Dynamic SSD Memory Operation Scheduling for Power Budget Control
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Solution Overview
Problem
Modern SSDs face challenges in dynamically controlling power consumption due to the asymmetric latency and power consumption characteristics of NAND flash memory, leading to inefficiencies in operation scheduling and increased power usage, especially in high-performance devices like NVMe devices in data centers and consumer electronics.
Innovation Solution
A dynamic memory operation scheduler that receives and reorders memory operations based on power consumption estimates, moving less power-intensive operations to time windows where the power budget is exceeded, thereby optimizing power usage and preventing excessive consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple NAND operations are executed simultaneously to hide high latency, then programming and erasing speed is improved, but power consumption increases
Solution Approach 1:
The patent implements dynamic operation scheduling that adjusts the degree of parallelism and operation timing based on real-time power consumption conditions. The memory controller dynamically selects between aggressive parallel execution (when power headroom exists) and conservative sequential execution (when power budget is constrained), allowing the system to optimize the trade-off between productivity and power consumption adaptively
Solution Approach 2:
The system changes operational parameters such as the number of simultaneous operations, operation duration, and timing based on power consumption thresholds. By monitoring power usage and adjusting these parameters dynamically, the system can maintain high productivity when power is abundant while reducing power consumption when necessary, directly addressing the contradiction between speed and energy use
2Productivity
If high-performance NVMe devices are used to improve data processing speed, then productivity is improved, but power consumption increases significantly
Solution Approach 1:
The patent introduces dynamic power management for NVMe devices that adjusts operational intensity based on workload demands and power availability. The memory controller monitors power consumption in real-time and dynamically scales the degree of parallelism, operation frequency, and resource allocation, enabling the system to achieve high productivity when power is available while consuming minimal power during low-utilization periods
Solution Approach 2:
The system implements periodic monitoring and adjustment of power consumption levels, using time-based windows to evaluate power usage and adjust scheduling strategies. This periodic control allows the system to maintain high performance during active periods while entering low-power states during idle or low-utilization periods, addressing the contradiction between sustained high performance and average power consumption
3Productivity
If aggressive operation scheduling is used to maximize throughput, then productivity is improved, but thermal and electrical stress on components increases
Solution Approach 1:
The patent implements preliminary monitoring and protective scheduling that anticipates thermal and electrical stress conditions. By monitoring power consumption trends and operational intensity, the system proactively adjusts scheduling aggressiveness before stress levels become harmful, preventing excessive thermal buildup and electrical stress while maintaining high throughput during safe operating conditions
Solution Approach 2:
The system uses feedback mechanisms that continuously monitor power consumption, thermal conditions, and component stress levels to adjust operation scheduling in real-time. This closed-loop control allows the system to maintain high productivity when conditions permit while automatically reducing operational intensity when thermal or electrical stress approaches harmful thresholds, directly addressing the contradiction between throughput and component stress
Data Source
AI summary
A memory device and a method for rescheduling memory operations is disclosed. The method includes receiving memory operations for memory arrays of a memory device; storing the memory operations in queues associated with the memory array; estimating power consumption for each of the memory operations queued in the queues based on a power model; determining that a memory operation causes an estimated power consumption of the memory device to be exceeded over an allowable power budget within a first time window; determining a candidate memory operation in the queues that is scheduled to operate in a second time window after the first time window, wherein the candidate memory operation has less power consumption than the memory operation according to the power model; and dynamically reordering the memory operations in the queues and generating rescheduled memory operations by reordering the memory operation out of the first time window and reordering the candidate memory operation into the first time window.