SSD Controller Boot Optimization via Speculative Data Rearrangement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data storage devices, such as solid state drives (SSDs), experience prolonged boot times due to inefficient storage and retrieval of necessary information during both graceful and ungraceful shutdowns, which affects their performance and the timing of executing host commands.
Innovation Solution
A data storage device with a controller that includes a boot optimization unit to collect statistics, predict data to be fetched, and rearrange data in the memory device for optimized boot operations, utilizing a central processing unit, database, and rearrangement unit to speculatively fetch and rearrange data for faster boot times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data is stored in internal memory or HMB without optimization, then the device can operate, but boot time is prolonged
Solution Approach 1:
The patent applies preliminary action by collecting statistics during the current boot operation and using them to predict and pre-arrange data fetch patterns for the next boot operation. The controller speculatively determines which data will be needed and arranges it in advance, so that when the next boot occurs, the data is already in optimal positions for rapid retrieval, thereby reducing boot time without adding operational complexity.
2Productivity
If data is fetched sequentially or inefficiently, then the boot operation can complete, but performance is reduced
Solution Approach 1:
The patent implements feedback by collecting statistics of fetched data during the boot operation and using this information to predict future data access patterns. The controller continuously monitors and learns from actual data fetch behavior, then uses this feedback to optimize subsequent data retrieval operations, creating a self-improving system that reduces boot time with each iteration.
Solution Approach 2:
The patent applies dynamics by making the data fetch pattern adaptive and changeable based on collected statistics. Rather than using a fixed sequential access pattern, the controller dynamically adjusts the data retrieval strategy based on predicted access patterns, allowing the system to optimize performance based on actual usage behavior while maintaining flexibility.
Data Source
AI summary
A data storage device includes a memory device and a controller coupled to the memory device. During a boot operation, the controller is configured to determine whether the boot is a device boot or a host boot. The controller includes a boot optimization unit. The boot optimization unit or the controller is configured to collect statistics of the fetched data, predict the data to be fetched next, and speculatively fetch the data. The controller further includes a rearrangement unit. The controller or the rearrangement unit is configured to rearrange data in the memory device based on the collect statistics of the fetched data so that the next boot operation is more optimized than the current boot operation.