SSD Power State Management Using Usage Pattern Forecasting
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Solution Overview
Problem
Conventional computer systems inefficiently manage power usage, particularly neglecting the energy costs associated with transitions between power states in components like solid state drives, leading to unnecessary energy consumption and lack of accurate energy forecasting.
Innovation Solution
A solid state device with an array of memory units and an interface that monitors low power mode statistics, compares them to a critical usage point, and dynamically adjusts power states to minimize energy usage by entering active or low power modes based on usage frequency, updating a power state table to optimize transitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by stationary object
If the solid state drive is placed in the lowest potential operation state to minimize power usage, then power consumption is reduced, but the drive requires frequent transitions between power states which increases overall energy usage
Solution Approach 1:
The system performs preliminary actions by forecasting future energy usage based on periodic activity patterns before making power state decisions. This allows the drive to anticipate upcoming access requirements and avoid unnecessary transitions to low-power states that would require energy-intensive wake-up sequences, thereby resolving the contradiction between minimizing power consumption and avoiding transition energy losses.
Solution Approach 2:
The patent implements dynamic power state management by continuously monitoring periodic activity patterns and adjusting power state declarations in real-time. The system dynamically forecasts energy usage and adapts power state transitions based on predicted workload, allowing the drive to optimize between staying in low-power states and transitioning to active states only when truly necessary, thus balancing power consumption against transition energy costs.
2Ease of operation
If conventional systems simply place components in lowest power state without considering transition costs, then power management is simplified, but accurate energy forecasting is not achieved
Solution Approach 1:
The system implements feedback mechanisms by monitoring actual periodic activity patterns and using this information to refine energy usage forecasts. The forecasted energy usage data feeds back into power state management decisions, creating a closed-loop system that continuously improves accuracy. This allows the system to maintain relatively simple operation while achieving precise energy forecasting through iterative learning from observed patterns.
3Speed
If the solid state drive transitions frequently between power states to respond to periodic activity, then responsiveness is improved, but overall energy efficiency deteriorates due to transition costs
Solution Approach 1:
By forecasting energy usage based on periodic activity patterns before transitions occur, the system can determine in advance whether a power state transition is truly necessary. This preliminary assessment allows the drive to maintain responsiveness to genuine activity while avoiding unnecessary transitions that would waste energy, thus resolving the contradiction between responsiveness and energy efficiency.
Solution Approach 2:
The system dynamically adjusts power state transitions based on forecasted energy usage and observed periodic patterns. Rather than using fixed transition rules, the system adapts its responsiveness behavior dynamically, transitioning to active states only when the forecast indicates actual workload is approaching, thereby maintaining necessary responsiveness while minimizing transition-related energy losses.
Data Source
AI summary
A solid state device is disclosed comprising an array of memory units, an interface connected to the memory units, at least one arrangement to monitor a temperature of the solid state device and an arrangement to monitor low power mode statistics of the solid state device and compare the low power mode statistics to a critical usage point power threshold at a temperature measured, wherein the arrangement to monitor the low power mode statistics of the solid state device is further configured to change a power mode of the solid state device based upon the low power mode statistics.