Dynamic Power Routing for Hardware Accelerators
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Data centers face challenges in efficiently managing power consumption due to the high energy demands of both central processing units (CPUs) and hardware accelerators, leading to costly and wasteful electrical power delivery systems, as traditional power provisioning components are often rated below the aggregate power consumption of these components when all are utilized simultaneously.
Innovation Solution
Dynamic power routing is employed to redirect power from less busy components like CPUs to hardware accelerators, which can perform specific tasks more efficiently, by determining the optimal distribution based on current and anticipated power consumption, workload priority, and other factors, allowing for proactive or reactive power adjustments to stay within power thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electrical power delivery components are sized to accommodate maximum power consumption of both CPUs and hardware accelerators simultaneously, then power supply reliability is improved, but system cost and waste increase
Solution Approach 1:
The patent implements dynamic power routing that allows the power delivery system to adapt its behavior based on real-time power consumption patterns. The system dynamically determines which components receive power and at what levels, transitioning from static power provisioning to dynamic control that matches actual hardware needs, thereby avoiding over-provisioning while ensuring reliability.
Solution Approach 2:
The system changes power allocation parameters dynamically based on workload characteristics. By monitoring and predicting power consumption patterns, the system adjusts power delivery parameters in real-time, allocating more power to hardware accelerators when needed and reducing power to CPUs or other components, thus optimizing the balance between reliability and energy efficiency.
2Productivity
If hardware accelerators are added to existing servers with fixed power delivery components, then processing capability is improved, but power consumption exceeds maximum rated power
Solution Approach 1:
The patent segments the power allocation by creating distinct power paths and control mechanisms for different hardware components. By separating power management for CPUs, hardware accelerators, and other components, the system can independently control power to each component type, allowing hardware accelerators to receive additional power without exceeding the overall system power rating.
Solution Approach 2:
The system introduces an intermediary power management layer that mediates between the fixed power delivery infrastructure and the variable power demands of hardware accelerators. This intermediary layer predicts and regulates power consumption, enabling hardware accelerators to be added to existing servers while maintaining compliance with maximum rated power limits through proactive power allocation decisions.
3Loss of energy
If power is routed dynamically to hardware accelerators, then power utilization efficiency is improved, but power routing complexity increases
Solution Approach 1:
The patent implements self-service power management where the power routing system automatically makes decisions based on built-in monitoring and prediction mechanisms. The system self-adjusts power allocation without requiring complex external control, using internal sensors and algorithms to predict power needs and route power accordingly, thereby reducing operational complexity while maintaining high efficiency.
Solution Approach 2:
The system employs feedback mechanisms where power consumption data from hardware accelerators and other components is continuously monitored and fed back to the power routing decisions. This closed-loop feedback allows the system to learn from actual usage patterns and refine its power allocation strategies, making the complexity management more intelligent and adaptive rather than purely algorithmic.
Data Source
AI summary
Dynamic power routing is utilized to route power from other components, which are transitioned to lower power consuming states, in order to accommodate more efficient processing of computational tasks by hardware accelerators, thereby staying within electrical power thresholds that would otherwise not have accommodated simultaneous full-power operation of the other components and such hardware accelerators. Once a portion of a workflow is being processed by hardware accelerators, the workflow, or the hardware accelerators, can be self-throttling to stay within power thresholds, or they can be throttled by independent coordinators, including device-centric and system-wide coordinators. Additionally, predictive mechanisms can be utilized to obtain available power in advance, by proactively transitioning other components to reduced power consuming states, or reactive mechanisms can be utilized to only transition components to reduced power consuming states when a specific need for increased hardware accelerator power is identified.