Memory Region Segmentation for Adaptive Power Scaling
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Solution Overview
Problem
Existing electronic device processor power management systems face challenges in efficiently managing power consumption, particularly due to high thermal design power (TDP) and significant energy usage by memory subsystems.
Innovation Solution
Implementing a memory region life-cycle based power management system that allocates short-term memory requests to short-term memory regions, which are powered down when the memory requests expire, and scales up or down multiple memory regions based on demand to optimize power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If memory subsystem is fully populated to meet compute requirements, then memory capacity and bandwidth are improved, but power consumption increases significantly (150-200 W for 16 DIMMs)
Solution Approach 1:
The memory subsystem is divided into multiple independent memory regions (first memory region, second memory region, etc.), each capable of being independently powered down. This segmentation allows the system to maintain only the necessary memory regions active based on current workload, reducing overall power consumption while preserving the ability to scale memory capacity when needed.
Solution Approach 2:
The memory architecture implements dynamic power management where memory regions can be transitioned between active and powered-down states based on real-time compute requirements. The system dynamically allocates memory resources by activating additional regions only when compute tasks require them, and powering them down when not in use, creating an adaptive power-capacity balance.
2Speed
If higher-speed interconnects such as CXL slots with additional memory are added, then memory bandwidth and capacity are improved, but power consumption increases by an additional 100 W
Solution Approach 1:
The interconnect architecture is segmented into multiple independent regions that can be selectively activated. High-speed interconnects like CXL slots are configured as separate memory regions that can be powered on only when applications require enhanced bandwidth or capacity, allowing the system to achieve peak performance when needed while minimizing power consumption during normal operation.
Solution Approach 2:
The system changes operational parameters by transitioning memory regions between different power states (active, standby, powered-down) based on workload demands. This parameter change approach allows the system to optimize the balance between memory bandwidth, capacity, and power consumption by adjusting the active state of each region according to real-time requirements.
3Use of energy by moving object
If memory regions are powered down to reduce power consumption, then power usage is improved, but memory bandwidth and capacity availability may be reduced
Solution Approach 1:
The memory power management system incorporates feedback mechanisms that monitor compute workload requirements and automatically adjust the power state of memory regions accordingly. When compute tasks require additional bandwidth or capacity, the system detects this demand and activates the necessary memory regions, ensuring that performance is maintained when needed while achieving power savings during lower-demand periods.
Solution Approach 2:
The memory architecture is designed with universal regions that can serve multiple functions and different compute workloads. Each memory region is capable of handling various types of memory operations and can be dynamically allocated to different applications based on demand, allowing the system to maximize the utility of each region and reduce the need for dedicated memory allocations.
Data Source
AI summary
The platform data aging for adaptive memory scaling described herein provides technical solutions for technical problems facing power management for electronic device processors. Technical solutions described herein include improved processor power management based on a memory region life-cycle (e.g., short-lived, long-lived, static). In an example, a short-term memory request is allocated to a short-term memory region, and that short-term memory region is powered down upon expiration of the lifetime of all short-term memory requests on the short-term memory region. Multiple memory regions may be scaled down (e.g., shut down) or scaled up based on demands for memory capacity and bandwidth.