Memory Power Scheduling via Operation Reordering
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Solution Overview
Problem
Memory systems, such as solid-state drives, face inefficiencies in power management due to throttling operations to avoid exceeding a maximum power threshold, resulting in suboptimal power utilization as different operations consume varying amounts of power.
Innovation Solution
Implementing a power-based operation scheduling method that reorders operations in a queue based on their power profiles to ensure that the maximum power threshold is not exceeded, allowing for more efficient power utilization by selecting alternative operations when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If operations are throttled to avoid exceeding maximum power threshold, then power consumption is controlled within limits, but power utilization efficiency deteriorates
Solution Approach 1:
The system performs preliminary classification of operations into power groups based on their power consumption profiles before execution. By pre-organizing operations into groups (e.g., high-power operations like program/erase and low-power operations like read), the system can proactively schedule operations that maximize power utilization without exceeding the threshold, rather than reactively throttling after power limits are approached.
Solution Approach 2:
The system dynamically adjusts the scheduling strategy based on the current state of the operation queue and power consumption profile. By maintaining a running total of power consumption and comparing it against the threshold, the system can adaptively select which operations to execute next, choosing from different power groups to optimize power utilization in real-time rather than using a static throttling approach.
2Ease of operation
If operations are executed in queue order, then operation simplicity is maintained, but power utilization efficiency deteriorates
Solution Approach 1:
The operation queue is segmented into multiple power groups based on the power consumption characteristics of individual operations. Instead of treating all operations uniformly, the system divides them into distinct groups (e.g., first power group for high-power operations, second power group for low-power operations) and schedules operations from different groups in an optimized sequence, thereby improving power utilization while maintaining manageable scheduling complexity.
3Power
If maximum power threshold is strictly enforced, then power consumption is controlled, but number of operations that can be performed deteriorates
Solution Approach 1:
The system changes the scheduling parameter from simple queue order to power-profile-based ordering. By reordering operations based on their power consumption characteristics and using a running total to track cumulative power consumption, the system can maximize the number of operations performed within the power threshold. This allows the system to perform more operations by strategically selecting which operations to execute next rather than simply enforcing a strict threshold without optimization.
Data Source
AI summary
A memory system and method for power-based operation scheduling are provided. In one embodiment, a memory system begins to perform a plurality of operations in an order in which they are stored in a queue. Before performing a next operation in the queue, the memory system determines whether the power consumed by performing the next operation would exceed a maximum power threshold. In response to determining that the power consumed would exceed the maximum power threshold, the memory system selects an operation out of order from the queue to perform instead, so the maximum power threshold would not be exceeded. Other embodiments are provided.