwidth increase
Solution Approach 1:
The system extracts and logs only the most relevant event data, commands, and sensor readings that are necessary for performance optimization and error analysis. By selectively capturing specific high-value metrics rather than all possible data points, the system maintains high measurement precision for critical parameters while minimizing the overall volume of data that needs to be stored and transmitted to remote computing devices.
Data Source
AI summary
The disclosed embodiments relate to logging activities of memory devices and adjusting the operation of a controller based on the activities. In one embodiment, a method comprises collecting, by a memory device, profile data, the profile data associated with read and write commands and corresponding address information issued to the memory device from a host device; storing, by the memory device, the profile data in a portion of a storage array managed by the memory device; receiving, by the memory device, an update generated based on the profile data, the update adjusting a configuration setting of the memory device; and processing, by the memory device, a received command based on the configuration setting.